Fast Low Resource Accurate Robust Organ And Pan Cancer Segmentation
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Fast Low Resource Accurate Robust Organ And Pan Cancer Segmentation
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Author : Jun Ma
language : en
Publisher: Springer Nature
Release Date : 2025-07-09
Fast Low Resource Accurate Robust Organ And Pan Cancer Segmentation written by Jun Ma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-09 with Computers categories.
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
Fast Low Resource And Accurate Organ And Pan Cancer Segmentation In Abdomen Ct
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Author : Jun Ma
language : en
Publisher: Springer Nature
Release Date : 2024-07-01
Fast Low Resource And Accurate Organ And Pan Cancer Segmentation In Abdomen Ct written by Jun Ma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-01 with Computers categories.
This book constitutes the proceedings of the MICCAI 2023 Challenge, FLARE 2023, held in Conjunction with MICCAI 2023, in Vancouver, BC, Canada, on October 8, 2023. The 27 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers present research and results for abdominal organ segmentation which has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis.
Bulletin Of The Atomic Scientists
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Author :
language : en
Publisher:
Release Date : 1973-10
Bulletin Of The Atomic Scientists written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973-10 with categories.
The Bulletin of the Atomic Scientists is the premier public resource on scientific and technological developments that impact global security. Founded by Manhattan Project Scientists, the Bulletin's iconic "Doomsday Clock" stimulates solutions for a safer world.
Fast Low Resource And Accurate Organ And Pan Cancer Segmentation In Abdomen Ct
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Author : Jun Ma
language : en
Publisher: Springer
Release Date : 2024-07-14
Fast Low Resource And Accurate Organ And Pan Cancer Segmentation In Abdomen Ct written by Jun Ma and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-14 with Computers categories.
This book constitutes the proceedings of the MICCAI 2023 Challenge, FLARE 2023, held in Conjunction with MICCAI 2023, in Vancouver, BC, Canada, on October 8, 2023. The 27 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers present research and results for abdominal organ segmentation which has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis.
Conference Papers Index
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Author :
language : en
Publisher:
Release Date : 1987
Conference Papers Index written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Engineering categories.
Fast And Low Resource Semi Supervised Abdominal Organ Segmentation
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Author : Jun Ma
language : en
Publisher: Springer Nature
Release Date : 2023-01-20
Fast And Low Resource Semi Supervised Abdominal Organ Segmentation written by Jun Ma and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-20 with Computers categories.
This book constitutes the proceedings of the MICCAI 2022 Challenge, FLARE 2022, held in Conjunction with MICCAI 2022, in Singapore, on September 22, 2022. The 28 full papers presented in this book were carefully reviewed and selected from 48 submissions. The papers present research and results for abdominal organ segmentation which has many important clinical applications, such as organ quantification, surgical planning, and disease diagnosis.
Model Based Validation Scheme For Organ Segmentation In Medical Image Data
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Author : Hossein Badakhshannoory
language : en
Publisher:
Release Date : 2011
Model Based Validation Scheme For Organ Segmentation In Medical Image Data written by Hossein Badakhshannoory and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Diagnostic imaging categories.
Model based methods have proven to be among the most reliable and robust solutions for application of medical image processing in organ segmentation and reconstruction. They assume a repetitive geometric pattern for the organ of interest and therefore utilize probabilistic models to characterize organs shape or other attributes. A common strategy, adopted by most of the model based methods, is to use model attributes as prior information in the actual segmentation process. In this work, we propose a novel approach for accurate 3D organ segmentation and modeling in the CT scan volumes. Instead of direct use of the organs prior information in the segmentation process, here we utilize the knowledge of the organ to validate a large number of potential segmentation hypotheses that are generated by a generic segmentation process. For this, PCA based organ space is utilized to measure the fidelity of each segment to the organ. We detail applications of the proposed method for 3D segmentation of human kidney and liver in CT scan volumes. For evaluation purposes, the public database of MICCAI 2007 grand challenge workshop has been used. Implementation results show an average Dice similarity measure of 90% for segmentation of the kidney which shows better results than the 88.6% presented by other kidney segmentation methods. For the liver, the proposed algorithm achieves an average volume overlap error of 8.7% and an average surface distance of 1.51 mm while the best reported average values for these measures are 6.65% and 1.03 mm by an automatic algorithm on the same dataset.