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Age estimation from whole-body MR images: A proof-of-principle study

Author:Thomas Küstner  Tobias Hepp  Karim Armanious  Konstantin Nikolaou  Sergios Gatidis  Bin Yang  

Institution:King's College London  University Hospital Tübingen  University of Stuttgart  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0808  

Room Live Q&A Session:Wednesday Parallel 3  

Automated Renal Segmentation in Healthy and Chronic Kidney Disease Subjects Using A Convolutional Neural Network

Author:Alexander Daniel  Charlotte Buchanan  Thomas Allcock  Daniel Scerri  Eleanor Cox  Benjamin Prestwich  Susan Francis  

Institution:University of Nottingham  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0811  

Room Live Q&A Session:Wednesday Parallel 3  

Automating Image-Based Body Composition Analysis with Missing Data

Author:Clint Frandsen  Alexander Weston  Kenneth Philbrick  Gian Marco Conte  Bradley Erickson  Timothy Kline  

Institution:Radiology Informatics Lab, Mayo Clinic  Physiology & Biomedical Engineering, Mayo Clinic College of Medicine & Science, Rochester, MN  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0814  

Room Live Q&A Session:Wednesday Parallel 3  

Deep Learning for Determination of Myometrial Invasion Depth and Automatic Lesion Identification Based on Endometrial Cancer MR Imaging

Author:Yida Wang  Yinqiao Yi  Minhua Shen  He Zhang  Xu Yan  Guang Yang  

Institution:East China Normal University  Obstetrics and Gynecology Hospital, Fudan University  Siemens Healthcare  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0810  

Room Live Q&A Session:Wednesday Parallel 3  

Diaphragm motion prediction with a LSTM network using MRI k-space data

Author:Carola Fischer  Florian Friedrich  Peter Bachert  Mark Ladd  Benjamin Knowles  

Institution:German Cancer Research Center (DKFZ)  Heidelberg University  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0813  

Room Live Q&A Session:Wednesday Parallel 3  

Local feature denoising and global feature extraction for malignancy characterization of hepatocellular carcinoma

Author:Wu Zhou  Hui Huang  Guangyi Wang  Honglai Zhang  

Institution:Guangdong General Hospital  Guangzhou University of Chinese Medicine  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0815  

Room Live Q&A Session:Wednesday Parallel 3  

Phase2Phase: Reconstruction of free-breathing MRI into multiple respiratory phases using deep learning without a ground truth

Author:Cihat Eldeniz  Weijie Gan  Sihao Chen  Jiaming Liu  Ulugbek Kamilov  Hongyu An  

Institution:Washington University in St. Louis  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0807  

Room Live Q&A Session:Wednesday Parallel 3  

Transfer Learning-Based Preoperative Prediction of Lymph Node Metastasis

Author:Renee Cattell  Jie Ding  Shenglan Chen  Chuan Huang  

Institution:Stony Brook University  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0809  

Room Live Q&A Session:Wednesday Parallel 3  

Unsupervised radial streak artifact reduction in time resolved MRI

Author:Sagar Mandava  Ty Cashen  Daniel Litwiller  Tetsuya Wakayama  Ersin Bayram  

Institution:Global MR Applications & Workflow, GE Healthcare  

Session Type:Oral  

Session Live Q&A Date:Wednesday, 12 August 2020  

Topic:Machine Learning, Imaging Optimization, and Cancer  

Session Name:Machine Learning in Body MRI  

Program Number:0812  

Room Live Q&A Session:Wednesday Parallel 3