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Developing a novel image marker to predict the clinical outcome of neoadjuvant chemotherapy (NACT) for ovarian cancer patients., , , , , , , , , and . Comput. Biol. Medicine, (2024)Virtual Adversarial Training for Semi-supervised Breast Mass Classification., , , , , , , , , and . CoRR, (2022)Developing a new radiomics-based CT image marker to detect lymph node metastasis among cervical cancer patients., , , , , , , , , and . Comput. Methods Programs Biomed., (2020)A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images., , , , , and . Comput. Methods Programs Biomed., (2017)Developing a Novel Image Marker to Predict the Responses of Neoadjuvant Chemotherapy (NACT) for Ovarian Cancer Patients., , , , , , , , , and . CoRR, (2023)A performance comparison of low- and high-level features learned by deep convolutional neural networks in epithelium and stroma classification., , , , , , , , and . Medical Imaging: Digital Pathology, volume 10581 of SPIE Proceedings, page 1058116. SPIE, (2018)Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 101343G. SPIE, (2017)Apply radiomics approach for early stage prognostic evaluation of ovarian cancer patients: a preliminary study., , , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10134 of SPIE Proceedings, page 1013449. SPIE, (2017)Recent advances and clinical applications of deep learning in medical image analysis., , , , , , , , , and . Medical Image Anal., (2022)Recent advances and clinical applications of deep learning in medical image analysis., , , , , , , , , and 1 other author(s). CoRR, (2021)