Tom Brosch - RankMe

23 papers B 4Journal 7Unranked 12

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease. Medical Image Anal. Danielle F. Pace, Adrian V. Dalca, Tom Brosch, Tal Geva, Andrew J. Powell, Jürgen Weese, Mehdi Hedjazi Moghari, Polina Golland
2021	J	`jnl`	Automated detection and segmentation of thoracic lymph nodes from CT using 3D foveal fully convolutional neural networks. BMC Medical Imaging Andra-Iza Iuga, Heike Carolus, Anna J. Höink, Tom Brosch, Tobias Klinder, David Maintz, Thorsten Persigehl, Bettina Baeßler, Michael Püsken
2020	J	`jnl`	3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images. CoRR Cheryl Sital, Tom Brosch, Dominique Tio, Alexander Raaijmakers, Jürgen Weese
2020	—	`conf`	Automated detection and segmentation of mediastinal and axillary lymph nodes from CT using foveal fully convolutional networks. Computer-Aided Diagnosis Heike Carolus, Andra-Iza Iuga, Tom Brosch, Rafael Wiemker, Frank Thiele, Anna J. Höink, David Maintz, Michael Püsken, Tobias Klinder
2018	B	`conf`	Automated abdominal plane and circumference estimation in 3D US for fetal screening. Image Processing Cristian Lorenz, Tom Brosch, Cybèle Ciofolo-Veit, Tobias Klinder, Thierry Lefevre, Angelo Cavallaro, Ibtisam Salim, Aris T. Papageorghiou, Caroline Raynaud, David Roundhill, Laurence Rouet, Nicole Schadewaldt, Alexander Schmidt-Richberg
2018	—	`conf`	Deep Learning-Based Boundary Detection for Model-Based Segmentation with Application to MR Prostate Segmentation. MICCAI (4) Tom Brosch, Jochen Peters, Alexandra Groth, Thomas Stehle, Jürgen Weese
2018	B	`conf`	Foveal fully convolutional nets for multi-organ segmentation. Image Processing Tom Brosch, Axel Saalbach
2018	—	`conf`	Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease. DLMIA/ML-CDS@MICCAI Danielle F. Pace, Adrian V. Dalca, Tom Brosch, Tal Geva, Andrew J. Powell, Jürgen Weese, Mehdi Hedjazi Moghari, Polina Golland
2018	J	`jnl`	Iterative Segmentation from Limited Training Data: Applications to Congenital Heart Disease. CoRR Danielle F. Pace, Adrian V. Dalca, Tom Brosch, Tal Geva, Andrew J. Powell, Jürgen Weese, Mehdi Hedjazi Moghari, Polina Golland
2018	B	`conf`	Nearest neighbor 3D segmentation with context features. Image Processing Evelin Hristova, Heinrich Schulz, Tom Brosch, Mattias P. Heinrich, Hannes Nickisch
2018	—	`conf`	Organ-At-Risk Segmentation in Brain MRI Using Model-Based Segmentation: Benefits of Deep Learning-Based Boundary Detectors. ShapeMI@MICCAI Eliza Orasanu, Tom Brosch, Carri Glide-Hurst, Steffen Renisch
2018	B	`conf`	Spine centerline extraction and efficient spine reading of MRI and CT data. Image Processing Cristian Lorenz, Nora Vogt, Peter Börnert, Tom Brosch
2017	—	`conf`	Abdomen Segmentation in 3D Fetal Ultrasound Using CNN-powered Deformable Models. FIFI/OMIA@MICCAI Alexander Schmidt-Richberg, Tom Brosch, Nicole Schadewaldt, Tobias Klinder, Angelo Cavallaro, Ibtisam Salim, David Roundhill, Aris T. Papageorghiou, Cristian Lorenz
2017	—	`conf`	Grey Matter Segmentation in Spinal Cord MRIs via 3D Convolutional Encoder Networks with Shortcut Connections. DLMIA/ML-CDS@MICCAI Adam Porisky, Tom Brosch, Emil Ljungberg, Lisa Y. W. Tang, Youngjin Yoo, Benjamin De Leener, Anthony Traboulsee, Julien Cohen-Adad, Roger C. Tam
2017	J	`jnl`	Spinal cord grey matter segmentation challenge. NeuroImage Ferran Prados, John Ashburner, Claudia Blaiotta, Tom Brosch, Julio Carballido-Gamio, Manuel Jorge Cardoso, Benjamin N. Conrad, Esha Datta, Gergely Dávid, Benjamin De Leener, Sara M. Dupont, Patrick Freund, Claudia A. M. Gandini Wheeler-Kingshott, Francesco Grussu, Roland G. Henry, Bennett A. Landman, Emil Ljungberg, Bailey Lyttle, Sébastien Ourselin, Nico Papinutto, Salvatore Saporito, Regina Schlaeger, Seth A. Smith, Paul E. Summers, Roger C. Tam, Marios C. Yiannakas, Alyssa H. Zhu, Julien Cohen-Adad
2016	—	`conf`	Corpus Callosum Segmentation in Brain MRIs via Robust Target-Localization and Joint Supervised Feature Extraction and Prediction. MICCAI (2) Lisa Y. W. Tang, Tom Brosch, Xingtong Liu, Youngjin Yoo, Anthony Traboulsee, David K. B. Li, Roger C. Tam
2016	J	`jnl`	Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation. IEEE Trans. Medical Imaging Tom Brosch, Lisa Y. W. Tang, Youngjin Yoo, David K. B. Li, Anthony Traboulsee, Roger C. Tam
2016	—	`conf`	Deep Learning of Brain Lesion Patterns for Predicting Future Disease Activity in Patients with Early Symptoms of Multiple Sclerosis. LABELS/DLMIA@MICCAI Youngjin Yoo, Lisa Y. W. Tang, Tom Brosch, David K. B. Li, Luanne Metz, Anthony Traboulsee, Roger C. Tam
2015	—	`conf`	Deep Convolutional Encoder Networks for Multiple Sclerosis Lesion Segmentation. MICCAI (3) Tom Brosch, Youngjin Yoo, Lisa Y. W. Tang, David K. B. Li, Anthony Traboulsee, Roger C. Tam
2015	J	`jnl`	Efficient Training of Convolutional Deep Belief Networks in the Frequency Domain for Application to High-Resolution 2D and 3D Images. Neural Comput. Tom Brosch, Roger C. Tam
2014	—	`conf`	Deep Learning of Image Features from Unlabeled Data for Multiple Sclerosis Lesion Segmentation. MLMI Youngjin Yoo, Tom Brosch, Anthony Traboulsee, David K. B. Li, Roger C. Tam
2014	—	`conf`	Modeling the Variability in Brain Morphology and Lesion Distribution in Multiple Sclerosis by Deep Learning. MICCAI (2) Tom Brosch, Youngjin Yoo, David K. B. Li, Anthony Traboulsee, Roger C. Tam
2013	—	`conf`	Manifold Learning of Brain MRIs by Deep Learning. MICCAI (2) Tom Brosch, Roger C. Tam