Automatic stratification of gliomas into WHO 2016 molecular subtypes using diffusion-weighted imaging and a pre-trained deep neural network

Computer-aided detection and segmentation of brain metastases in MRI for stereotactic radiosurgery via a deep learning ensemble

Author:Zijian Zhou  Jeremiah Sanders  Jason Johnson  Tina Briere  Mark Pagel  Jing Li  Jingfei Ma  

Institution:The University of Texas MD Anderson Cancer Center  

Session Type:Oral  

Session Live Q&A Date:Tuesday, 11 August 2020  

Topic:Brain tumors  

Session Name:Emerging AI Applications in Neuro-Oncology  

Program Number:0421  

Room Live Q&A Session:Tuesday Parallel 2  

Fast multimodal image fusion with deep 3D convolutional networks for neurosurgical guidance – A preliminary study

Author:Jhimli Mitra  Soumya Ghose  David Mills  Lowell Smith  Sarah Frisken  Alexandra Golby  Thomas Foo  Desmond Yeo  

Institution:Brigham and Women's Hospital  General Electric Research  

Session Type:Oral  

Session Live Q&A Date:Tuesday, 11 August 2020  

Topic:Brain tumors  

Session Name:Emerging AI Applications in Neuro-Oncology  

Program Number:0419  

Room Live Q&A Session:Tuesday Parallel 2  

Identifying Overall Survival in Glioblastoma Patients Using VASARI Features at 3T

Author:Banu Sacli-Bilmez  Zeynep Firat  Melih Topcuoglu  C. Kaan Yaltirik  Ugur Türe  Esin Ozturk-Isik  

Institution:Bogazici University  Yeditepe University  

Session Type:Oral  

Session Live Q&A Date:Tuesday, 11 August 2020  

Topic:Brain tumors  

Session Name:Emerging AI Applications in Neuro-Oncology  

Program Number:0422  

Room Live Q&A Session:Tuesday Parallel 2  

IDH1 genotype prediction in lower-grade gliomas: a machine learning study with VASARI and ADC radiomics

MRI-based Radiomics as a Predictive Biomarker of Survival in High Grade Gliomas Treated with Chimeric Antigen Receptor T-Cell Therapy

A radiomic signature for predicting recurrence of FLAIR abnormality in glioblastomas using multi-modal MRI

An RNN and Autoencoder-based Deep Learning Approach for Detecting Brain Metastases in MRI

Using anatomic and diffusion MRI with deep convolutional neural networks to distinguish treatment-induced injury from recurrent glioblastoma