Resume

Christoph Jud is a senior researcher at the Center for medical Images Analyses and Navigation (CIAN) of the University of Basel where he leads the research group for Image Registration and Motion Modelling. He received his B.E. (2007) in information technology from the Zurich University of Applied Sciences, Switzerland, and his M.S. (2010) in computer science from the University of Basel, Switzerland, where he also finished his Ph.D. (2014) in computer science.

His main research focus lies in machine learning methods and their application in the biomedical field. In particular, his attention is drawn to weakly-supervised methods in order to quantify pathologies. He is working with a wide range of data types such as medical images (MR, CT, US), histology images, mass spectra and DNA methylation. He is also highly curious about novel machine learning methods, tools and paradigms and likes to try them out and play with them.

 

Dr. Christoph Jud

 

Dr. Christoph Jud
CIAN

Gewerbestr. 14, Room 14.04.010
CH-4123 Allschwil, Switzerland
t: +41 61 207 54 17
e: christoph.jud@clutterunibas.ch

Book Chapters:

C. Jud, P. C. Cattin, and F. Preiswerk, “Statistical respiratory models for motion estimation”, Statistical Shape and Deformation Analysis: Methods, Implementation and Applications, vol. 1, p. 379, 2017. read

Reviewed Journal Papers:

T. Ronchetti, C. Jud, P. M. Maloca, S. Orgül, A. T. Giger, C. Meier, H. P. Scholl, R. K. M. Chun, Q.Liu, C.-H. To, et al., “Statistical framework for validation without ground truth of choroidal thicknesschanges detection”, PloS one, vol. 14, no. 6, 2019. read

A. T. Giger, M. Stadelmann, F. Preiswerk, C. Jud, V. De Luca, Z. Celicanin, O. Bieri, R. Salomir, and P. C. Cattin, “Ultrasound-driven 4D MRI”, Physics in medicine and biology, 2018. read

M. Lüthi, T. Gerig, C. Jud, and T. Vetter, “Gaussian process morphable models”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 40, no. 8, pp. 1860–1873, 2017. read

A. Giger, C. Jud, and P. C. Cattin, “Respiratory motion compensation for the robot-guided laser osteotome”, International Journal of Computer Assisted Radiology and Surgery, pp. 1–12, 2017. read

N. Möri, C. Jud, R. Salomir, and P. C. Cattin, “Leveraging respiratory organ motion for non-invasive tumor treatment devices: A feasibility study”, Physics in medicine and biology, vol. 61, no. 11, p. 4247,2016. read

C. Jud, M. Lüthi, T. Albrecht, S. Schönborn, and T. Vetter, “Variational image registration using in-homogeneous regularization”, Journal of mathematical imaging and vision, vol. 50, no. 3, pp. 246–260,2014. read

Reviewed Conference Papers:

R. Sandkühler, S. Andermatt, G. Bauman, S. Nyilas, C. Jud, and P. C. Cattin, “Recurrent registration neural networks for deformable image registration”, in Advances in Neural Information Processing Systems, 2019, pp. 8758-8768. read

R. Sandkühler, G. Bauman, S. Nyilas, O. Pusterla, C. Willers, O. Bieri, P. Latzin, C. Jud, and P. C. Cattin, “Gated recurrent neural networks for accelerated ventilation mri”, in International Workshop on Machine Learning in Medical Imaging, Springer, Cham, 2019, pp. 549–556. read

A. Giger, C. Jud, D. Nguyen, M. Krieger, Y. Zhang, A. J. Lomax, O. Bieri, R. Salomir, and P. C.Cattin, “Inter-fractional respiratory motion modelling from abdominal ultrasound: A feasibility study”, in International Workshop on Predictive Intelligence In Medicine, Springer, Cham, 2019, pp. 11–22. read

R. Sandkühler, C. Jud, G. Bauman, C. Willers, O. Pusterla, S. Nyilas, A. Peters, L. Ebner, E. Stranziger, O. Bieri, et al., “Weakly supervised learning strategy for lung defect segmentation”, in International Workshop on Machine Learning in Medical Imaging, Springer, Cham, 2019, pp. 541–548. read

