A reasonably recent version of my CV can be downloaded here [pdf].

List of Publications, Dr Bernhard Kainz

In Computer Science peer reviewed full papers at leading, top-ranked conferences are as important and sometimes more selective as journal publications. See e.g.,http://bit.ly/2KzvvyZ or http://bit.ly/2ptl1tF for a discussion of this topic.

My research about human centred AI in health care is at the interface of Computer Science, Medical Image Analysis, Machine Learning and Clinical Science. Thus, both, journal and conference publications count equally much, and I have a good record in both categories.

The leading journals in my area are IEEE Transactions on Medical Imaging (IEEE Trans Med Imag), Elsevier Medial Image Analysis (Med Image Anal) and from a machine learning perspective the Journal of Machine Learning Research (JMLR). The leading conference is the international Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) and its associated workshops.

Currently, machine learning related research is done at an extremely fast pace. Like in Physics and Maths, preprints, e.g. on arXiv.org that have not been fully peer reviewed are important in our field. For example, according to google scholar, two of my most cited papers are preprints that have only been published later as fully peer reviewed journal publications. Interestingly, authors predominantly post works on arXiv that are of high enough quality to likely pass peer-review. Most of these papers are accepted after peer review at a later point.

Publicly available online preprints and source code repositories foster open science and are becoming more and more important in Computer Science especially in Machine Learning related domains; thus, these contributions are listed as well.

Due to my proximity to the healthcare sector and bioengineering domain I also co-author publications in clinical top journals such as The Lancet and bioengineering journals like the Elsevier Journal of Biomechanics (J Biomech).

Besides traditional publication formats, challenges (public competitions) are a common way in medical image analysis to benchmark algorithms against each other. Winning one of these competitions is highly prestigious.

There are no strict rules for author positions in my area of Computer Science. Significant contribution to the content of the paper is a must for co-authorship. Usually, Ph.D. students are preferred for the first author position and student/post-doctoral contributors follow. Principal investigators share the last author positions, sorted by their institutional supervision relationship to the first author and seniority. I have contributed in all of these roles as evident in the (automatically generated) list below.

Peer reviewed journal papers:

1. Kainz B, Heinrich MP, Makropoulos A, Oppenheimer J, Mandegaran R, Sankar S, Deane C, Mischkewitz S, Al-Noor F, Rawdin AC, Ruttloff A., Curry N., Non-invasive diagnosis of deep vein thrombosis from ultrasound imaging with machine learning. NPJ Digital Medicine. 2021 Sep 15;4(1):1-8.

2. Budd S, Robinson EC, Kainz B. A survey on active learning and human-in-the-loop deep learning for medical image analysis. Medical Image Analysis. 2021 Apr 9:102062.

3. Day TG, Kainz B, Hajnal J, Razavi R, Simpson JM. Artificial intelligence, fetal echocardiography, and congenital heart disease. Prenatal Diagnosis. 2021 May;41(6):733-42.

4. Dou Q, So TY, Jiang M, Liu Q, Vardhanabhuti V, Kaissis G, Li Z, Si W, Lee HH, Yu K, Feng Z., Kainz B., Rueckert D., Glocker B., Yu SCH, Heng PA, Federated deep learning for detecting COVID-19 lung abnormalities in CT: a privacy-preserving multinational validation study. NPJ digital medicine. 2021 Mar 29;4(1):1-1.

5. Meng, Q., Matthew, J., Zimmer, V.A., Gomez, A., Lloyd, D.F.A., Rueckert, D., Kainz, B., “Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging.” IEEE Transactions on Medical Imaging. 2020 Nov 3;40(2):722-34.

6. Miolane, N., Guigui, N., Le Brigant, A., Mathe, J., Hou, B., Thanwerdas, Y., Heyder, St., Peltre, O., Koep, N., Zaatiti, H., Hajri, H., Cabanes, Y., Gerald, Th., Chauchat, P., Shewmake, Ch., Brooks, D., Donnat, C., Kainz, B., Pennec, X., "Geomstats: A Python Package for Riemannian Geometry in Machine Learning", Editors: Francis Bach, David Blei, and Bernhard Schölkopf, To appear in Journal of Machine Learning Research (JMLR) 2020

7. Jiang, G., Kainz, B., “Deep Radiance Caching: Convolutional Autoencoders Deeper in Ray Tracing”. Computers & Graphics. 2020 Oct 7. Volume 94, February 2021, Pages 22-31 (reproducibility stamp award)

8. Robinson, R., Valindria, V.V., Bai, W., Oktay, O., Kainz, B., Suzuki, H., Sanghvi, M.M., Aung, N., Paiva, J.M., Zemrak, F., Fung, K., Lukaschuk, E., Lee, A.M., Carapella, V., Kim, Y.J., Piechnik, St.K., Neubauer, St., Petersen, St.E., Page, Ch., Matthews, P.M., Rueckert, D., Glocker, B., “Automated quality control in image segmentation: application to the UK Biobank cardiovascular magnetic resonance imaging study.” Journal of Cardiovascular Magnetic Resonance. 2019 Dec 1;21(1):18.

9. Matthew, J., Deprez, M., Uus, A., Holder, M., McCabe, L., Van Poppel, M., Skelton, E., Smith, S., Sankaran, S., Wright, R., Patkee, P.A., Kainz, B., Hajnal, J., Rutherford, M., “Syndromic craniofacial dysmorphic feature assessment in utero: potential for a novel imaging methodology with reconstructed 3D fetal MRI models.” Ultrasound in Obstetrics & Gynecology. 2019 Oct;54:29-.

10. Meng, Q., Sinclair, M., Zimmer, V., Hou, B., Rajchl, M., Toussaint, N., Oktay, O., Schlemper, J., Gomez ,A., Housden, J., Matthew, J., Rueckert, D., Schnabel, J., Kainz, B., “Weakly supervised estimation of shadow confidence maps in fetal ultrasound imaging.” IEEE Trans Med Imag. 2019 Apr 25;38(12):2755-67.

11. Lloyd, D.F.A., Pushparajah, K., Simpson, J.M., Van Amerom, J.F., Van Poppel, M.P., Schulz, A., Kainz, B., Deprez, M., Lohezic, M., Allsop, J., Mathur, S., Bellsham-Revell, H., Vigneswaran, T., Charakida, M., Miller, O., Zidere, V., Sharland, G., Rutherford, M., Hajnal, J.V., Razavi, R., “Three-dimensional visualisation of the fetal heart using prenatal MRI with motion-corrected slice-volume registration: a prospective, single-centre cohort study.” The Lancet. 2019 Apr 20;393(10181):1619-27.

12. Schlemper, J., Oktay, O., Schaap, M., Heinrich, M., Kainz, B., Glocker, B., Rueckert, D., “Attention gated networks: Learning to leverage salient regions in medical images.” Medical image analysis. 2019 Apr 1;53:197-207.

13. Alansary, A., Oktay, O., Li, Y., Le Folgoc, L., Hou, B., Vaillant, G., Kamnitsas, K., Vlontzos, A., Glocker, B., Kainz, B., Rueckert, D., “Evaluating reinforcement learning agents for anatomical landmark detection.” Medical image analysis. 2019 Apr 1;53:156-64.

14. Castro, D.C., Tan, J., Kainz, B., Konukoglu, E., Glocker, B., “Morpho-Mnist: Quantitative assessment and diagnostics for representation learning.” Journal of Machine Learning Research. 2019;20(178):1-29.

15. Bai, W., Sinclair, M., Tarroni, G., Oktay, O., Rajchl, M., Vaillant, G., Lee, A.M., Aung, N., Lukaschuk, E., Sanghvi, M. M., Zemrak, F., Fung, K., Paiva, J.M., Carapella, V., Kim, Y.J., Suzuki, H., Kainz, B., Matthews, P.M., Petersen, St. E., Piechnik, St. K., Neubauer, St., Glocker, B., Rueckert, D., “Automated cardiovascular magnetic resonance image analysis with fully convolutional networks”. Journal of Cardiovascular Magnetic Resonance. 2018 Dec 1;20(1):65.

