361 citations
- University of California, Los AngelesUS8 papers
- Stanford UniversityUS6 papers
- Icahn School of Medicine at Mount SinaiUS4 papers
- University of California, San FranciscoUS4 papers
- University of EdinburghGB4 papers
- Cedars-Sinai Smidt Heart InstituteUS3 papers
- Child Health and Development InstituteUS3 papers
- Shahid Beheshti University of Medical SciencesIR3 papers
- The Queen's Medical Research InstituteGB3 papers
- University of WashingtonUS3 papers
- Brigham Young UniversityUS2 papers
- Columbia UniversityUS2 papers
4 papers · 1 filter
A novel 3D multi-path DenseNet for improving automatic segmentation of glioblastoma on pre-operative multi-modal MR images
Jie Fu, Kamal Singhrao, X. Sharon Qi +3
Convolutional neural networks have achieved excellent results in automatic medical image segmentation. In this study, we proposed a novel 3D multi-path DenseNet for generating the…
An automatic deep learning-based workflow for glioblastoma survival prediction using pre-operative multimodal MR images
Jie Fu, Kamal Singhrao, Xinran Zhong +5
We proposed a fully automatic workflow for glioblastoma (GBM) survival prediction using deep learning (DL) methods. 285 glioma (210 GBM, 75 low-grade glioma) patients were included…
Deep Learning-based Radiomic Features for Improving Neoadjuvant Chemoradiation Response Prediction in Locally Advanced Rectal Cancer
Jie Fu, Xinran Zhong, Ning Li +6
Radiomic features achieve promising results in cancer diagnosis, treatment response prediction, and survival prediction. Our goal is to compare the handcrafted (explicitly designed…
Generation of abdominal synthetic CTs from 0.35T MR images using generative adversarial networks for MR-only liver radiotherapy
Jie Fu, Kamal Singhrao, Minsong Cao +7
Electron density maps must be accurately estimated to achieve valid dose calculation in MR-only radiotherapy. The goal of this study is to assess whether two deep learning models,…