Snehashis Roy | DeepAI

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Bennett A. Landman
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Vishwesh Nath
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Zihao Wu
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Dzung L. Pham
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Blake E. Dewey
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John A. Butman
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Daniel S. Reich
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Samuel W. Remedios
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Samuel Remedios
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∙ 03/04/2021

Contrast Adaptive Tissue Classification by Alternating Segmentation and Synthesis

Deep learning approaches to the segmentation of magnetic resonance image...

0 Dzung L. Pham, et al. ∙

∙ 11/13/2019

Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection

Multiple instance learning (MIL) is a supervised learning methodology th...

15 Samuel W. Remedios, et al. ∙

∙ 03/11/2019

Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury

Machine learning models are becoming commonplace in the domain of medica...

24 Samuel Remedios, et al. ∙

∙ 11/17/2018

Alternating Segmentation and Simulation for Contrast Adaptive Tissue Classification

A key feature of magnetic resonance (MR) imaging is its ability to manip...

0 Dzung L. Pham, et al. ∙

∙ 07/27/2018

Synthesizing CT from Ultrashort Echo-Time MR Images via Convolutional Neural Networks

With the increasing popularity of PET-MR scanners in clinical applicatio...

0 Snehashis Roy, et al. ∙

∙ 07/27/2018

TBI Contusion Segmentation from MRI using Convolutional Neural Networks

Traumatic brain injury (TBI) is caused by a sudden trauma to the head th...

0 Snehashis Roy, et al. ∙

∙ 04/16/2018

Classifying magnetic resonance image modalities with convolutional neural networks

Magnetic Resonance (MR) imaging allows the acquisition of images with di...

0 Samuel Remedios, et al. ∙

∙ 03/24/2018

Multiple Sclerosis Lesion Segmentation from Brain MRI via Fully Convolutional Neural Networks

Multiple Sclerosis (MS) is an autoimmune disease that leads to lesions i...

0 Snehashis Roy, et al. ∙

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