  1. Oktay, O., Ferrante , E., Kamnitsas , K., Heinrich, M., Bai, W., Caballero, J., Cook, S. A., de Marvao, A., Dawes, T., O’Regan, D. P., Kainz, B., Glocker, B., and Rueckert, D., “ Anatomically Constrained Neural Networks (ACNNs): Application to Cardiac Image Enhancement and Segmentation ” IEEE Trans. Med Imag 37, (2018), 384-395.
  2. Lloyd, D. F. A., van Poppel, M., Schultz, A., Pushparajah, K., Simpson, J., van Amerom, J.F.P., Kainz, B., Kuklisova-Murgasova, M., Vigneswaran, T., Charakida, M., Miller, O., Zidere, V., Sharland, G., Rutherford, M., Hajnal, J., and Razavi, R., “ Motion corrected fetal cardiac MRI increases diagnostic confidence in clinically” challenging cases , Heart 104, (2018), A11–A11
  3. Verbruggen, St. W., Kainz, B., Shelmerdine, S. C., Hajnal, J. V., Rutherford, M. A, Arthurs, O. J., Phillips, A. T. M., and Nowlan, N. C., “ Stresses and strains on the human fetal skeleton during development ”, J. Royal Soc. Interface 15(138), (2018), 20170593
  4. Verbruggen, S.W., Kainz, B., Shelmerdine, S.C., Arthurs, O.J., Hajnal, J.V., Rutherford, M.A., Phillips, A.T., and Nowlan, N.C., "Altered biomechanical stimulation of the developing hip joint in presence of hip dysplasia risk factors", J Biomech 78, (2018), 1 - 9
  5. Hou, B., Khanal, B., Alansary, A., McDonagh, St., Davidson, A., Rutherford, M., Hajnal, J. V., Rueckert, D., Glocker, B., and Kainz, B., “ 3-D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images ”, IEEE Trans Med Imag 37, (2018), 1737-1750
  6. Alansary, A., Rajchl, M., McDonagh, S. G., Murgasova, M., Damodaram, M., Lloyd, D. F. A., Davidson, A., Rutherford, M., Hajnal, J. V., Rueckert, D., and Kainz, B., “ PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI ”, IEEE Trans Med Imag 36, (2017), 2031-2044
  7. Miao, H., Mistelbauer, G., Karimov, A., Alansary, A., Davidson, A., Lloyd, D. F. A., Damodaram, M., Story, L., Hutter, J., Hajnal, J. V., Rutherford, M., Preim, B., Kainz, B., and Gröller, M. E., “ Placenta Maps: In Utero Placental Health Assessment of the Human Fetus ”, IEEE Trans Vis Comput Grap 23, (2017),1612-1623
  8. Rajchl, M., Lee, M. C. H., Oktay, O., Kamnitsas, K., Passerat-Palmbach, J., Bai, W., Damodaram, M., Rutherford, M. A., Hajnal, J. V., Kainz, B., and Rueckert, D., “ DeepCut: Object Segmentation From Bounding Box Annotations Using Convolutional Neural Networks ”, IEEE Trans Med Imag 36, (2017), 674-683
  9. Baumgartner, C. F., Kamnitsas, K., Matthew, J., Fletcher, T. P., Smith, S., Koch, L. M., Kainz, B., and Rueckert, D., “ SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound ”, IEEE Trans Med Imag 36, (2017), 2204-2215
  10. Lloyd, D., Kainz, B., van Amerom, J. F., Lohezic, M., Pushparajah, K., Simpson, J. M., Malamateniou, Ch., Hajnal, J. V., Rutherford, M., and Razavi, R., “ Prenatal MRI visualisation of the aortic arch and fetal vasculature using motion-corrected slice-to-volume reconstruction ”, J Cardiovasc Magn Reson 18, (2016), 180
  11. Rueckert, D., Glocker, B., and Kainz, B., “ Learning clinically useful information from images: Past, present and future “, Med Image Anal 33, (2016), 13 - 18
  12. Egger, J., Busse, H., Brandmaier, P., Seider, D., Gawlitza, M., Strocka, S., Voglreiter, P., Dokter, M., Hofmann, M., Kainz, B., Hann, A., Chen, X., Alhonnoro, T., Pollari, M.; Schmalstieg, D., and Moche, M., “ Interactive Volumetry Of Liver Ablation Zones ”, Scientific Reports, 5, (2015), 15373
  13. Kainz, B., Steinberger, M., Wein, W., Kuklisova-Murgasova, M., Malamateniou, C., Keraudren, K., Torsney-Weir, T., Rutherford, M., Aljabar, P., Hajnal, J.V., and Rueckert, D., “ Fast Volume Reconstruction From Motion Corrupted Stacks of 2D Slices ”, IEEE Trans Med Imag 34, (2015),1901–1913
  14. Keraudren, K., Kuklisova-Murgasova, M., Kyriakopoulou, V., Malamateniou, C., Rutherford, M.A., Kainz, B., Hajnal, J.V. and Rueckert, D., 2014. Automated fetal brain segmentation from 2D MRI slices for motion correction. NeuroImage, 101, pp.633-643.
  15. Steinberger, M., Kenzel, M., Kainz, B., Wonka, P. and Schmalstieg, D., 2014, May. „On‐the‐fly generation and rendering of infinite cities on the GPU”. In Computer graphics forum (Vol. 33, No. 2, pp. 105-114)
  16. Steinberger, M., Kenzel, M., Kainz, B., Müller, J., Peter, W. and Schmalstieg, D., 2014, May. „Parallel generation of architecture on the GPU”. In Computer graphics forum (Vol. 33, No. 2, pp. 73-82)
  17. Khlebnikov, R., Voglreiter, P., Steinberger, M., Kainz, B., and Schmalstieg, D., 2014, June. Parallel Irradiance Caching for Interactive Monte‐Carlo Direct Volume Rendering. In Computer graphics forum (Vol. 33, No. 3, pp. 61-70)
  18. Khlebnikov, R., Kainz, B., Steinberger, M. and Schmalstieg, D., 2013. Noise-based volume rendering for the visualization of multivariate volumetric data.IEEE transactions on visualization and computer graphics, 19(12), pp.2926-2935.
  19. Khlebnikov, R., Kainz, B., Steinberger, M., Streit, M. and Schmalstieg, D., 2012, June. „Procedural Texture Synthesis for Zoom‐Independent Visualization of Multivariate Data”. In Computer graphics forum (Vol. 31, No. 3pt4, pp. 1355-1364). Oxford, UK: Blackwell Publishing Ltd.
  20. Steinberger, M., Kainz, B., Kerbl, B., Hauswiesner, S., Kenzel, M. and Schmalstieg, D., 2012. „Softshell: dynamic scheduling on GPUs”. ACM Transactions on Graphics (TOG), 31(6), p.161.
  21. Steinberger, M., Kainz, B., Hauswiesner, S., Khlebnikov, R., Kalkofen, D. and Schmalstieg, D., „Ray prioritization using stylization and visual saliency”. Computers & Graphics, 36(6), 2012, 673-684.
  22. Khlebnikov, R., Kainz, B., Muehl, J. and Schmalstieg, D., 2011. „Crepuscular rays for tumor accessibility planning”. IEEE Transactions on Visualization & Computer Graphics, (12), pp.2163-2172.
  23. Kainz, B. , Grabner, M., Bornik, A., Hauswiesner, S., Muehl, J. and Schmalstieg, D., , December. „Ray casting of multiple volumetric datasets with polyhedral boundaries on manycore GPUs”. In ACM Transactions on Graphics (TOG) 28, No. 5, (ACM) 2009, 152.
  24. Reiter, G., Reiter, U., Kovacs, G., Kainz, B., Schmidt, K., Maier, R., Olschewski, H. and Rienmueller, R., “Magnetic Resonance–Derived 3-Dimensional Blood Flow Patterns in the Main Pulmonary Artery as a Marker of Pulmonary Hypertension and a Measure of Elevated Mean Pulmonary Arterial Pressure” Circulation: Cardiovascular Imaging. 2008 Jul;1(1):23-30.

