AAPM VL-Data Science, Radiomics, and Computing

2021 AAPM Virtual 63rd Annual Meeting - Session: Data Science, Radiomics, and Computing

Multi-Class Classification Based On Multi-Loss Strategy and Auxiliary Deep Learning Network with Applications in Medical Imaging
Zong Fan University of Illinois Urbana-Champaign

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All videos in this session:

	A Multi-Modality Radiomics-Based Model for Recurrence Risk Stratification in Non-Small Cell Lung Cancer - Jaryd Christie Western University
	Computer-Assisted Diagnosis of Hepatic Portal Hypertension: A Novel, Attention-Guided Deep Learning Framework Based On CT Imaging and Laboratory Data Integration - Yuqi Wang Duke University
	JACK KROHMER EARLY-CAREER INVESTIGATOR COMPETITION WINNER: Multi-Group Multi-Block Data Integration for Harmonizing 18F-FDG-PET/CT Radiomics Associated with Circulating Tumor Cells and Predicting Recurrence-Free Survival Across Independent Lung Cancer Radiotherapy Studies - Sang Ho Lee, PhD University of Pennsylvania
	Multi-Institutional Data Analysis of Radiomic Signature Set to Predict Overall Survival in Glioblastoma Patients - Eric Carver Wayne State University
	A Radiomics-Boosted Deep Learning Model for COVID-19 and Non-COVID-19 Pneumonia Detection Using Chest X-Ray Image - Zongsheng Hu Duke Kunshan University
	Spatial Reconstruction of Statistically Significant Radiomics Signatures Using 3D Wavelet Decomposition in Tumors of Oropharyngeal Cancer - Hassan Bagher-Ebadian Henry Ford Health System
	Q & A -

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AAPM Virtual Library

2021 AAPM Virtual 63rd Annual Meeting - Session: Data Science, Radiomics, and Computing