Vishwesh Nath | DeepAI

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∙ 07/31/2023

Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-training

Harnessing the power of pre-training on large-scale datasets like ImageN...

0 Jeya Maria Jose Valanarasu, et al. ∙

∙ 06/05/2023

Robust Fiber ODF Estimation Using Deep Constrained Spherical Deconvolution for Diffusion MRI

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical ima...

0 Tianyuan Yao, et al. ∙

∙ 03/29/2023

A Unified Single-stage Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI

Diffusion-weighted (DW) MRI measures the direction and scale of the loca...

0 Tianyuan Yao, et al. ∙

∙ 03/28/2023

Communication-Efficient Vertical Federated Learning with Limited Overlapping Samples

Federated learning is a popular collaborative learning approach that ena...

0 Jingwei Sun, et al. ∙

∙ 11/04/2022

MONAI: An open-source framework for deep learning in healthcare

Artificial Intelligence (AI) is having a tremendous impact across most a...

6 M. Jorge Cardoso, et al. ∙

∙ 09/13/2022

Warm Start Active Learning with Proxy Labels & Selection via Semi-Supervised Fine-Tuning

Which volume to annotate next is a challenging problem in building medic...

0 Vishwesh Nath, et al. ∙

∙ 03/23/2022

MONAI Label: A framework for AI-assisted Interactive Labeling of 3D Medical Images

The lack of annotated datasets is a major challenge in training new task...

31 Andres Diaz-Pinto, et al. ∙

∙ 01/04/2022

Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images

Semantic segmentation of brain tumors is a fundamental medical image ana...

0 Ali Hatamizadeh, et al. ∙

∙ 11/29/2021

Self-Supervised Pre-Training of Swin Transformers for 3D Medical Image Analysis

Vision Transformers (ViT)s have shown great performance in self-supervis...

0 Yucheng Tang, et al. ∙

∙ 07/12/2021

The Power of Proxy Data and Proxy Networks for Hyper-Parameter Optimization in Medical Image Segmentation

Deep learning models for medical image segmentation are primarily data-d...

0 Vishwesh Nath, et al. ∙

∙ 01/07/2021

Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation

Active learning is a unique abstraction of machine learning techniques w...

25 Vishwesh Nath, et al. ∙

∙ 03/17/2020

The Value of Nullspace Tuning Using Partial Label Information

In semi-supervised learning, information from unlabeled examples is used...

0 Colin B. Hansen, et al. ∙

∙ 02/20/2020

Deep Learning Estimation of Multi-Tissue Constrained Spherical Deconvolution with Limited Single Shell DW-MRI

Diffusion-weighted magnetic resonance imaging (DW-MRI) is the only non-i...

15 Vishwesh Nath, et al. ∙

∙ 11/13/2019

Deep Learning Captures More Accurate Diffusion Fiber Orientations Distributions than Constrained Spherical Deconvolution

Confocal histology provides an opportunity to establish intra-voxel fibe...

0 Vishwesh Nath, et al. ∙

∙ 07/15/2019

Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE

Abstract. Intra-voxel models of the diffusion signal are essential for i...

0 Vishwesh Nath, 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. ∙

∙ 11/10/2018

Coronary Calcium Detection using 3D Attention Identical Dual Deep Network Based on Weakly Supervised Learning

Coronary artery calcium (CAC) is biomarker of advanced subclinical coron...

0 Yuankai Huo, et al. ∙

∙ 10/09/2018

Inter-Scanner Harmonization of High Angular Resolution DW-MRI using Null Space Deep Learning

Diffusion-weighted magnetic resonance imaging (DW-MRI) allows for non-in...

0 Vishwesh Nath, et al. ∙

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