40. Skelton, E., Matthew, J., Li, Y., Gupta, Ch., Knight, C., Khanal, B., Kainz, B., Hajnal, J.V., Rutherford, M., "Towards automated extraction of 2D standard fetal head planes from 3D ultrasound acquisitions: A clinical evaluation and quality assessment comparison Radiography." to appear in Radiography 2020 https://doi.org/10.1016/j.radi.2020.11.006

  1. Koestenbauer, S., Stiegler, P., Stadlbauer, V., Mayrhauser, U., Leber, B., Blattl, D., Kainz, B., Reich, O., Portugaller, R.H., Wiederstein-Grasser, I. and Tschliessnigg, K.H., 2011. Visualization of large-scale sections. J Surg Radiol, 2, pp.170-3.
  2. Kainz, B., Reiter, U., Reiter, G. and Schmalstieg, D.,. „In vivo interactive visualization of four-dimensional blood flow patterns”. The visual computer, 25(9), 2009, 853-862.

Books edited:

  1. Stoyanov, D.; Taylor, Z.; Kainz, B.; Maicas, G.; Beichel, R.; Martel, A.; Maier-Hein, L.; Bhatia, K; Vercauteren, T., Oktay, O. T., Carneiro O., Carneiro, G.; Bradley, A. P.; Nascimento, J.; Min, H.; Brown, M. S.; Jacobs, C.; Lassen-Schmidt, B.; Mori, K.; Petersen, J.; Estépar ,R. S. J.; Schmidt-Richberg, A.; Veiga, C. (Eds.), “ Image Analysis for Moving Organ, Breast, and Thoracic Images: Third International Workshop, RAMBO 2018, Fourth International Workshop, BIA 2018, and First International Workshop, TIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16 and 20, 2018, Proceedings ”, Lecture Notes in Computer Science (LNCS) 11040, ( Springer International Publishing) 2018
  2. Zuluaga, M. A.; Bhatia, K.; Kainz, B.; Moghari, M. H.; Pace, D. F. (Eds.), Reconstruction, Segmentation, and Analysis of Medical Images: First International Workshops, RAMBO 2016 and HVSMR 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 17, 2016, Revised Selected Papers , volume LNCS 10129, ( Springer International Publishing) 2017
  3. Cardoso, J., Arbel, T.; Gao, F.; Kainz, B.; van Walsum, T.; Shi, K.; Bhatia, K. K.; Peter, R.; Vercauteren, T.; Reyes, M.; Dalca, A.; Wiest, R.; Niessen, W.; Emmer, B. J. (Eds.), Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment. Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Québec City, QC, Canada, September 14, 2017, Proceedings , volume 10555, (Springer, Cham) 2017

Peer reviewed full papers at scientific conferences:

  1. Hou B, Kaissis G, Summers RM, Kainz B. RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2021 Sep 27 (pp. 293-303). Springer, Cham.
  2. Reynaud H, Vlontzos A, Hou B, Beqiri A, Leeson P, Kainz B. Ultrasound Video Transformers for Cardiac Ejection Fraction Estimation. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2021 Sep 27 (pp. 495-505). Springer, Cham.
  3. Budd S, Sinclair M, Day T, Vlontzos A, Tan J, Liu T, Matthew J, Skelton E, Simpson J, Razavi R, Glocker B., Rueckert D., Robinson MC, Kainz B., Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-Specific Atlas Maps. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2021 Sep 27 (pp. 207-217). Springer, Cham.
  4. Tan J, Hou B, Day T, Simpson J, Rueckert D, Kainz B. Detecting Outliers with Poisson Image Interpolation. In International Conference on Medical Image Computing and Computer-Assisted Intervention 2021 Sep 27 (pp. 581-591). Springer, Cham.
  5. Chartsias A, Gao S, Mumith A, Oliveira J, Bhatia K, Kainz B, Beqiri A. Contrastive Learning for View Classification of Echocardiograms. In International Workshop on Advances in Simplifying Medical Ultrasound 2021 Sep 27 (pp. 149-158). Springer, Cham.
  6. Ma Q, Robinson EC, Kainz B, Rueckert D, Alansary A. PialNN: A Fast Deep Learning Framework for Cortical Pial Surface Reconstruction. InInternational Workshop on Machine Learning in Clinical Neuroimaging 2021 Sep 27 (pp. 73-81). Springer, Cham.
  7. Budd S, Day T, Simpson J, Lloyd K, Matthew J, Skelton E, Razavi R, Kainz B. Can non-specialists provide high quality gold standard labels in challenging modalities?. InDomain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health 2021 Oct 1 (pp. 251-262). Springer, Cham.
  8. Li L, Sinclair M, Makropoulos A, Hajnal JV, David Edwards A, Kainz B, Rueckert D, Alansary A. CAS-Net: Conditional Atlas Generation and Brain Segmentation for Fetal MRI. In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis 2021 Oct 1 (pp. 221-230). Springer, Cham.
  9. Schmidtke L, Vlontzos A, Ellershaw S, Lukens A, Arichi T, Kainz B. Unsupervised Human Pose Estimation through Transforming Shape Templates. InProceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2021 (pp. 2484-2494).
  10. Hinterreiter, A., Streit, M., Kainz, B., “Projective Latent Interventions for Understanding and Fine-Tuning Classifiers”. In Interpretable and Annotation-Efficient Learning for Medical Image Computing 2020 at MICCAI 2020 Oct 4 (pp. 13-22), Springer, Cham. (best paper award)
  11. Budd, S., Patkee, P., Baburamani, A., Rutherford, M., Robinson, E.C., Kainz, B., “Surface Agnostic Metrics for Cortical Volume Segmentation and Regression.” In 3rd international workshop on machine learning in clinical neuroimaging (MLCN2020) at MICCAI 2020, Springer, Cham. (best paper honourable mention award)

57. Tan, J., Hou, B., Batten, J., Qiu, H., Kainz, B., “Detecting Outliers with Foreign Patch Interpolation” Medical Out-of-Distribution Analysis Challenge, publication pending http://medicalood.dkfz.de/web/ https://arxiv.org/abs/2011.04197 (winning entry)

58. Liu, T., Meng, Q., Vlontzos, A., Tan, J., Rueckert, D., Kainz, B., "Ultrasound Video Summarization Using Deep Reinforcement Learning", In Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 pp. 483-492, Springer Cham. (acceptance rate ~30%)

59. Grzech, D., Kainz, B., Glocker, B., Le Folgoc, L., “Image Registration via Stochastic Gradient Markov Chain Monte Carlo”. In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis: Second International Workshop, UNSURE 2020 at MICCAI 2020, and Third International Workshop, GRAIL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings (p. 3). Springer Nature. (nurturing talented RA Le Folgoc with last author position)

60. Vlontzos, A., Budd, S., Hou, B., Rueckert, D., Kainz, B., “3D Probabilistic Segmentation and Volumetry from 2D projection images”. In International Workshop on Thoracic Image Analysis 2020 at MICCAI 2020 Oct 8 (pp. 48-57). Springer, Cham.

61. Meng, Q., Rueckert, D., Kainz, B., “Unsupervised Cross-domain Image Classification by Distance Metric Guided Feature Alignment.” In Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis 2020 at MICCAI 2020 Oct 4 (pp. 146-157). Springer, Cham.

62. Tan, J., Au, A., Meng, Q., Finesilver-Smith, S., Simpson, J., Rueckert, D., Razavi, R., Day, T., Lloyd, D., Kainz, B., “Automated Detection of Congenital Heart Disease in Fetal Ultrasound Screening”. In Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis 2020 at MICCAI 2020 Oct 4 (pp. 243-252). Springer, Cham.

