211 citations · 290 across the 15 of their papers we have counts for
4 papers · 1 filter
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…
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…
CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging
Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas +3
Cox proportional hazard model (CPH) is commonly used in clinical research for survival analysis. In quantitative medical imaging (radiomics) studies, CPH plays an important role in…
Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma
Yucheng Zhang, Edrise M. Lobo-Mueller, Paul Karanicolas +3
Pancreatic Ductal Adenocarcinoma (PDAC) is one of the most aggressive cancers with an extremely poor prognosis. Radiomics has shown prognostic ability in multiple types of cancer i…