Naslov
Segmentation and Quantification of Bi-Ventricles and Myocardium Using 3D SERes-U-Net

Autori
Habijan, Marija ; Galić, Irena ; Leventić, Hrvoje ; Romić, Krešimir ; Babin, Danilo

Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni

Knjiga
Systems, Signals and Image Processing

Urednik/ci
Gregor Rozinaj, Radoslav Vargic

Izdavač
Springer

Grad
Bratislava

Godina
2022

Raspon stranica
3-14

ISSN
1865-0929

Ključne riječi
Cardiac MRI segmentation ; Left ventricle ; Right ventricle ; Myocardium ; Residual learning ; Squeeze and excitation ; 3D SERes- U-Net

Sažetak
Automatic cardiac MRI segmentation, including left and right ventricular endocardium and epicardium, has an essential role in clinical diagnosis by providing crucial information about cardiac function. Determining heart chamber properties, such as volume or ejection fraction, directly relies on their accurate segmentation. In this work, we propose a new automatic method for the segmentation of myocardium, left, and right ventricles from MRI images. We introduce a new architecture that incorporates SERes blocks into 3D U-net architecture (3D SERes-U-Net). The SERes blocks incorporate squeeze-and-excitation operations into residual learning. The adaptive feature recalibration ability of squeeze-and- excitation operations boosts the network's representational power while feature reuse utilizes e ective learning of the features, which improves segmentation performance. We evaluate the proposed method on the testing dataset of the MICCAI Automated Cardiac Diagnosis Challenge (ACDC) dataset and obtain highly comparable results to the state-of-the-art methods.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA