Mathias Perslev

According to our database, Mathias Perslev authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Fully Automated Tumor Segmentation for Brain MRI data using Multiplanner UNet.

Sumit Pandey, Satyasaran Changdar, Mathias Perslev, Erik B. Dam

CoRR, 2024

Local Gamma Augmentation for Ischemic Stroke Lesion Segmentation on MRI.

Jon Middleton, Marko Bauer, Kaining Sheng, Jacob Johansen, Mathias Perslev, Silvia Ingala, Mads Nielsen, Akshay Pai

Proceedings of the Northern Lights Deep Learning Conference, 2024

2023

Multi-planar 3D knee MRI segmentation via UNet inspired architectures.

Sandeep Singh Sengar, Christopher Meulengracht, Mikael Ploug Boesen, Anders Føhrby Overgaard, Henrik Gudbergsen, Janus Damm Nybing, Mathias Perslev, Erik Bjørnager Dam

Int. J. Imaging Syst. Technol., May, 2023

The Liver Tumor Segmentation Benchmark (LiTS).

Patrick Bilic, Patrick Ferdinand Christ, Hongwei Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland H. 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, Miriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Grün, 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 K. Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John S. Lowengrub, Jun Ma, Klaus H. 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, Manuel Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern H. Menze

Medical Image Anal., 2023

Advancing Kidney, Kidney Tumor, Cyst Segmentation: A Multi-Planner U-Net Approach for the KiTS23 Challenge.

Sumit Pandey, Toshali, Mathias Perslev, Erik B. Dam

Proceedings of the Kidney and Kidney Tumor Segmentation - MICCAI 2023 Challenge, 2023

2022

Can information on past and near-future weather and field conditions predict the safest pesticide application day?

Jeanne Vuaille, Maja Holbak, Mathias Perslev, Efstathios Diamantopoulos, Signe M. Jensen, Merete E. Styczen, Carsten T. Petersen, Bjarne W. Strobel, Per Abrahamsen

Comput. Electron. Agric., 2022

2021

U-Sleep: resilient high-frequency sleep staging.

Mathias Perslev, Sune Darkner, Lykke Kempfner, Miki Nikolic, Poul Jørgen Jennum, Christian Igel

npj Digit. Medicine, 2021

The Medical Segmentation Decathlon.

Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern H. Menze, Olaf Ronneberger, Ronald M. Summers, Bram van Ginneken, Michel Bilello, Patrick Bilic, Patrick Ferdinand Christ, Richard K. G. Do, Marc Gollub, Stephan Heckers, Henkjan J. Huisman, William R. Jarnagin, Maureen McHugo, Sandy Napel, Jennifer Goli-Pernicka, Kawal S. Rhode, Catalina Tobon-Gomez, Eugene Vorontsov, James A. Meakin, Sébastien Ourselin, Manuel Wiesenfarth, Pablo Arbeláez, Byeonguk Bae, Sihong Chen, Laura Alexandra Daza, Jianjiang Feng, Baochun He, Fabian Isensee, Yuanfeng Ji, Fucang Jia, Namkug Kim, Ildoo Kim, Dorit Merhof, Akshay Pai, BeomHee Park, Mathias Perslev, Ramin Rezaiifar, Oliver Rippel, Ignacio Sarasua, Wei Shen, Jaemin Son, Christian Wachinger, Liansheng Wang, Yan Wang, Yingda Xia, Daguang Xu, Zhanwei Xu, Yefeng Zheng, Amber L. Simpson, Lena Maier-Hein, M. Jorge Cardoso

CoRR, 2021

How Few Annotations are Needed for Segmentation Using a Multi-planar U-Net?

William Michael Laprade, Mathias Perslev, Jon Sporring

Proceedings of the Deep Generative Models, and Data Augmentation, Labelling, and Imperfections, 2021

2020

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset.

Arjun D. Desai, Francesco Calivá, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew A. Torigian, Jutta Ellermann, Mehmet Akçakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry Gold, Brian A. Hargreaves, Valentina Pedoia, Akshay S. Chaudhari

CoRR, 2020

2019

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging.

Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jørgen Jennum, Christian Igel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation.

Mathias Perslev, Erik Bjørnager Dam, Akshay Pai, Christian Igel

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Accurate Segmentation of Dental Panoramic Radiographs with U-NETS.

Thorbjørn Louring Koch, Mathias Perslev, Christian Igel, Sami Sebastian Brandt

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019