CDSE-UNet: Enhancing COVID-19 CT Image Segmentation with Canny Edge Detection and Dual-Path SENet Feature Fusion

Accurate segmentation of COVID-19 CT images is crucial for reducing the severity and mortality rates associated with COVID-19 infections. In response to blurred boundaries and high variability characteristic of lesion areas in COVID-19 CT images, we introduce CDSE-UNet: a novel UNet-based segmentati...

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Veröffentlicht in:	arXiv.org 2024-03
Hauptverfasser:	Jiao Ding, Chang, Jie, Han, Renrui, Yang, Li
Format:	Artikel
Sprache:	eng
Schlagworte:	Computed tomography Convolution COVID-19 Edge detection Feature extraction Image enhancement Image segmentation Lesions
Online-Zugang:	Volltext
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