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Automated Localization and Segmentation of Locally-Advanced Rectal Cancer Based on T2, DWI and DCE Multi-Parametric MRI Using Deep Learning

Evaluation of MRI-Guided Radiotherapy Planning Target Volume Delineation for Colorectal Cancer Due to Variations in Image Contrast and Patient Motion

Machine Learning for Prediction of Chemoradiation Therapy Response in Patients with Locally-Advanced Rectal Cancer (LARC) Using Pre- and Early-Treatment Follow-up Multiparametric MRI

Author:Yang Zhang  Liming Shi  Xiaonan Sun  Tianye Niu  Ning Yue  Tiffany Kwong  Peter Chang  Melissa Khy  Daniel Chow  Min-Ying Su  Ke Nie  

Author Institution:Rutgers-The State University of New Jersey  Sir Run Run Shaw Hospital, Zhejiang University School of Medicine  University of California  

Session Type:Oral  

Session Date:Wednesday, 20 June 2018  

Session Time:13:45  

Session:Pancreas/GI  

Program Number:0829  

Presentation Time:14:57  

Room Number:S05  

Computer Number:

Radiomics subtyping improves 5-year disease free survival prediction beyond key clinical and radiological characteristics in patients with locally advanced rectal cancer (LARC)