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20182024
most citedMONAI: An open-source framework for deep learning in healthcare

452 citations · 605 across the 11 of their papers we have counts for

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5 papers · 1 filter

eess.IV202237 cited

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

Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang +3

Semantic segmentation of brain tumors is a fundamental medical image analysis task involving multiple MRI imaging modalities that can assist clinicians in diagnosing the patient an…

eess.IV2021

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

Vishwesh Nath, Dong Yang, Ali Hatamizadeh +4

Deep learning models for medical image segmentation are primarily data-driven. Models trained with more data lead to improved performance and generalizability. However, training is…

eess.IV2020

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

Vishwesh Nath, Sudhir K. Pathak, Kurt G. Schilling +2

Diffusion-weighted magnetic resonance imaging (DW-MRI) is the only non-invasive approach for estimation of intra-voxel tissue microarchitecture and reconstruction of in vivo neural…

eess.IV20191 cited

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

Vishwesh Nath, Kurt G. Schilling, Colin B. Hansen +10

Confocal histology provides an opportunity to establish intra-voxel fiber orientation distributions that can be used to quantitatively assess the biological relevance of diffusion…

eess.IV2019

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

Vishwesh Nath, Ilwoo Lyu, Kurt G. Schilling +9

Intra-voxel models of the diffusion signal are essential for interpreting organization of the tissue environment at micrometer level with data at millimeter resolution. Recent adva…