17 citations · 27 across the 8 of their papers we have counts for
8 papers
Stroke Lesion Segmentation using Multi-Stage Cross-Scale Attention
Liang Shang, William A. Sethares, Anusha Adluru +4
Precise characterization of stroke lesions from MRI data has immense value in prognosticating clinical and cognitive outcomes following a stroke. Manual stroke lesion segmentation…
MICCAI-CDMRI 2023 QuantConn Challenge Findings on Achieving Robust Quantitative Connectivity through Harmonized Preprocessing of Diffusion MRI
Nancy R. Newlin, Kurt Schilling, Serge Koudoro +33
White matter alterations are increasingly implicated in neurological diseases and their progression. International-scale studies use diffusion-weighted magnetic resonance imaging (…
Segmenting Small Stroke Lesions with Novel Labeling Strategies
Liang Shang, Zhengyang Lou, Andrew L. Alexander +4
Deep neural networks have demonstrated exceptional efficacy in stroke lesion segmentation. However, the delineation of small lesions, critical for stroke diagnosis, remains a chall…
Vision Backbone Enhancement via Multi-Stage Cross-Scale Attention
Liang Shang, Yanli Liu, Zhengyang Lou +4
Convolutional neural networks (CNNs) and vision transformers (ViTs) have achieved remarkable success in various vision tasks. However, many architectures do not consider interactio…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Accurate Automatic Segmentation of Amygdala Subnuclei and Modeling of Uncertainty via Bayesian Fully Convolutional Neural Network
Yilin Liu, Gengyan Zhao, Brendon M. Nacewicz +5
Recent advances in deep learning have improved the segmentation accuracy of subcortical brain structures, which would be useful in neuroimaging studies of many neurological disorde…
Evaluating consistency of deterministic streamline tractography in non-linearly warped DTI data
Nagesh Adluru, Daniel J. Destiche, Do P. M. Tromp +3
Tractography is typically performed for each subject using the diffusion tensor imaging (DTI) data in its native subject space rather than in some space common to the entire study…
Kernel Regression on Manifolds and Its Application to Modeling Disconnected Anatomic Structures
Moo K. Chung, Nagesh Adluru, Houri K. Vorperian
We present a unified statistical approach to modeling disconnected 3D anatomical structures extracted from medical images. Due to image acquisition and preprocessing noises, it is…