Visual representations of the semantic segmentation of drone images from Database-3 obtained using different state-of-the-art networks.

Source publication

Fig. 1. Workflow of the proposed scheme for segmenting lung lesions of...

Fig. 2. Schematic representation of the two-stage implementation of the...

Fig. 3. Schematic representations of the proposed encoder and decoder...

Fig. 5. Schematic representations of the down transition unit...

Fig. 6. Schematic representation of the proposed Multi-Scale Fusion...

CovSegNet: A Multi Encoder-Decoder Architecture for Improved Lesion Segmentation of COVID-19 Chest CT Scans

Preprint

Full-text available

Dec 2020

Tanvir Mahmud
Md Awsafur Rahman
Shaikh Anowarul Fattah
Sun-Yuan Kung

Automatic lung lesions segmentation of chest CT scans is considered a pivotal stage towards accurate diagnosis and severity measurement of COVID-19. Traditional U-shaped encoder-decoder architecture and its variants suffer from diminutions of contextual information in pooling/upsampling operations with increased semantic gaps among encoded and deco...