Balancing High-performance and Lightweight: HL-UNet for 3D Cardiac Medical Image Segmentation
H Zhou, B Hu, N Yi, Q Li, D Ergu, F Liu - Academic Radiology, 2024 - Elsevier
Rationale and Objectives Cardiac magnetic resonance imaging is a crucial tool for
analyzing, diagnosing, and formulating treatment plans for cardiovascular diseases …
analyzing, diagnosing, and formulating treatment plans for cardiovascular diseases …
Fairness in AI: are deep learning-based CMR segmentation algorithms biased?
Abstract Background/Introduction Artificial intelligence (AI) is providing opportunities to
transform cardiovascular medicine. A particular challenge in the application of AI technology …
transform cardiovascular medicine. A particular challenge in the application of AI technology …
Overview of the whole heart and heart chamber segmentation methods
Background Preservation and improvement of heart and vessel health is the primary
motivation behind cardiovascular disease (CVD) research. Development of advanced …
motivation behind cardiovascular disease (CVD) research. Development of advanced …
Automatic segmentation of left and right ventricles in cardiac MRI using 3D-ASM and deep learning
H Hu, N Pan, H Liu, L Liu, T Yin, Z Tu… - Signal Processing: Image …, 2021 - Elsevier
Segmentation of the left and right ventricles in cardiac MRI (Magnetic Resonance Imaging)
is a prerequisite step for evaluating global and regional cardiac function. This work presents …
is a prerequisite step for evaluating global and regional cardiac function. This work presents …
3-D consistent and robust segmentation of cardiac images by deep learning with spatial propagation
We propose a method based on deep learning to perform cardiac segmentation on short
axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to …
axis Magnetic resonance imaging stacks iteratively from the top slice (around the base) to …
Left ventricle segmentation in cardiac MR: A systematic mapping of the past decade
MAO Ribeiro, FLS Nunes - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
Left ventricle segmentation in short-axis cardiac magnetic resonance images is important to
diagnose heart disease. However, repetitive manual segmentation of these images requires …
diagnose heart disease. However, repetitive manual segmentation of these images requires …
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI
Current state-of-the-art deep learning segmentation methods have not yet made a broad
entrance into the clinical setting in spite of high demand for such automatic methods. One …
entrance into the clinical setting in spite of high demand for such automatic methods. One …
Deep learning based automatic segmentation of cardiac computed tomography
Background Cardiac Computed Tomography Angiography (CCTA) is routinely performed in
clinical practice to visualize cardiac structures and for quantification of functional parameters …
clinical practice to visualize cardiac structures and for quantification of functional parameters …
A study on heart segmentation using deep learning algorithm for mri scans
Among all body organs heart is a one of the most vital of organs of human body. Dysfunction
of heart function even for a couple of moments can be fatal, therefore, efficient monitoring of …
of heart function even for a couple of moments can be fatal, therefore, efficient monitoring of …
A review of segmentation methods in short axis cardiac MR images
C Petitjean, JN Dacher - Medical image analysis, 2011 - Elsevier
For the last 15 years, Magnetic Resonance Imaging (MRI) has become a reference
examination for cardiac morphology, function and perfusion in humans. Yet, due to the …
examination for cardiac morphology, function and perfusion in humans. Yet, due to the …