63. Tan, J., Kainz, B., “Divergent search for image classification behaviors.” In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion 2020 Jul 8 (pp. 91-92).

64. Miolane, N., Guigui, N., Zaatiti, H., Shewmake, C., Hajri, H., Brooks, D., Le Brigant, A., Mathe, J., Hou, B., Thanwerdas, Y., Heyder, S., Peltre, O., Koep, N., Cabanes, Y., Gerald, Th., Chauchat, P., Kainz, B., Donnat, C., Holmes, S., Pennec, X., “Introduction to Geometric Learning in Python with Geomstats.” In Proceedings of the 19th Python in Science Conference 2020 Jul 6 (Vol. 2020).

65. Hou, B., Vlontzos, A., Alansary, A., Rueckert, D., Kainz, B., “Flexible Conditional Image Generation of Missing Data with Learned Mental Maps.” In International Workshop on Machine Learning for Medical Image Reconstruction 2019 at MICCAI 2019 Oct 17 (pp. 139-150). Springer, Cham.

66. Meng, Q., Pawlowski, N., Rueckert, D., Kainz, B., “Representation disentanglement for multi-task learning with application to fetal ultrasound.” In Smart Ultrasound Imaging and Perinatal, Preterm and Paediatric Image Analysis 2019 at MICCAI 2019 Oct 17 (pp. 47-55). Springer, Cham.

67. Chotzoglou, E., Kainz, B., “Exploring the Relationship Between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks.” In Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention 2019 at MICCAI 2019 Oct 13 (pp. 51-60). Springer, Cham.

68. Wright, R., Toussaint, N., Gomez, A., Zimmer, V., Khanal, B., Matthew, J., Skelton, E., Kainz, B., Rueckert, D., Hajnal, J.V., Schnabel, J.A., “Complete Fetal Head Compounding from Multi-view 3D Ultrasound.” In International Conference on Medical Image Computing and Computer-Assisted Intervention 2019 at MICCAI 2019 Oct 13 (pp. 384-392). Springer, Cham. (acceptance rate ~30%)

69. Tan, J., Au, A., Meng, Q., Kainz, B., “Semi-supervised Learning of Fetal Anatomy from Ultrasound.” In Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data 2019 at MICCAI 2019 Oct 13 (pp. 157-164). Springer, Cham.

70. #Holland, R., Patel, U., Lung, P., Chotzoglou, E., Kainz, B., “Automatic detection of bowel disease with residual networks.” In International Workshop on PRedictive Intelligence In MEdicine 2019 at MICCAI 2019 Oct 13 (pp. 151-159). Springer, Cham.

71. Budd, S., Sinclair, M., Khanal, B., Matthew, J., Lloyd, D., Gomez, A., Toussaint, N., Robinson, E.C., Kainz, B., Confident head circumference measurement from ultrasound with real-time feedback for sonographers. In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2019 Oct 13 (pp. 683-691). Springer, Cham. (acceptance rate ~30%)

72. Vlontzos, A., Alansary, A., Kamnitsas, K., Rueckert, D., Kainz, B., “Multiple landmark detection using multi-agent reinforcement learning.” In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2019 Oct 13 (pp. 262-270). Springer, Cham. (acceptance rate ~30%)

