MSR U-Net: An Improved U-Net Model for Retinal Blood Vessel Segmentation

For the proper diagnosis and treatment of a variety of retinal conditions, retinal blood vessel segmentation is crucial. Delineation of vessels with varying thicknesses is critical for detecting disease symptoms. However, this task is challenging due to inadequate contextual information, complex ves...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access 2024, Vol.12, p.534-551
Hauptverfasser:	Kande, Giri Babu, Ravi, Logesh, Kande, Nitya, Nalluri, Madhusudana Rao, Kotb, Hossam, AboRas, Kareem M., Yousef, Amr, Ghadi, Yazeed Yasin, Sasikumar, A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Biomedical imaging Blood vessels Convolution Convolutional neural networks Feature extraction fundus Image segmentation Lesions Medical imaging Morphology Retina segmentation Signs and symptoms Thickness U-Net
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!