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Artificial Intelligence Analysis on Prostate DCE-MRI to Distinguish Prostate Cancer and Benign Prostatic Hyperplasia

Automatic Detection and Segmentation of Breast Cancer on MRI Using Mask R-CNN Trained on Non-Fat-Sat Images and Tested on Fat-Sat Images

Classification of Spinal Metastases Coming from Different Primary Cancer Origin by Using Quantitative Radiomics Analysis with Multi-Class SVM

Author:Yongye Chen  Yang Zhang  Enlong Zhang  Xiaoying Xing  Qizheng Wang  Huishu Yuan  Min-Ying Su  Ning Lang  

Institution:Peking University Third Hospital  University of California  

Session Type:Oral - Power Pitch  

Session Live Q&A Date:Thursday, 13 August 2020  

Topic:Hot Topics & Cancer  

Session Name:Musculoskeletal 1  

Program Number:1149  

Room Live Q&A Session:Thursday Parallel 1  

Comparison of Breast Cancer Diagnostic Performance Using Radiomics Models Built Based on Features Extracted from DCE-MRI and Mammography

Deep learning for the detection and differentiation of vertebral fracture

Diagnosis of Benign and Malignant Breast Lesions on DCE-MRI by Using Radiomics and Deep Learning with Consideration of Peri-Tumor Tissue

Diagnosis of Non-Mass-Like Enhancement Lesions on DCE-MRI by Using Quantitative Radiomics and Radiologists’ BI-RADS Reading

Differentiation of Breast Cancer Molecular Subtypes on DCE-MRI by Using Convolutional Neural Network with Transfer Learning

Radiomics and Machine Learning for Prediction of Recurrence in Meningiomas

Radiomics Approach for Prediction of Recurrence in Pituitary Macroadenomas