  1. Alansary, A.; Le Folgoc, L.; Vaillant, G.; Oktay, O.; Li, Y.; Bai, W.; Passerat-Palmbach, J., Guerrero, R., Kamnitsas, K., Hou, B., McDonagh, S., Glocker, B., Kainz, B., and Rueckert, D., “ Automatic View Planning with Multi-scale Deep Reinforcement Learning Agents ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 277-285 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  2. Tanno, R., Makropoulos, A., Arslan, S., Oktay, O., Mischkewitz, S., Al-Noor, F., Oppenheimer, J., Mandegaran, R., Kainz, B., and Heinrich, M., “ AutoDVT: Joint Real-time Classification for Vein Compressibility Analysis in Deep Vein Thrombosis Ultrasound Diagnostics ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 905-912 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  3. Li, Y., Alansary, A., Cerrolaza, J., Khanal, B., Sinclair, M., Matthew, J., Gupta, C., Knight, C., Kainz, B., and Rueckert, D. “ Fast Multiple Landmark Localisation Using a Patch-based Iterative Network ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 563-571 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  4. Hou, B., Miolane, N., Khanal, B., Lee, M., Alansary, A., McDonagh, S., Hajnal, J., Glocker, B., Rueckert, D., and Kainz, B., “ Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry ”, in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 756-764 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  5. Li, Y., Khanal, B., Hou, B., Alansary, A., Cerrolaza, J., Sinclair, M., Matthew, J., Gupta, C., Knight, C., Kainz, B., and Rueckert, D., “ Standard Plane Detection in 3D Fetal Ultrasound Using an Iterative Transformation Network ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 392-400 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  6. Cerrolaza, J., Li, Y., Biffi, C., Gomez, A., Sinclair, M., Matthew, J., Knight, C. Kainz, B., and Rueckert, D., “ 3D Fetal Skull Reconstruction from 2DUS via Deep Conditional Generative Networks ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 383-391 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  7. Robinson, R., Oktay, O., Bai, W., Valindria, V., Kainz, B., Piechnik, S., Neubauer, S., Petersen, S., Page, C., Rueckert, D., Glocker, B., “ Real-time Prediction of Segmentation Quality ”, in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018 Frangi, A. F., Schnabel, J. A., Davatzikos, C., Alberola-Lopez, C., and Fichtinger, G. ed (Springer International Publishing) 2018, 578-585 (Proc. 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2018) (acceptance rate ~30%)
  8. Oktay, O., Schlemper, J., Le Folgoc, L., Lee, M., Heinrich, M., Misawa, K., Mori, K., McDonagh, S., Hammerla, N. Y., Kainz, B., Glocker, B., and Rueckert, D., “ Attention U-Net: Learning Where to Look for the Pancreas ” in Medical Imaging with Deep Learning 2018, https://openreview.net/forum?id=Skft7cijM, conference track, non-archival, 2018, to appear in Medical Image Analysis (acceptance rate ~30%)
  9. Alansary, A., Oktay, O., Li, Y., Le Folgoc, L., Hou, B., Vaillant, G., Glocker, B., Kainz, B., and Rueckert, D. “ Evaluating Reinforcement Learning Agents for Anatomical Landmark Detection ”, in Medical Imaging with Deep Learning 2018, https://openreview.net/forum?id=SyQK4-nsz, conference track, non-archival, 2018, to appear in Medical Image Analysis (acceptance rate ~30%)
  10. Schlemper, J., Oktay, O., Chen, L., Matthew, J., Knight, C., Toussaint, N., Kainz, B., Glocker, B., and Rueckert, D. “ Attention-Gated Networks for Improving Ultrasound Scan Plane Detection ”, in Medical Imaging with Deep Learning 2018, https://openreview.net/forum?id=BJtn7-3sM, conference track, non-archival, 2018, to appear in Medical Image Analysis (acceptance rate ~30%)
  11. Sinclair, M. D., Cerrolaza Martinez, J., Skelton, E., Li, Y., Baumgartner, C. F., Bai, W., Matthew, J., Knight, C. L., Smith, S., Hajnal, J., King, A. P., Kainz, B., and Rueckert, D., “ Cascaded Transforming Multi-task Networks For Abdominal Biometric Estimation from Ultrasound ”, in Medical Imaging with Deep Learning 2018, https://openreview.net/forum?id=r1ZGQW2if, conference track, non-archival, 2018, (acceptance rate ~30%)
  12. Kamnitsas, K., Bai, W., Ferrante, E., McDonagh, S., Sinclair, M., Pawlowski, N., Rajchl, M., Lee, M., Kainz, B., Rueckert, D. and Glocker, B., “Ensembles of multiple models and architectures for robust brain tumour segmentation” In International MICCAI Brainlesion Workshop 2017 Crimi, A. et al. ed (Springer, Cham.), 2017, 450-462. winner of the MICCAI BraTS 2017 challenge
  13. Sinclair, M., Baumgartner, C. F., Matthew, J., Bai, W., Cerrolaza, J. J. , Li, Y., Smith, S., Knight, C., Kainz, B., Hajnal, J. V., King, A. P., and Rueckert, D., “ Human-level performance on automatic head biometrics in fetal ultrasound using fully convolutional neural networks ”, in “40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), , Honolulu, HI, USA, 2018” (IEEE) 2018, 714-717 (Proc. EMBC’18, ) (acceptance rate ~40%)
  14. McDonagh, S., Hou, B., Kamnitsas, K., Oktay, O., Alansary, A., Rutherford, M., Hajnal, J.V., and Kainz, B., “ Context-Sensitive Super-Resolution for Fast Fetal Magnetic Resonance Imaging ” in “RAMBO 2017, CMMI 2017, SWITCH 2017: Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment ” Zuluaga, M. A.; et al. ed (Springer International Publishing) 2017, 116-126 (Proc. Reconstruction and Analysis of Moving Body Organs (RAMBO)’18) (acceptance rate ~50%)
  15. Cerrolaza, J. J., Oktay, O., Gomez, A., Matthew, J., Knight, C., Kainz, B., and Rueckert, D., “ Fetal Skull Segmentation in 3D Ultrasound via Structured Geodesic Random Forest ” in “Fetal, Infant and Ophthalmic Medical Image Analysis: International Workshop, FIFI 2017, and 4th International Workshop, OMIA 2017, Held in Conjunction with MICCAI 2017, Qu'ebec City, QC, Canada, September 14” Cardoso, M. J. et al. ed (Springer International Publishing) 2017, 25–32 (Proc. Fetal, Infant and Ophthalmic Medical Image Analysis 2017) (acceptance rate ~50%)
  16. Hou, B., Alansary, A., McDonagh, S., Davidson, A., Rutherford, M., Hajnal, J. V., Rueckert, D., Glocker, B., and Kainz, B., “ Predicting Slice-to-Volume Transformation in Presence of Arbitrary Subject Motion ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2017, LNCS 10434 Descoteaux, M. et al. ed (Springer International Publishing) 2017, 296–304 (Proc. 20th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2017) (acceptance rate ~30%)
  17. Toisoul, A., Rueckert, D., Kainz, B., “ Accessible GLSL Shader Programming ” in “EG 2017 - Education Papers” J. J. Bourdin and A. Shesh ed (Eurographics Proceedings The Eurographics Association) 2017, 35-42 (Proc. 38th Annual Conference of the European Association for Computer Graphics (Eurographics) 2017) (acceptance rate ~30%)
  18. Alansary, A., Kamnitsas, K., Rajchl, M., Davidson, A., Khlebnikov, R., Malamateniou, C., Rutherford, M., Hajnal, J., Glocker, B., Rueckert, D., and Kainz, B., “ Fast Fully Automatic Segmentation of the Human Placenta from Motion Corrupted MRI ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2016, LNCS 9901 Ourselin, S. et al. ed (Springer International Publishing) 2016, 589--597 (Proc. 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016) (acceptance rate ~30%)
  19. Kainz, B. , Lloyd, D. F.A., Alansary, A., Kuklisova Murgasova, M., Khlebnikov, R., Rueckert, D., Rutherford, M., Razavi, R., and Hajnal, J. V., “ High-Performance Motion Correction of Fetal MRI ” in “EuroRV3: EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization” Lawonned, K. et al. (The Eurographics Association) 2016, 5–7 (Proc. EuroRV3: EuroVis Workshop on Reproducibility, Verification, and Validation in Visualization 2016)
  20. Lloyd, D. F.A., Kainz, B., van Amerom, J. F. P., Pushparajah, K., Simpson, J. M., Zidere, V., Miller, O., Sharland, G., Zhang, T., Lohezic, M., Allsop, J., Fox, M., Malamateniou, C., Rutherford, M., Hajnal, J., and Razavi, R., “Three-Dimensional Modelling of the Fetal Vasculature from Prenatal MRI using Motion Corrected Slice-to-Volume Registration“ in Int. Soc. Magn. Reson. Med.. Vol. 24 (International Society of Magnetic Resonance in Medicine) 2016, O413 (Proceedings of the International Society of Magnetic Resonance in Medicine (ISMRM 2016)
