1 citations · 2 across the 10 of their papers we have counts for
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Learning To Focus: Anatomy-Guided Attention Regularization for Medical Image Classification
Tonmoy Hossain, Atiqur Rahman, Farhana Hossain Swarnali +1
Medical image classification models are ideally expected to identify diagnostically relevant regions while making predictions, yet standard classification losses rarely provide spa…
Learning to Unify Deformable Shape and Texture Representations for Cardiac Video Classification
Tonmoy Hossain, Miaomiao Zhang
Deformable shape representations have proven to be robust complements to texture features in cardiac image classification, offering geometric priors that are invariant to imaging a…
Learning Group Actions In Disentangled Latent Image Representations
Farhana Hossain Swarnali, Miaomiao Zhang, Tonmoy Hossain
Modeling group actions on latent representations enables controllable transformations of high-dimensional image data. Prior works applying group-theoretic priors or modeling transf…
CoRLD: Contrastive Representation Learning Of Deformable Shapes In Images
Tonmoy Hossain, Miaomiao Zhang
Deformable shape representations, parameterized by deformations relative to a given template, have proven effective for improved image analysis tasks. However, their broader applic…
TPIE: Topology-Preserved Image Editing With Text Instructions
Nivetha Jayakumar, Srivardhan Reddy Gadila, Tonmoy Hossain +2
Preserving topological structures is important in real-world applications, particularly in sensitive domains such as healthcare and medicine, where the correctness of human anatomy…
Invariant Shape Representation Learning For Image Classification
Tonmoy Hossain, Jing Ma, Jundong Li +1
Geometric shape features have been widely used as strong predictors for image classification. Nevertheless, most existing classifiers such as deep neural networks (DNNs) directly l…
TLRN: Temporal Latent Residual Networks For Large Deformation Image Registration
Nian Wu, Jiarui Xing, Miaomiao Zhang
This paper presents a novel approach, termed {\em Temporal Latent Residual Network (TLRN)}, to predict a sequence of deformation fields in time-series image registration. The chall…
LaMoD: Latent Motion Diffusion Model For Myocardial Strain Generation
Jiarui Xing, Nivetha Jayakumar, Nian Wu +3
Motion and deformation analysis of cardiac magnetic resonance (CMR) imaging videos is crucial for assessing myocardial strain of patients with abnormal heart functions. Recent adva…
Multimodal Learning To Improve Cardiac Late Mechanical Activation Detection From Cine MR Images
Jiarui Xing, Nian Wu, Kenneth Bilchick +2
This paper presents a multimodal deep learning framework that utilizes advanced image techniques to improve the performance of clinical analysis heavily dependent on routinely acqu…
MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations
Tonmoy Hossain, Miaomiao Zhang
Geometric transformations have been widely used to augment the size of training images. Existing methods often assume a unimodal distribution of the underlying transformations betw…
SADIR: Shape-Aware Diffusion Models for 3D Image Reconstruction
Nivetha Jayakumar, Tonmoy Hossain, Miaomiao Zhang
3D image reconstruction from a limited number of 2D images has been a long-standing challenge in computer vision and image analysis. While deep learning-based approaches have achie…