211 citations · 290 across the 15 of their papers we have counts for
17 papers
Synthetic Correlated Diffusion Imaging Hyperintensity Delineates Clinically Significant Prostate Cancer
Alexander Wong, Hayden Gunraj, Vignesh Sivan +1
Prostate cancer (PCa) is the second most common cancer in men worldwide and the most frequently diagnosed cancer among men in more developed countries. The prognosis of PCa is exce…
A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account
Khashayar Namdar, Masoom A. Haider, Farzad Khalvati
Receiver operating characteristic (ROC) curve is an informative tool in binary classification and Area Under ROC Curve (AUC) is a popular metric for reporting performance of binary…
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-weighted MRI using Convolutional Neural Networks
Ruqian Hao, Khashayar Namdar, Lin Liu +2
Data augmentation refers to a group of techniques whose goal is to battle limited amount of available data to improve model generalization and push sample distribution toward the t…
Evolution-based Fine-tuning of CNNs for Prostate Cancer Detection
Khashayar Namdar, Isha Gujrathi, Masoom A. Haider +1
Convolutional Neural Networks (CNNs) have been used for automated detection of prostate cancer where Area Under Receiver Operating Characteristic (ROC) curve (AUC) is usually used…
A Transfer Learning Approach for Automated Segmentation of Prostate Whole Gland and Transition Zone in Diffusion Weighted MRI
Saman Motamed, Isha Gujrathi, Dominik Deniffel +3
The segmentation of prostate whole gland and transition zone in Diffusion Weighted MRI (DWI) are the first step in designing computer-aided detection algorithms for prostate cancer…
Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images
Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas +3
As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past a few years. Recent studies in radiomics aim to investigat…