  21. Baumgartner, C. F., Kamnitsas, K. , Matthew, J., Smith, S., Kainz, B., and Rueckert, D., “ Real-Time Standard Scan Plane Detection and Localisation in Fetal Ultrasound Using Fully Convolutional Neural Networks ” ” in Medical Image Computing and Computer Assisted Intervention -- MICCAI 2016, LNCS 9901 Ourselin, S. et al. ed (Springer International Publishing) 2016, 203–211(Proc. 19th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2016) (acceptance rate ~30%)
  22. Kainz, B. , Alansary, A., Malamateniou, C., Keraudren, K., Rutherford, M., Hajnal, J. V., and Rueckert, D., “ Flexible Reconstruction and Correction of Unpredictable Motion from Stacks of 2D Images ” in Medical Image Computing and Computer-Assisted Intervention– MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part II, volume 9350 Navab, N. et al. ed (2015), 555–562 (Proc. 18th International Conference on Medical Image Computing and Computer-Assisted Intervention 2015) (acceptance rate ~30%)
  23. Kainz, B. , Malamateniou, C., Ferrazzi, G., Murgasova, M., Egger, J., Keraudren, K., Rutherford, M., Hajnal, J.V. and Rueckert, D., 2015, April. “Adaptive scan strategies for fetal MRI imaging using slice to volume techniques”. In Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on(pp. 849-852). IEEE.
  24. Alansary, A., Lee, M., Keraudren, K., Kainz, B., Malamateniou, C., Rutherford, M., Hajnal, J.V., Glocker, B. and Rueckert, D., 2015, July. “Automatic brain localization in fetal MRI using superpixel graphs”. In Medical Learning Meets Medical Imaging (pp. 13-22). Springer, Cham.
  25. Egger, J., Busse, H., Brandmaier, P., Seider, D., Gawlitza, M., Strocka, S., Voglreiter, P., Dokter, M., Hofmann, M., Kainz, B. and Chen, X., 2015, August. RFA-cut: semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal st-cuts. In Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE (pp. 2423-2429). IEEE.
  26. Keraudren, K., Kainz, B., Oktay, O., Kyriakopoulou, V., Rutherford, M., Hajnal, J.V. and Rueckert, D., 2015, October. “Automated localization of fetal organs in MRI using random forests with steerable features”. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 620-627). Springer, Cham.
  27. Bowles, C., Nowlan, N.C., Hayat, T.T., Malamateniou, C., Rutherford, M., Hajnal, J.V., Rueckert, D. and Kainz, B., 2015, March. “Machine learning for the automatic localisation of foetal body parts in cine-MRI scans”. In Medical Imaging 2015: Image Processing (Vol. 9413, p. 94130N). International Society for Optics and Photonics.
  28. Kainz, B. , Keraudren, K., Kyriakopoulou, V., Rutherford, M., Hajnal, J.V. and Rueckert, D., 2014, April. “Fast fully automatic brain detection in fetal MRI using dense rotation invariant image descriptors”. In Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on (pp. 1230-1233). IEEE.
  29. Kainz, B. , Voglreiter, P., Sereinigg, M., Wiederstein-Grasser, I., Mayrhauser, U., Köstenbauer, S., Pollari, M., Khlebnikov, R., Seise, M., Alhonnoro, T. and Häme, Y., 2014, April. High-resolution contrast enhanced multi-phase hepatic Computed Tomography data fromaporcine Radio-Frequency Ablation study. In Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on (pp. 81-84). IEEE.
  30. Kainz, B., Malamateniou, C., Murgasova, M., Keraudren, K., Rutherford, M., Hajnal, J.V. and Rueckert, D., 2014, September. “Motion corrected 3D reconstruction of the fetal thorax from prenatal MRI”. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 284-291). Springer, Cham.
  31. Voglreiter, P., Steinberger, M., Kainz, B ., Khlebnikov, R., Schmalstieg, D., “ Dynamic GPU Scheduling for Volume Rendering ”, IEEE Scientific Visualization, IEEE Scientific Visualization 2013, 2013, Best poster honourable mention for IEEE SciVis 2013
  32. Kerbl, B., Voglreiter, P., Khlebnikov, R., Schmalstieg, D., Seider, D., Moche, M., Stiegler, P., Portugaller, R.H. and Kainz, B., 2012, October. „Intervention planning of hepatocellular carcinoma radio-frequency ablations”. In Workshop on Clinical Image-Based Procedures (pp. 9-16). Springer, Berlin, Heidelberg.
  33. Seider, D., Kolesnik, M., Kainz, B., Payne, S., Flanagan, R., Pollari, M., Stiegler, P. and Moche, M., 2013, April. “Entwicklung einer komplexen Softwareumgebung für die patientenspezifische Planung und Simulation der Radiofrequenzablation (RFA) von Lebertumoren“. In RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Vol. 185, No. S 01, p. VO301_4).
  34. Kainz, B. , Hauswiesner, S., Reitmayr, G., Steinberger, M., Grasset, R., Gruber, L., Veas, E., Kalkofen, D., Seichter, H. and Schmalstieg, D., 2012, December. “OmniKinect: real-time dense volumetric data acquisition and applications.” In Proceedings of the 18th ACM symposium on Virtual reality software and technology (pp. 25-32). ACM.
  35. Steinberger, M., Kenzel, M., Kainz, B., and Schmalstieg, D., 2012, May. „Scatteralloc: Massively parallel dynamic memory allocation for the GPU”. In Innovative Parallel Computing (InPar), 2012 (pp. 1-10). IEEE.
  36. Voglreiter, P., Steinberger, M., Schmalstieg, D. and Kainz, B., 2012, October. „Volumetric real-time particle-based representation of large unstructured tetrahedral polygon meshes”. In Workshop on Mesh Processing in Medical Image Analysis (pp. 159-168). Springer, Berlin, Heidelberg.
  37. Khlebnikov, R., Kainz, B., Roth, B., Muehl, J. and Schmalstieg, D.,. „GPU Based On-the-fly Light Emission-absorption Approximation for Direct Multi-volume Rendering”. In Eurographics (Posters) 2011, 11-12.
  38. Kainz, B. , Steinberger, M., Hauswiesner, S., Khlebnikov, R. and Schmalstieg, D.,. Stylization-based ray prioritization for guaranteed frame rates. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering (43-54). 2011, August ACM.
  39. Kainz, B. , Steinberger, M., Hauswiesner, S., Khlebnikov, R., Kalkofen, D. and Schmalstieg, D., 2011, February. Using perceptual features to prioritize ray-based image generation. In Symposium on Interactive 3D Graphics and Games (pp. 215-215). ACM.
  40. Kainz, B. , Portugaller, R.H., Seider, D., Moche, M., Stiegler, P. and Schmalstieg, D., 2011, September. “Volume visualization in the clinical practice”. In Workshop on Augmented Environments for Computer-Assisted Interventions (pp. 74-84). Springer, Berlin, Heidelberg.
  41. Kainz, B. , Steinberger, M., Hauswiesner, S., Khlebnikov, R. and Schmalstieg, D., 2011, August. ”Stylization-based ray prioritization for guaranteed frame rates”. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Non-Photorealistic Animation and Rendering (pp. 43-54). ACM.
  42. Muehl, J., Kainz, B., Bornik, A., Grabner, M., Hauswiesner, S. and Schmalstieg, D., 2009. The Future of Volume Graphics in Medical Virtual Reality. In World Congress on Medical Physics and Biomedical Engineering, September 7-12, 2009, Munich, Germany (pp. 1349-1352). Springer, Berlin, Heidelberg.
  43. Alhonnoro, T., Pollari, M., Lilja, M., Flanagan, R., Kainz, B., Muehl, J., Mayrhauser, U., Portugaller, H., Stiegler, P. and Tscheliessnigg, K., , September. “Vessel segmentation for ablation treatment planning and simulation. In International Conference on Medical Image Computing and Computer-Assisted Intervention” . Springer, Berlin, Heidelberg, 2010, 45-52.
  44. Grabner, M., Pock, T., Gross, T. and Kainz, B.,.” Automatic differentiation for GPU-accelerated 2D/3D registration”. InAdvances in Automatic Differentiation 2008, 259-269). Springer, Berlin, Heidelberg.
  45. Wagner, D., Schmalstieg, D. and Kainz, B., “Realtime 3D graphics programming using the Quake3 engine”. CGEMS: Computer graphics educational materials source , pp.8–8, 2008
  46. Kainz, B. , Grabner, M. and Ruether, M., “Fast marker based C-arm pose estimation” in 11th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) Metaxas, D. et al. ed (Springer, Berlin, Heidelberg), 2008, 652-659

