Advanced Faster RCNN: a non-contrast CT-based algorithm for detecting pancreatic lesions in multiple disease stages

• Published in: Nan fang yi ke da xue xue bao = Journal of Southern Medical University Vol. 43; no. 5; p. 755
• Main Authors: Liang, L, Zhang, H, Lu, Q, Zhou, C, Li, S
• Format: Journal Article
• Language: Chinese
• Published: China 20.05.2023
• Subjects: lesion detection; pancreatic cancer; non-contrast CT
• ISSN: 1673-4254
• DOI: 10.12122/j.issn.1673-4254.2023.05.11

To propose a non-contrast CT-based algorithm for automated and accurate detection of pancreatic lesions at a low cost. With Faster RCNN as the benchmark model, an advanced Faster RCNN (aFaster RCNN) model for pancreatic lesions detection based on plain CT was constructed. The model uses the residual connection network Resnet50 as the feature extraction module to extract the deep image features of pancreatic lesions. According to the morphology of pancreatic lesions, 9 anchor frame sizes were redesigned to construct the RPN module. A new Bounding Box regression loss function was proposed to constrain the training process of RPN module regression subnetwork by comprehensively considering the constraints of the lesion shape and anatomical structure. Finally, a detection frame was generated using the detector in the second stage. The data from a total of 728 cases of pancreatic diseases from 4 clinical centers in China were used for training (518 cases, 71.15%) and testing (210 cases, 28.85%) of the model. The pe