Cross-Cohort Automatic Knee MRI Segmentation With Multi-Planar U-Nets

Autor: Mathias Perslev, Akshay Pai, Jos Runhaar, Christian Igel, Erik B. Dam

Publikováno v: Journal of Magnetic Resonance Imaging, 55(6), 1650-1663. John Wiley & Sons Inc.
Perslev, M, Pai, A, Runhaar, J, Igel, C & Dam, E B 2022, ' Cross-Cohort Automatic Knee MRI Segmentation With Multi-Planar U-Nets ', Journal of Magnetic Resonance Imaging, vol. 55, no. 2, pp. 1650-1663 . https://doi.org/10.1002/jmri.27978

Background: Segmentation of medical image volumes is a time-consuming manual task. Automatic tools are often tailored toward specific patient cohorts, and it is unclear how they behave in other clinical settings. Purpose: To evaluate the performance

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::112bb74b2c9afd1bd823cdf450675aee
https://doi.org/10.1002/jmri.27978

Medial Cartilage Surface Integrity as a Surrogate Measure for Incident Radiographic Knee Osteoarthritis following Weight Changes

Autor: Jos Runhaar, Edwin H.G. Oei, Erik B. Dam, Sita M A Bierma-Zeinstra

Publikováno v: Cartilage, 13(1_suppl), 424S-427S. SAGE Publishing
Runhaar, J, Dam, E B, Oei, E H G & Bierma-Zeinstra, S M A 2019, ' Medial Cartilage Surface Integrity as a Surrogate Measure for Incident Radiographic Knee Osteoarthritis following Weight Changes ', Cartilage, vol. 13, no. Suppl. 1, pp. 424S-427S . https://doi.org/10.1177/1947603519892305
Cartilage

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77e677ff6c84e5d5505874dc35f32141
https://doi.org/10.1177/1947603519892305

The Liver Tumor Segmentation Benchmark (LiTS)

Autor: Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze

Publikováno v: Med. Image Anal. 84:102680 (2022)
Medical Image Analysis, 84
Bilic, P, Christ, P, Li, H B, Vorontsov, E, Ben-Cohen, A, Kaissis, G, Szeskin, A, Jacobs, C, Mamani, G E H, Chartrand, G, Lohöfer, F, Holch, J W, Sommer, W, Hofmann, F, Hostettler, A, Lev-Cohain, N, Drozdzal, M, Amitai, M M, Vivanti, R, Sosna, J, Ezhov, I, Sekuboyina, A, Navarro, F, Kofler, F, Paetzold, J C, Shit, S, Hu, X, Lipková, J, Rempfler, M, Piraud, M, Kirschke, J, Wiestler, B, Zhang, Z, Hülsemeyer, C, Beetz, M, Ettlinger, F, Antonelli, M, Bae, W, Bellver, M, Bi, L, Chen, H, Chlebus, G, Dam, E B, Dou, Q, Fu, C-W, Georgescu, B, Giró-I-Nieto, X, Gruen, F, Han, X, Heng, P-A, Hesser, J, Moltz, J H, Igel, C, Isensee, F, Jäger, P, Jia, F, Kaluva, K C, Khened, M, Kim, I, Kim, J-H, Kim, S, Kohl, S, Konopczynski, T, Kori, A, Krishnamurthi, G, Li, F, Li, H, Li, J, Li, X, Lowengrub, J, Ma, J, Maier-Hein, K, Maninis, K-K, Meine, H, Merhof, D, Pai, A, Perslev, M, Petersen, J, Pont-Tuset, J, Qi, J, Qi, X, Rippel, O, Roth, K, Sarasua, I, Schenk, A, Shen, Z, Torres, J, Wachinger, C, Wang, C, Weninger, L, Wu, J, Xu, D, Yang, X, Yu, S C-H, Yuan, Y, Yue, M, Zhang, L, Cardoso, J, Bakas, S, Braren, R, Heinemann, V, Pal, C, Tang, A, Kadoury, S, Soler, L, van Ginneken, B, Greenspan, H, Joskowicz, L & Menze, B 2023, ' The Liver Tumor Segmentation Benchmark (LiTS) ', Medical Image Analysis, vol. 84, 102680 . https://doi.org/10.1016/j.media.2022.102680

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical I

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e22b7afec9cac0b49d2cb615d2787280
https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=67003

Patch-based Medical Image Segmentation using Matrix Product State Tensor Networks

Autor: Raghavendra Selvan, Erik B Dam, Søren Alexander Flensborg, Jens Petersen

Publikováno v: Selvan, R, Dam, E B, Flensborg, S A & Petersen, J 2022, ' Patch-based Medical Image Segmentation using Matrix Product State Tensor Networks ', The Journal of Machine Learning for Biomedical Imaging, vol. 2022, 005, pp. 1-24 . https://doi.org/10.48550/arXiv.2109.07138

Tensor networks are efficient factorisations of high-dimensional tensors into a network of lower-order tensors. They have been most commonly used to model entanglement in quantum many-body systems and more recently are witnessing increased applicatio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87659be48946ad2b3a7800520bdbc70d
http://arxiv.org/abs/2109.07138

A multispectral camera system for automated minirhizotron image analysis

Autor: Jens Michael Carstensen, Kristian Thorup-Kristensen, Simon F. Svane, Erik B. Dam

Publikováno v: Plant and Soil. 441:657-672

Roots are vital organs for plants, but the assessment of root traits is difficult, particularly in deep soil layers under natural field conditions. A popular technique to investigate root growth under field or semi-field conditions is the use of mini

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dc169e3cc67b83cf4425d6414f8a7f53
https://doi.org/10.1007/s11104-019-04132-8