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20162026
most citedDeep learning for cardiac image segmentation: A review

870 citations · 1.2k across the 29 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

eess.IV2019★ 870 cited

Deep learning for cardiac image segmentation: A review

Chen Chen, Chen Qin, Huaqi Qiu +4

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation pap…

eess.IV2019★ 65 cited

Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation

Chen Chen, Cheng Ouyang, Giacomo Tarroni +4

In this work, we present a fully automatic method to segment cardiac structures from late-gadolinium enhanced (LGE) images without using labelled LGE data for training, but instead…

cs.CV2019★ 30 cited

Self-Supervised Learning for Cardiac MR Image Segmentation by Anatomical Position Prediction

Wenjia Bai, Chen Chen, Giacomo Tarroni +6

In the recent years, convolutional neural networks have transformed the field of medical image analysis due to their capacity to learn discriminative image features for a variety o…

eess.IV2019★ 47 cited

Learning Shape Priors for Robust Cardiac MR Segmentation from Multi-view Images

Chen Chen, Carlo Biffi, Giacomo Tarroni +3

Cardiac MR image segmentation is essential for the morphological and functional analysis of the heart. Inspired by how experienced clinicians assess the cardiac morphology and func…

eess.IV2019★ 1 cited

Explainable Anatomical Shape Analysis through Deep Hierarchical Generative Models

Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni +12

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of p…

cs.CV2019

3D High-Resolution Cardiac Segmentation Reconstruction from 2D Views using Conditional Variational Autoencoders

Carlo Biffi, Juan J. Cerrolaza, Giacomo Tarroni +4

Accurate segmentation of heart structures imaged by cardiac MR is key for the quantitative analysis of pathology. High-resolution 3D MR sequences enable whole-heart structural imag…