Extended Task10_Colon Medical Decathlon (Extended Task10_Colon of Medical Segmentation Decathlon dataset)

A dataset of abdominal CT studies in NifTi format from the open-source medical data repository Medical Decathlon was utilized. To expedite the partitioning process, the MONAILabel plugin of the MONAI framework within the 3D Slicer program was employed. A radiologist with 15 years of experience conducted a validation process, wherein the boundaries of the colon markup were verified on each slice. The existing colorectal cancer markings in the dataset remained unaltered. Validation by a radiologist reduced the size of the validated dataset to 122 studies. In this case, the 122 studies were categorized into three subsets based on the quality of the data: The "good" subset comprises 100 studies, while the "bad" subset contains 17 cropped studies (in which the entire colon is not visible on the image). The "bad" subset comprises five studies. Two of these studies were of poor quality and could not identify the entire colon. Two further studies involved colon stomas following surgery, while one study involved a hernia. Four studies were excluded from the set due to broken images, with axial plane images duplicated or the slice order mixed