Deep learning models for preoperative T-stage assessment in rectal cancer using MRI: exploring the impact of rectal filling
Chang Tian,
Xiaolu Ma,
Haidi Lu
et al.
Abstract:BackgroundThe objective of this study was twofold: firstly, to develop a convolutional neural network (CNN) for automatic segmentation of rectal cancer (RC) lesions, and secondly, to construct classification models to differentiate between different T-stages of RC. Additionally, it was attempted to investigate the potential benefits of rectal filling in improving the performance of deep learning (DL) models.MethodsA retrospective study was conducted, including 317 consecutive patients with RC who underwent MRI… Show more
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