2 citations · 3 across the 5 of their papers we have counts for
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Alternating Segmentation and Simulation for Contrast Adaptive Tissue Classification
Dzung L. Pham, Snehashis Roy
A key feature of magnetic resonance (MR) imaging is its ability to manipulate how the intrinsic tissue parameters of the anatomy ultimately contribute to the contrast properties of…
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…
TBI Contusion Segmentation from MRI using Convolutional Neural Networks
Snehashis Roy, John A. Butman, Leighton Chan +1
Traumatic brain injury (TBI) is caused by a sudden trauma to the head that may result in hematomas and contusions and can lead to stroke or chronic disability. An accurate quantifi…
Classifying magnetic resonance image modalities with convolutional neural networks
Samuel Remedios, Dzung L. Pham, John A. Butman +1
Magnetic Resonance (MR) imaging allows the acquisition of images with different contrast properties depending on the acquisition protocol and the magnetic properties of tissues. Ma…
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…