T. Ronchetti, P. Maloca, E. R. de Carvalho, T. F. Heeren, K. Balaskas, A. Tufail, C. Egan, M. Okada, S.Orgül, C. Jud, et al., “Feasibility study of subfoveal choroidal thickness changes in spectral-domain optical coherence tomography measurements of macular telangiectasia type 2”, in Computational Pathology and Ophthalmic Medical Image Analysis, Springer, 2018, pp. 303–309. read

C. Jud, D. Nguyen, R. Sandkühler, A. Giger, O. Bieri, and P. C. Cattin, “Motion aware mr imaging viaspatial core correspondence”, in International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2018, pp. 198–205. read

A. Giger, R. Sandkühler, C. Jud, G. Bauman, O. Bieri, R. Salomir, and P. C. Cattin, “Respiratory motionmodelling using cgans”, in International Conference on Medical Image Computing and Computer-AssistedIntervention, Springer, 2018, pp. 81–88. read

C. Jud, R. Sandkühler, and P. C. Cattin, “An inhomogeneous multi-resolution regularization concept for discontinuity preserving image registration”, in 8th International Workshop on Biomedical Image Registration, 2018, pp. 3–12. read

R. Sandkühler, C. Jud, S. Pezold, and P. C. Cattin, “Adaptive graph diffusion regularisation for discontinuity preserving image registration”, in 8th International Workshop on Biomedical Image Registration, 2018, pp. 24–34. read

C. Jud, A. Giger, R. Sandkühler, and P. C. Cattin, “A localized statistical motion model as a reproducingkernel for non-rigid image registration”, in International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2017, pp. 261–269. read

C. Jud, R. Sandkühler, N. Möri, and P. C. Cattin, “Directional averages for motion segmentation indiscontinuity preserving image registration”, in International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2017, pp. 249–256. read

 N. Möri, L. Gui, C. Jud, O. Lorton, R. Salomir, and P. C. Cattin, “An optimal control approach for high intensity focused ultrasound self-scanning treatment planning”, in International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, 2017, pp. 532–539. read

T. Ronchetti, P. Maloca, C. Jud, C. Meier, S. Orgül, H. P. Scholl, B. Povazay, and P. C. Cattin, “Detecting early choroidal changes using piecewise rigid image registration and eye-shape adherent regularization”, in Fetal, Infant and Ophthalmic Medical Image Analysis, Springer, 2017, pp. 92–100. read

T. Ronchetti, P. Maloca, C. Meier, S. Orgül, C. Jud, P. Hasler, B. Povazay, and P. C. Cattin, “Intensity-based choroidal registration using regularized block matching”, in International Workshop on Ophthalmic Medical Image Analysis (MICCAI OMIA), University of Iowa, 2016. read

R. Sandkühler, C. Jud, and P. C. Cattin, “On a spectral image metric for non-rigid group-wise registration of dynamic MR image series”, in International Workshop on Pulmonary Image Analysis, 2016. read

C. Jud, N. Möri, B. Bitterli, and P. C. Cattin, “Bilateral regularization in reproducing kernel hilbert spaces for discontinuity preserving image registration”, in International Workshop on Machine Learning in Medical Imaging, Springer, 2016, pp. 10–17. read

C. Jud, N. Möri, and P. C. Cattin, “Sparse kernel machines for discontinuous registration and non stationary regularization”, in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016, pp. 9–16. read

C. Jud, F. Preiswerk, and P. C. Cattin, “Respiratory motion compensation with topology independent surrogates”, in Workshop on imaging and computer assistance in radiation therapy, 2015. read

C. Jud and T. Vetter, “Using object probabilities in deformable model fitting”, in 22nd International Conference on Pattern Recognition (ICPR), IEEE, 2014, pp. 3310–3314. read

C. Jud and T. Vetter, “Geodesically damped shape models”, in Abstract Proceedings of Shape 2014, Shape Symposium on Statistical Shape Models and Applications, SICAS, 2014, p. 14.

 M. Lüthi, C. Jud, and T. Vetter, “A unified approach to shape model fitting and non-rigid registration”, in International Workshop on Machine Learning in Medical Imaging, Springer, 2013, pp. 66–73. read

M. Lüthi, C. Jud, and T. Vetter, “Using landmarks as a deformation prior for hybrid image registration”, in Pattern Recognition: 33rd DAGM Symposium, Springer, 2011, pp. 196–205. read