Peer reviewed conference abstracts

119. Ellershaw, S., Schmidtke, L., Khatib, N., Eden, J., Jones, A., Dall'Orso, S., Muceli, S., Burdet, E., Nowlan, N., Arichi, T., Kainz, B., "3D Infant Pose Estimation Using Transfer Learning", Medical Imaging meets NeurIPS 2020 (oral, acceptance rat 14%)

120. Hou, B., Kaissis, G., Summers, R., Kainz, B., "RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting", Medical Imaging meets NeurIPS 2020

121. Chotzoglou, E., Budd, S., Day, Th., Simpson, J., Kainz, B., "Unsupervised detection of Hypoplastic Left Heart Syndrome in fetal screening", Medical Imaging meets NeurIPS 2020

  1. Li, Y., Cerrolaza, J. J., Sinclair, M., Hou, B., Alansary, A., Khanal, B., Matthew, J., Kainz, B., and Rueckert, D., Standard Plane Localisation in 3D Fetal Ultrasound Using Network with Geometric and Image Loss , Medical Imaging with Deep Learning Conference (MIDL) 2018, https://openreview.net/pdf?id=BykcN8siz , abstract track, non-archival, 2018
  2. Meng, Q., Baumgartner, C., Sinclair, M., Housden, J., Rajchl, M., Gomez, A., Hou, B., Toussaint, N., Tan, J., Matthew, J., Rueckert, D., Schnabel, J., and Kainz, B., “ Automatic Shadow Detection in 2D Ultrasound” , Medical Imaging with Deep Learning Conference (MIDL) 2018, https://openreview.net/forum?id=SkU16Ec5f , abstract track, non-archival, 2018
  3. Robinson, R., Oktay, O., Bai, W., Valindria, V. V., Sanghvi, M. M., Aung, N., Paiva, J. M., Zemrak, F., Fung, K., Lukaschuk, E., Lee, A. M., Carapella, V., Kimm, Y. J., Kainz, B., Piechnik, S. K., Neubauer, S., Petersen, S. E., Page, C., Rueckert, D., and Glocker, B. “ Subject-level Prediction of Segmentation Failure using Real-Time Convolutional Neural Nets” , Medical Imaging with Deep Learning Conference (MIDL) 2018, https://openreview.net/forum?id=SJJfBr9oM , abstract track, non-archival, 2018
  4. Hou, B., Miolane, N., Khanal, B., Lee, M., Alansary, A., McDonagh, S., Hajnal, J., Rueckert, D., Glocker, B., and Kainz, B., Deep Pose Estimation for Image-Based Registration , Medical Imaging with Deep Learning Conference (MIDL) 2018, https://openreview.net/forum?id=SyweajisG , abstract track, non-archival, 2018
  5. Hou, B., Khanal, B., Alansary, A., McDonagh, S., Davidson, A., Rutherford, M., Hajnal, J. V., Rueckert, D., Glocker, B., and Kainz, B., “ Image-Based Registration in Canonical Atlas Space ”, Medical Imaging with Deep Learning Conference (MIDL) 2018, https://openreview.net/forum?id=Syxv3ijjf , abstract track, non-archival, 2018
  6. Verbruggen, S. W., Kainz, B., Shelmerdine, S. C., Hajnal, J. V., Rutherford, M. A., Arthurs, O. J., Phillips, A.T.M., and Nowlan, N. C., “ Altered Biomechanical Stimulation of the Fetal Skeleton Correlates with Risk Factors for Developmental Dysplasia of the Hip ”, peer reviewed poster abstract, ORS Annual meeting of the Orthopaedic Research Society Volume 43 March 10-13 (Orthopaedic Research Society) 0696
  7. Budd, S., Robinson, E. C., Kainz, B., “ The Cortical Explorer: A Web-based User-interface for the Exploration of the Human Cerebral Cortex ”, in proceedings of the 7th Eurographics Workshop on Visual Computing for Biology and Medicine (Posters), 2017
  8. Verbruggen, S. W., Kainz, B., Arthurs, O. J., Hajnal, J. V., Rutherford, M. A., Phillips, A. T.M., Nowlan, N. C., “ Modelling the biomechanics of fetal movements ”, XXVI Congress of the International Society of Biomechanics 23 -27 July 2017, Brisbane Convention & Exhibition Centre Brisbane, Australia – International Society of Biomechanics Meeting (International Society of Biomechanics ) 2017, 612
  9. Kim, H., Lau, J., Kainz, B., McGuillen, P., Xu, D., and Peyvandi, S. Fetal brain volumetry to predict neonatal brain injury in patients with congenital heart disease , Organization for Human Brain Mapping (OHBM) 2017 - Organization for Human Brain Mapping, 2017 (Proc 23rd Annual Meeting of the Organization for Human Brain Mapping June 25–29, 2017, Vancouver Convention Centre | Vancouver, British Columbia, Canada)
  10. Verbruggen, S. W., Kainz, B., Hajnal, J. V., Rutherford, M. A., Phillips, A.T.M., Nowlan, N. C., Exploring the Link between Fetal Movements and Hip Dysplasia in Singleton and Twin Pregnancies , the 2017 meeting of the Orthopaedic Research Society, 2016
  11. Egger, J., Voglreiter, P., Dokter, M., Hofmann, M., Busse, H., Seider, D., Brandmaier, P., Rautio, R., Zettel, G., Schmerböck, B. and van Amerongen, M., Jenniskens, S., Kolesnik, M., Kainz, B. , Sequeiros R.B., Portugaller, H., Stiegler, P., Futterer, J., Schmalstieg, D., Moche, M., “ In-depth Multicenter Workflow Analysis of Liver Tumor Ablations for the Development of a Novel Computer-aided Software Tool ”, RSNA Annual Meeting - Radiological Society of North America, 101th Annual Meeting of The Radiological Society of North America (RSNA), 2015
  12. Reiter, U., Reiter, G., Kovacs, G., Schmidt, K., Maier, R., Kainz, B., Olschewski, H. and Rienmueller, R., 2009, April. „Magnetresonanz-basierte Messung des erhöhten, mittleren pulmonalarteriellen Drucks“. In RöFo-Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren (Vol. 181, No. S 01, p. VO329_6).
  13. Muehl, J.K., Kainz, B.K., Portugaller, H.R., Stiegler, P.B. and Bauer, C.H., , September. „Computer oriented image acquisition of the liver: Toward a better numerical model for radiofrequency ablation”. In Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE (IEEE) 2009, 3755-3758..

Public source code and demos

135. http://ratchet.lucidifai.com/ demo and public source code for MICCAI 2021 [46]

136. https://github.com/bkainz/ShaderLabWeb (public source code for new online teaching framework in 60005 – to be released with start of spring term)

137. https://github.com/einbandi/latent-projective-interventions -- source code for conference paper [55]

138. https://github.com/Lorna-Liu/ultrasound_vsumm_RL -- source code for conference paper [58]

139. https://github.com/jemtan/FPI -- source code for conference paper [49]

140. https://github.com/bkainz/fastreg -- fast registration library, source code for paper [59]

141. https://github.com/qmeng99/MetFA -- source code for paper [69]

142. https://github.com/qmeng99/Multi-task-Representation-Disentanglement -- source code for paper [61]

143. https://github.com/sambuddinc/PHiSeg-code -- source code for conference paper [71]

144. https://github.com/thanosvlo/MARL-for-Anatomical-Landmark-Detection -- source code for conference paper [7]

145. https://github.com/thanosvlo/Causal-Future-Prediction-in-a-Minkowski-Space-Time -- source code for preprint paper [168]

146. https://github.com/qmeng99/mutual-information-based-disentangled-neural-networks -- source code for journal paper [5]

147. https://github.com/geomstats/geomstats -- source code for paper [64]

148. https://osr.jstudios.ovh/index -- source code and plugins for paper [7]

149. https://github.com/qmeng99/shadowConfidenceMap -- source code for paper [10]

150. https://github.com/ozan-oktay/Attention-Gated-Networks -- source code for paper [80]

151. https://github.com/amiralansary/rl-medical -- source code for paper [81]

152. https://github.com/dccastro/Morpho-MNIST -- source code for paper [14]

153. http://ibd.lucidifai.com – UG group project to make machine learning algorithms accessible for clinicians

154. http://lung.lucidifai.com/ -- MEng final year project to provide a lung analyser for ongoing COVID-19 crisis

155. http://torchmedic.lucidifai.com/ -- MEng group project demo for stochastic segmentation library

156. https://play.google.com/store/apps/details?id=xyz.hutt.meng.generic&hl=en-GB&ah=FTmUe9cKkd_Rs7VpdciJLay-gJ0 – MEng final year project demo mobile application for clinical image recognition and image style transfer (only accessible with Google developer account, will soon become public)

157. https://github.com/bkainz/ShaderLabFramework Teaching framework for Computer Graphics (updated in 2018)

158. https://github.com/bkainz/DeepPose pose estimation with CNNs and Riemannian metrics in SE(3)

159. https://github.com/bkainz/Attention-Gated-Networks attention gated networks for segmentation and classification

160. http://www.corticalexplorer.com/ outreach framework to visualise cortical brain function

161. SonoNet https://github.com/baumgach/SonoNet-weights framework for real-time fetal standard scan plane detection during ultrasound examinations

162. https://github.com/bkainz/fetalReconstruction PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI

163. https://github.com/bkainz/fetalReconstruction GPU accelerated Motion compensation for medical images

Preprints

164. Liu T, Meng Q, Huang JJ, Vlontzos A, Rueckert D, Kainz B. Video Summarization through Reinforcement Learning with a 3D Spatio-Temporal U-Net. arXiv preprint arXiv:2106.10528. 2021 Jun 19.

165. Vlontzos A, Kainz B, Gilligan-Lee CM. Estimating the probabilities of causation via deep monotonic twin networks. arXiv preprint arXiv:2109.01904. 2021 Sep 4.

166. Gomez A, Zimmer VA, Wheeler G, Toussaint N, Deng S, Wright R, Skelton E, Matthew J, Kainz B, Hajnal J, Schnabel J. PRETUS: A plug-in based platform for real-time ultrasound imaging research. arXiv preprint arXiv:2109.06519. 2021 Sep 14.

167. Schlüter HM, Tan J, Hou B, Kainz B. Self-Supervised Out-of-Distribution Detection and Localization with Natural Synthetic Anomalies (NSA). arXiv preprint arXiv:2109.15222. 2021 Sep 30.

168. Vlontzos, A., Rocha, H.B., Rueckert, D., Kainz, B., “Causal Future Prediction in a Minkowski Space-Time.” arXiv preprint arXiv:2008.09154. 2020 Aug 20. (MIT tech review feature story, https://bit.ly/35cN6rq )

169. Budd, S., Robinson, E.C., Kainz B., “A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis”. arXiv preprint arXiv:1910.02923. 2019 Oct 7.

