- Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images
Samuel G. Armato et al, 2017, Medical Imaging 2017: Computer-Aided Diagnosis CrossRef - A two-step convolutional neural network based computer-aided detection scheme for automatically segmenting adipose tissue volume depicting on CT images
Yunzhi Wang et al, 2017, Computer Methods and Programs in Biomedicine CrossRef - Exploring a new quantitative image marker to assess benefit of chemotherapy to ovarian cancer patients
Tessa S. Cook et al, 2017, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications CrossRef - Anti-tumor effect of Scutellaria barbata D. Don extracts on ovarian cancer and its phytochemicals characterisation
Lin Zhang et al, 2017, Journal of Ethnopharmacology CrossRef - Piperine functions as a tumor suppressor for human ovarian tumor growth via activation of JNK/p38 MAPK-mediated intrinsic apoptotic pathway
Lihui Si et al, 2018, Bioscience Reports CrossRef - An Effective CNN Method for Fully Automated Segmenting Subcutaneous and Visceral Adipose Tissue on CT Scans
Zheng Wang et al, 2020, Annals of Biomedical Engineering CrossRef - Utilizing a Pathomics Biomarker to Predict the Effectiveness of Bevacizumab in Ovarian Cancer Treatment
Patrik Gilley et al, 2024, Bioengineering CrossRef - Applying Quantitative CT Image Feature Analysis to Predict Response of Ovarian Cancer Patients to Chemotherapy
Gopichandh Danala et al, 2017, Academic Radiology CrossRef - Correlation of imaging and plasma based biomarkers to predict response to bevacizumab in epithelial ovarian cancer (EOC)
Megan E. Buechel et al, 2021, Gynecologic Oncology CrossRef - Developing global image feature analysis models to predict cancer risk and prognosis
Bin Zheng et al, 2019, Visual Computing for Industry, Biomedicine, and Art CrossRef - Body Composition and Metabolic Dysfunction Really Matter for the Achievement of Better Outcomes in High-Grade Serous Ovarian Cancer
Mauricio A. Cuello et al, 2023, Cancers CrossRef - Development and Assessment of a New Global Mammographic Image Feature Analysis Scheme to Predict Likelihood of Malignant Cases
Morteza Heidari et al, 2020, IEEE Transactions on Medical Imaging CrossRef - Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review
Antti Tolonen et al, 2021, European Journal of Radiology CrossRef - Anti-angiogenic therapy in ovarian cancer: Current understandings and prospects of precision medicine
Chao Mei et al, 2023, Frontiers in Pharmacology CrossRef - Applying a computer-aided scheme to detect a new radiographic image marker for prediction of chemotherapy outcome
Yunzhi Wang et al, 2016, BMC Medical Imaging CrossRef - The role of pazopanib on tumour angiogenesis and in the management of cancers: A review
Dinesh Kumar Chellappan et al, 2017, Biomedicine & Pharmacotherapy CrossRef