Search Results for author: Shreyas Fadnavis

Found 7 papers, 3 papers with code

EVC-Net: Multi-scale V-Net with Conditional Random Fields for Brain Extraction

1 code implementation6 Jun 2022 Jong Sung Park, Shreyas Fadnavis, Eleftherios Garyfallidis

While previous methods have used machine learning with structural/geometric priors, with the development of deep learning in computer vision tasks, there has been an increase in proposed convolutional neural network architectures for this semantic segmentation task.

Image Segmentation Semantic Segmentation

NUQ: A Noise Metric for Diffusion MRI via Uncertainty Discrepancy Quantification

no code implementations3 Mar 2022 Shreyas Fadnavis, Jens Sjölund, Anders Eklund, Eleftherios Garyfallidis

However, it is hard to estimate the impact of noise on downstream tasks based only on such qualitative assessments.

Denoising

ThetA -- fast and robust clustering via a distance parameter

no code implementations13 Feb 2021 Eleftherios Garyfallidis, Shreyas Fadnavis, Jong Sung Park, Bramsh Qamar Chandio, Javier Guaje, Serge Koudoro, Nasim Anousheh

Clustering is a fundamental problem in machine learning where distance-based approaches have dominated the field for many decades.

Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning​

1 code implementation NeurIPS 2020 Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis

Diffusion-weighted magnetic resonance imaging (DWI) is the only non-invasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain.

Denoising Self-Supervised Learning

Patch2Self: Denoising Diffusion MRI with Self-Supervised Learning

1 code implementation2 Nov 2020 Shreyas Fadnavis, Joshua Batson, Eleftherios Garyfallidis

Diffusion-weighted magnetic resonance imaging (DWI) is the only noninvasive method for quantifying microstructure and reconstructing white-matter pathways in the living human brain.

Denoising Medical Diagnosis +1

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