Fully end-to-end deep-learning-based diagnosis of pancreatic tumors.

ABSTRACT: Artificial intelligence can facilitate clinical decision making by considering massive amounts of medical imaging data. Various algorithms have been implemented for different clinical applications. Accurate diagnosis and treatment require reliable and interpretable data. For pancreatic tumor diagnosis, only 58.5% of images from the First Affiliated Hospital and the Second Affiliated Hospital, Zhejiang University School of Medicine are used, increasing labor and time costs to manually filter out images not directly used by the diagnostic model. Methods: This study used a training dataset of 143,945 dynamic contrast-enhanced CT images of the abdomen from 319 patients. The proposed model contained four stages: image screening, pancreas location, pancreas segmentation, and pancreatic tu

SUBMITTER: Si K 

PROVIDER: S-EPMC7778580 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature