ULFAC-Net: Ultra-Lightweight Fully Asymmetric Convolutional Network for Skin Lesion Segmentation

Segmentation of skin lesions is a critical step in the process of skin lesion diagnosis. Such segmentation is challenging due to the irregular shape, fuzzy contours and severe noise interference in the skin lesion region. Existing deep learning-based skin lesion segmentation methods are usually comp...

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Bibliographic Details
Published in:	IEEE journal of biomedical and health informatics Vol. 27; no. 6; pp. 2886 - 2897
Main Authors:	Ma, Yuliang, Wu, Liping, Gao, Yunyuan, Gao, Farong, Zhang, