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Artificial Intelligence for Predicting Pathological Complete Response to Neoadjuvant Chemotherapy from MRI and Prognostic Clinical Features

Author:Hongyi Duanmu  Pauline Huang  Srinidhi Brahmavar  Fusheng Wang  Tim Q Duong  

Institution:Stony Brook University  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0267  

Room Live Q&A Session:Monday Parallel 5  

Evaluating Noise Robustness of CNN-based Head&Neck Tumor Segmentations on Multiparametric MRI Data

Author:Lars Bielak  Nicole Wiedenmann  Arnie Berlin  Leonard Hägele  Thomas Lottner  Sebastian Gross  Anca-Ligia Grosu  Michael Bock  

Institution:Medical Center - University of Freiburg, Faculty of Medicine  The MathWorks, Inc.  German Cancer Consortium (DKTK), Partner Site Freiburg  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0269  

Room Live Q&A Session:Monday Parallel 5  

Identification of Sarcomatoid De-Differentiation in Renal Cell Carcinoma by Machine Learning on Multiparametric MRI

Author:Asim Mazin  Samuel Hawkins  Olya Stringfield  Jasreman Dhillon  Brandon Manley  Daniel Jeong  Natarajan Raghunand  

Institution:Moffitt Cancer Center  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0266  

Room Live Q&A Session:Monday Parallel 5  

The impact of radiomic feature reproducibility on a head and neck cancer radiotherapy response model: a comparison of two common analysis packages

Author:James Korte  Carlos Cardenas  Tomas Kron  Nicholas Hardcastle  Jihong Wang  Houda Bahig  Baher Elgohari  Laurence Court  Clifton Fuller  Sweet Ng  

Institution:Centre Hospitalier de l'Université de Montréal  Peter MacCallum Cancer Centre  The University of Texas MD Anderson Cancer Center  University of Texas MD Anderson Cancer Center  The University of Melbourne  University of Wollongong  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0268  

Room Live Q&A Session:Monday Parallel 5  

Proof-of-principle for endogenous signal classification towards voxel-wise tumor detection using statistical machine learning

Author:Artur Hahn  Julia Krüwel-Bode  Yannis Seemann  Sarah Schuhegger  Johann Jende  Anja Hohmann  Volker Sturm  Ke Zhang  Sabine Heiland  Martin Bendszus  Michael Breckwoldt  Christian Ziener  Felix Kurz  

Institution:German Cancer Research Center (DKFZ)  Heidelberg University Hospital  University of Heidelberg  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0264  

Room Live Q&A Session:Monday Parallel 5  

Radiomic features of cervical tumors: identifying volume thresholds for transition to a poor prognosis phenotype

Author:Benjamin Wormald  Thomas Ind  Nandita deSouza  

Institution:The Institute of Cancer Research  The Royal Marsden NHS FoundationTrust  St. Georges University Hospital  The Royal Marsden NHS Foundation Trust  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0265  

Room Live Q&A Session:Monday Parallel 5  

Radiomics analysis for Characterizing Ovarian Tumor Based on a DCE-MRI Pharmacokinetic Protocol

Author:Xiao-li Song  Jia-Liang Ren  Kaiyu Wang  Jinliang Niu  

Institution:GE Healthcare, Beijing, China.  GE Healthcare, Beijing, China  Shanxi Medical University Second Affiliated Hospital  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:1243  

Room Live Q&A Session:Monday Parallel 5  

Triaging dense breast screening MR images using a dilated convolutional neural network

Author:Angelo Zuffianò  Bob de Vos  Jorrit Glastra  Pim Moeskops  Valerio Fortunati  Ivana Išgum  Tim Leiner  Carla van Gils  Wouter Veldhuis  

Institution:Amsterdam University Medical Center  Quantib  Utrecht University Medical Center  

Session Type:Oral  

Session Live Q&A Date:Monday, 10 August 2020  

Topic:Cancer Imaging: Machine Learning & Advanced Imaging  

Session Name:Cancer Imaging: Machine Learning  

Program Number:0263  

Room Live Q&A Session:Monday Parallel 5