SM-SegNet: A Lightweight Squeeze M-SegNet for Tissue Segmentation in Brain MRI Scans

In this paper, we propose a novel squeeze M-SegNet (SM-SegNet) architecture featuring a fire module to perform accurate as well as fast segmentation of the brain on magnetic resonance imaging (MRI) scans. The proposed model utilizes uniform input patches, combined-connections, long skip connections,...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Nagaraj Yamanakkanavar, Jae Young Choi, Bumshik Lee
Aineistotyyppi: Artikkeli
Kieli:English
Julkaistu: MDPI AG 2022-07-01
Sarja:Sensors
Aiheet:
Linkit:https://www.mdpi.com/1424-8220/22/14/5148