Monitoring response to neoadjuvant therapy for breast cancer in all treatment phases using an ultrasound deep learning model
Jingwen Zhang,
Jingwen Deng,
Jin Huang
et al.
Abstract:PurposeThe aim of this study was to investigate the value of a deep learning model (DLM) based on breast tumor ultrasound image segmentation in predicting pathological response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodsThe dataset contains a total of 1393 ultrasound images of 913 patients from Renmin Hospital of Wuhan University, of which 956 ultrasound images of 856 patients were used as the training set, and 437 ultrasound images of 57 patients underwent NAC were used as the test set. A U-Net… Show more
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