4.2k citations · 4.4k across the 4 of their papers we have counts for
3 papers · 1 filter
A Physics-Guided Modular Deep-Learning Based Automated Framework for Tumor Segmentation in PET Images
Kevin H. Leung, Wael Marashdeh, Rick Wray +4
The objective of this study was to develop a PET tumor-segmentation framework that addresses the challenges of limited spatial resolution, high image noise, and lack of clinical tr…
Next Generation Radiogenomics Sequencing for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients Using Multimodal Imaging and Machine Learning Approaches
Isaac Shiri, Hassan Maleki, Ghasem Hajianfar +5
Aim: In the present work, we aimed to evaluate a comprehensive radiomics framework that enabled prediction of EGFR and KRAS mutation status in NSCLC cancer patients based on PET an…
PET/CT Radiomic Sequencer for Prediction of EGFR and KRAS Mutation Status in NSCLC Patients
Isaac Shiri, Hassan Maleki, Ghasem Hajianfar +5
The aim of this study was to develop radiomic models using PET/CT radiomic features with different machine learning approaches for finding best predictive epidermal growth factor r…