( en | de | ru )

 

Disambiguation of "Machura, Bartosz"

Author of the publication

copydeleteadd this publication to your clipboard
Segmenting Brain Tumors from MRI Using Cascaded 3D U-Nets.

, , , , , and . BrainLes@MICCAI (2), volume 12659 of Lecture Notes in Computer Science, page 265-277. Springer, (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Jacek Machura

Georg Machura

Stefan Machura

Bartosz Filipecki

Bartosz Rylski

 

Other publications of authors with the same name

Detecting liver cirrhosis in computed tomography scans using clinically-inspired and radiomic features., , , , , , , , and . Comput. Biol. Medicine, (2023)Infusing Domain Knowledge into nnU-Nets for Segmenting Brain Tumors in MRI., , , , and . BrainLes@MICCAI, volume 13769 of Lecture Notes in Computer Science, page 186-194. Springer, (2022)Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients., , , , , , , , , and 4 other author(s). Comput. Biol. Medicine, (March 2023)Fully-automated deep learning-powered system for DCE-MRI analysis of brain tumors., , , , , , , , , and 4 other author(s). Artif. Intell. Medicine, (2020)Federated Evaluation of nnU-Nets Enhanced with Domain Knowledge for Brain Tumor Segmentation., , , , , and . BrainLes@MICCAI (2), volume 14092 of Lecture Notes in Computer Science, page 218-227. Springer, (2022)Robustifying Automatic Assessment of Brain Tumor Progression from MRI., , and . BrainLes@MICCAI, volume 13769 of Lecture Notes in Computer Science, page 90-101. Springer, (2022)Segmenting Brain Tumors from MRI Using Cascaded 3D U-Nets., , , , , and . BrainLes@MICCAI (2), volume 12659 of Lecture Notes in Computer Science, page 265-277. Springer, (2020)Coupling nnU-Nets with Expert Knowledge for Accurate Brain Tumor Segmentation from MRI., , , , and . BrainLes@MICCAI (2), volume 12963 of Lecture Notes in Computer Science, page 197-209. Springer, (2021)Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre- and post-operative glioblastoma patients., , , , , , , , , and 4 other author(s). CoRR, (2022)