Artificial intelligence–based technology for semi-automated segmentation of rectal cancer using high-resolution MRI

ABSTRACT:

Aim

Although MRI has a substantial role in directing treatment decisions for locally advanced rectal cancer, precise interpretation of the findings is not necessarily available at every institution. In this study, we aimed to develop artificial intelligence-based software for the segmentation of rectal cancer that can be used for staging to optimize treatment strategy and for preoperative surgical simulation.

Method

Images from a total of 201 patients who underwent preoperative MRI were analyzed for training data. The resected specimen was processed in a circular shape in 103 cases. Using these datasets, ground-truth labels were prepared by annotating MR images with ground-truth segmentation labels of tumor area based on pathologically confirmed lesions. In addition, the

SUBMITTER: Hamabe A 

PROVIDER: S-EPMC9205476 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature