Cargando…
Automatic Left Ventricle Segmentation from Short-Axis Cardiac MRI Images Based on Fully Convolutional Neural Network
Background: Left ventricle (LV) segmentation using a cardiac magnetic resonance imaging (MRI) dataset is critical for evaluating global and regional cardiac functions and diagnosing cardiovascular diseases. LV clinical metrics such as LV volume, LV mass and ejection fraction (EF) are frequently extr...
Autores principales: | Shaaf, Zakarya Farea, Jamil, Muhammad Mahadi Abdul, Ambar, Radzi, Alattab, Ahmed Abdu, Yahya, Anwar Ali, Asiri, Yousef |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8871002/ https://www.ncbi.nlm.nih.gov/pubmed/35204504 http://dx.doi.org/10.3390/diagnostics12020414 |
Ejemplares similares
-
A Combined Fully Convolutional Networks and Deformable Model for Automatic Left Ventricle Segmentation Based on 3D Echocardiography
por: Dong, Suyu, et al.
Publicado: (2018) -
Fully automatic wound segmentation with deep convolutional neural networks
por: Wang, Chuanbo, et al.
Publicado: (2020) -
Fully Automatic Left Ventricle Segmentation Using Bilateral Lightweight Deep Neural Network
por: Shoaib, Muhammad Ali, et al.
Publicado: (2023) -
Fully automatic segmentation of short and long axis cine cardiac MR
por: Fradkin, Maxim, et al.
Publicado: (2009) -
Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks
por: Chen, Liang, et al.
Publicado: (2017)