509 citations
- National Institutes of HealthUS4 papers
- Johns Hopkins UniversityUS3 papers
- Center for Neuroscience and Regenerative MedicineUS2 papers
- El Camino HospitalUS1 paper
- Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUS1 paper
- Google (United States)US1 paper
- Jackson FoundationUS1 paper
- National Institutes of Health Clinical CenterUS1 paper
- Naval Medical Center San DiegoUS1 paper
- Tempus Labs (United States)US1 paper
- University Health NetworkCA1 paper
- University of DelawareUS1 paper
6 papers
Data-driven Uncertainty Quantification in Computational Human Head Models
Kshitiz Upadhyay, Dimitris G. Giovanis, Ahmed Alshareef +6
Computational models of the human head are promising tools for estimating the impact-induced response of brain, and thus play an important role in the prediction of traumatic brain…
Contrast Adaptive Tissue Classification by Alternating Segmentation and Synthesis
Dzung L. Pham, Yi-Yu Chou, Blake E. Dewey +3
Deep learning approaches to the segmentation of magnetic resonance images have shown significant promise in automating the quantitative analysis of brain images. However, a continu…
Development and Validation of a Deep Learning Algorithm for Improving Gleason Scoring of Prostate Cancer
Kunal Nagpal, Davis Foote, Yun Liu +17
For prostate cancer patients, the Gleason score is one of the most important prognostic factors, potentially determining treatment independent of the stage. However, Gleason scorin…
Synthesizing CT from Ultrashort Echo-Time MR Images via Convolutional Neural Networks
Snehashis Roy, John A. Butman, Dzung L. Pham
With the increasing popularity of PET-MR scanners in clinical applications, synthesis of CT images from MR has been an important research topic. Accurate PET image reconstruction r…
Multiple Sclerosis Lesion Segmentation from Brain MRI via Fully Convolutional Neural Networks
Snehashis Roy, John A. Butman, Daniel S. Reich +2
Multiple Sclerosis (MS) is an autoimmune disease that leads to lesions in the central nervous system. Magnetic resonance (MR) images provide sufficient imaging contrast to visualiz…
Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI): A framework for single-subject analysis in diffusion tensor imaging
Cheng Guan Koay, Ping-Hong Yeh, John M. Ollinger +5
The purpose of this work is to develop a framework for single-subject analysis of diffusion tensor imaging (DTI) data. This framework (termed TOADDI) is capable of testing whether…