This is the train and testing dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) Challenge. This data consists of images of Abdominal CT and MRI from different patients. There are 20 training and 20 testing cases in the CT dataset. MRI dataset contains 20 training and 20 testing cases with T1-Dual and T2 SPIR sequences. Train data contains both DICOM images and their ground truth masks. The testing set only contains DICOM images. In CT cases only livers were annotated. In MRI cases, livers, left/right kidneys, and spleens were annotated. For further information about the data and challenge, please visit https://chaos.grand-challenge.org/ and read the CHAOS_Submission_Manual.pdf Important note: Ground truths/reference...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Abdominal multi-organ segmentation is one of the most attractive topics in the field of medical imag...
This dataset was used as the labeled training set in MICCAI FLARE 2022 Challenge https://flare22.gra...
This is the train and test dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) ...
This is the train and test dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) ...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Abdominal multi-organ segmentation is one of the most attractive topics in the field of medical imag...
This dataset was used as the labeled training set in MICCAI FLARE 2022 Challenge https://flare22.gra...
This is the train and test dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) ...
This is the train and test dataset of Combined (CT-MR) Healthy Abdominal Organ Segmentation (CHAOS) ...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
International audienceSegmentation of abdominal organs has been a comprehensive, yet unresolved, res...
Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many y...
Abdominal multi-organ segmentation is one of the most attractive topics in the field of medical imag...
This dataset was used as the labeled training set in MICCAI FLARE 2022 Challenge https://flare22.gra...