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20172022
most citedCoronary Artery Plaque Characterization from CCTA Scans using Deep Learning and Radiomics

21 citations · 96 across the 19 of their papers we have counts for

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Showing eess.IVShow all

8 papers · 1 filter

eess.IV20211 cited

Style Curriculum Learning for Robust Medical Image Segmentation

Zhendong Liu, Van Manh, Xin Yang +6

The performance of deep segmentation models often degrades due to distribution shifts in image intensities between the training and test data sets. This is particularly pronounced…

eess.IV20211 cited

A Deep Discontinuity-Preserving Image Registration Network

Xiang Chen, Nishant Ravikumar, Yan Xia +1

Image registration aims to establish spatial correspondence across pairs, or groups of images, and is a cornerstone of medical image computing and computer-assisted-interventions.…

eess.IV20211 cited

CAR-Net: Unsupervised Co-Attention Guided Registration Network for Joint Registration and Structure Learning

Xiang Chen, Yan Xia, Nishant Ravikumar +1

Image registration is a fundamental building block for various applications in medical image analysis. To better explore the correlation between the fixed and moving images and imp…

eess.IV202017 cited

Spatio-temporal Multi-task Learning for Cardiac MRI Left Ventricle Quantification

Sulaiman Vesal, Mingxuan Gu, Andreas Maier +1

Quantitative assessment of cardiac left ventricle (LV) morphology is essential to assess cardiac function and improve the diagnosis of different cardiovascular diseases. In current…

eess.IV2020

COPD Classification in CT Images Using a 3D Convolutional Neural Network

Jalil Ahmed, Sulaiman Vesal, Felix Durlak +4

Chronic obstructive pulmonary disease (COPD) is a lung disease that is not fully reversible and one of the leading causes of morbidity and mortality in the world. Early detection a…

eess.IV2019

Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach

Siming Bayer, Xia Zhong, Weilin Fu +2

Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions…