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20222025
most citedRadiology Report Generation Using Transformers Conditioned with Non-imaging Data

13 citations · 18 across the 20 of their papers we have counts for

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cs.CV20241 cited

GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation

Fengming Lin, Yan Xia, Michael MacRaild +6

The automated segmentation of cerebral aneurysms is pivotal for accurate diagnosis and treatment planning. Confronted with significant domain shifts and class imbalance in 3D Rotat…

cs.CV2024

Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning

Fengming Lin, Yan Xia, Michael MacRaild +6

Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models. Since cros…

cs.CV202313 cited

Radiology Report Generation Using Transformers Conditioned with Non-imaging Data

Nurbanu Aksoy, Nishant Ravikumar, Alejandro F Frangi

Medical image interpretation is central to most clinical applications such as disease diagnosis, treatment planning, and prognostication. In clinical practice, radiologists examine…

cs.CV2023

Beyond Images: An Integrative Multi-modal Approach to Chest X-Ray Report Generation

Nurbanu Aksoy, Serge Sharoff, Selcuk Baser +2

Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images. Most existing methods focus solely on the im…

cs.CV2023

Learning disentangled representations for explainable chest X-ray classification using Dirichlet VAEs

Rachael Harkness, Alejandro F Frangi, Kieran Zucker +1

This study explores the use of the Dirichlet Variational Autoencoder (DirVAE) for learning disentangled latent representations of chest X-ray (CXR) images. Our working hypothesis i…

cs.CV2022

Agent with Tangent-based Formulation and Anatomical Perception for Standard Plane Localization in 3D Ultrasound

Yuxin Zou, Haoran Dou, Yuhao Huang +9

Standard plane (SP) localization is essential in routine clinical ultrasound (US) diagnosis. Compared to 2D US, 3D US can acquire multiple view planes in one scan and provide compl…