Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation
MICCAI Challenge, FLARE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings
Herausgegeben: Ma, Jun; Wang, Bo
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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 seg...
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 scans
Subtask 2: Abdominal CT organ segmentation on laptop
Subtask 3: Unsupervised domain adaptation for abdominal organ segmentation in MRI Scans
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 scans
Subtask 2: Abdominal CT organ segmentation on laptop
Subtask 3: Unsupervised domain adaptation for abdominal organ segmentation in MRI Scans
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