170. Jiang, G., Kainz, B., “One Shot Radiance: Global Illumination Using Convolutional Autoencoders.” arXiv preprint arXiv:1910.02480. 2019 Oct 6.

171. Meng, Q., Matthew, J., Zimmer, V.A., Gomez, A., Lloyd, D.F., Rueckert, D., Kainz, B., “Mutual Information-based Disentangled Neural Networks for Classifying Unseen Categories in Different Domains: Application to Fetal Ultrasound Imaging.” arXiv preprint arXiv:2011.00739. 2020 Oct 30.

172. Hinterreiter, A., Streit, M., Kainz, B., “Projective Latent Space Decluttering.” arXiv preprint arXiv:2006.12902. 2020 Jun 23.

173. Liu, T., Meng, Q., Vlontzos, A., Tan, J., Rueckert, D., Kainz, B., “Ultrasound Video Summarization using Deep Reinforcement Learning.” arXiv preprint arXiv:2005.09531. 2020 May 19.

174. Tan, J., Kainz, B., “Divergent Search for Few-Shot Image Classification.” arXiv preprint arXiv:2004.07903. 2020 Apr 16.

175. Meng, Q., Rueckert, D., Kainz, B., “Learning Cross-domain Generalizable Features by Representation Disentanglement.” arXiv preprint arXiv:2003.00321. 2020 Feb 29.

176. Budd, S., Patkee, P., Baburamani, A., Rutherford, M., Robinson, E.C., Kainz, B., “Surface Agnostic Metrics for Cortical Volume Segmentation and Regression.” arXiv preprint arXiv:2010.01669. 2020 Oct 4.

177. Robinson, R., Valindria, V.V., Bai, W., Oktay, O., Kainz, B., Suzuki, H., Sanghvi, M.M., Aung, N., Paiva, J., Zemrak, F., Fung, K. Paiva, J.M., Carapella, V., Kim, Y.J., Suzuki, H., Kainz, B., Matthews, P.M., Petersen, St. E., Piechnik, St. K., Neubauer, St., Glocker, B., Rueckert, D., “Automated Quality Control in Image Segmentation: Application to the UK Biobank” Cardiac MR Imaging Study. arXiv preprint arXiv:1901.09351. 2019 Jan 27.

178. Bakas, S., …, Kainz, B., …, et al. (327+ authors) “Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge.” arXiv preprint arXiv:1811.02629. 2018 Nov 5.

  1. Meng, Q., Sinclair, M., Zimmer, V., Hou, B., Rajchl, M., Toussaint, N., Gomez, A., Housden, J., Matthew, J., Rueckert, D., Schnabel, J., Kainz, B., "Weakly Supervised Estimation of Shadow Confidence Maps in Ultrasound Imaging", Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1811.08164 e-prints, 2018
  2. Hou, B., Miolane, N., Khanal, B., Lee, M.C., Alansary, A., McDonagh, S., Hajnal, J.V., Rueckert, D., Glocker, B. and Kainz, B., “ Computing CNN Loss and Gradients for Pose Estimation with Riemannian Geometry ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1805.01026 e-prints, 2018
  3. Schlemper, J., Oktay, O., Schaap, M., Heinrich, M., Kainz, B., Glocker, B. and Rueckert, D., “Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images“ Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1808.08114 e-prints, 2018
  4. Schlemper, J., Oktay, O., Chen, L., Matthew, J., Knight, C., Kainz, B., Glocker, B. and Rueckert, D., “ Attention-Gated Networks for Improving Ultrasound Scan Plane Detection ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv1804.05338 e-prints, 2018
  5. Oktay, O., Schlemper, J., Folgoc, L.L., Lee, M., Heinrich, M., Misawa, K., Mori, K., McDonagh, S., Hammerla, N.Y., Kainz, B., and Glocker, B., “ Attention U-Net: Learning Where to Look for the Pancreas ”, ArXiv e-prints, 2018
  6. Zhou, K., and Kainz, B., “ Efficient Image Evidence Analysis of CNN Classification Results ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1801.01693 e-prints, 2018
  7. Pawlowski, N., Ktena, S.I., Lee, M.C., Kainz, B., Rueckert, D., Glocker, B. and Rajchl, M., DLTK: State of the Art Reference Implementations for Deep Learning on Medical Images , Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1711.06853 e-prints, 2017
  8. Kamnitsas, K., Bai, W., Ferrante, E., McDonagh, S., Sinclair, M., Pawlowski, N., Rajchl, M., Lee, M., Kainz, B., Rueckert, D. and Glocker, B., “ Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1711.01468 e-prints, winner of the MICCAI BraTS 2017 challenge, 2017
  9. Bai, W., Sinclair, M., Tarroni, G., Oktay, O., Rajchl, M., Vaillant, G., Lee, A.M., Aung, N., Lukaschuk, E., Sanghvi, M.M. Zemrak, F., Fung, K., Paiva, J.M., Carapella, V., Kim, Y.J., Suzuki, H., Kainz, B., Matthews, P.M., Petersen, S.E., Piechnik, S.K., Neubauer, S., Glocker, B., and Rueckert, D., “Automated cardiovascular magnetic resonance image analysis with fully convolutional networks”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1710.09289 e-prints, 2017
  10. Hou, B., Khanal, B., Alansary, A., McDonagh, S., Davidson, A., Rutherford, M., Hajnal, J.V., Rueckert, D., Glocker, B. and Kainz, B., “ 3D Reconstruction in Canonical Co-ordinate Space from Arbitrarily Oriented 2D Images ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1709.06341, 2017
  11. Baumgartner, C.F., Kamnitsas, K., Matthew, J., Fletcher, T.P., Smith, S., Koch, L.M., Kainz, B., and Rueckert, D., “ Real-Time Detection and Localisation of Fetal Standard Scan Planes in 2D Freehand Ultrasound ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv: 1612.05601 e-prints, 2016
  12. Rajchl, M., Lee, M.C., Schrans, F., Davidson, A., Passerat-Palmbach, J., Tarroni, G., Alansary, A., Oktay, O., Kainz, B. and Rueckert, “ Learning under Distributed Weak Supervision ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv :1606.01100, 2016
  13. Rajchl, M., Lee, M.C., Oktay, O., Kamnitsas, K., Passerat-Palmbach, J., Bai, W., Damodaram, M., Rutherford, M.A., Hajnal, J.V., Kainz, B., and Rueckert, D., “ DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv:1605.07866, 2016
  14. Oktay, O., Ferrante, E., Kamnitsas, K., Heinrich, M., Bai, W., Caballero, J., Cook, S.A., de Marvao, A., Dawes, T., O‘Regan, D.P., Kainz, B., Glocker, B., Rueckert, D., “ Anatomically Constrained Neural Networks (ACNN): Application to Cardiac Image Enhancement and Segmentation ”, CoRR, volume abs/1705.08302, 2017
  15. Alansary, A., Rajchl, M., McDonagh, S.G., Murgasova, M., Damodaram, M., Lloyd, D.F., Davidson, A., Rutherford, M., Hajnal, J.V., Rueckert, D. and Kainz, B., “ PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI ”, Computer Vision and Pattern Recognition (cs.CV), preprint available on arXiv:1611.07289, 2016, Computer Vision and Pattern Recognition (cs.CV)

Patents:

  1. Al-Noor F, Mischkewitz S, Makropoulos A, Tanno R, Kainz B, Oktay O, inventors; Thinksono Ltd, assignee. Blood vessel obstruction diagnosis method, apparatus & system. United States patent application US 16/491,553. 2021 May 6.
  2. Mühl, J., Köstenbauer, S., Seise, M., Kainz, B., Stiegler, P., Mayrhauser, U., Portugaller, R.H., Fusion von CT Volumen und histologischen Schnitten orientiert an natürlichen Merkmalspunkten , 2011, DE Patent 102,010,042,073
  3. Granted but not published yet.