Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation
Produktnummer:
1890014723c21146c2be6c0cdab42f9706
| Themengebiete: | Abdomen Artificial intelligence Computed tomography Computer vision Computer vision tasks Computing methodologies Machine learning Medical Image Segmentation Organ Scene understanding |
|---|---|
| Veröffentlichungsdatum: | 10.07.2025 |
| EAN: | 9783031962011 |
| Sprache: | Englisch |
| Seitenzahl: | 270 |
| Produktart: | Kartoniert / Broschiert |
| Herausgeber: | Ma, Jun Wang, Bo |
| Verlag: | Springer International Publishing |
| Untertitel: | MICCAI Challenge, FLARE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings |
Produktinformationen "Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation"
This book constitutes the proceedings of the MICCAI 2024 Challenge, FLARE 2024, held in Conjunction with MICCAI 2024, in Marrakesh, Morocco, during October 2024. The 20 full papers included in this book were carefully reviewed and selected from 24 submissions. They describe the solutions the participants found for automatic abdominal organ and pan-cancer segmentation using the official training dataset released for this pupose.This challenge focuses on both organ and pan-cancer segmentation, including three subtasks:Subtask 1: Pan-cancer segmentation in CT scansSubtask 2: Abdominal CT organ segmentation on laptopSubtask 3: Unsupervised domain adaptation for abdominal organ segmentation in MRI Scans
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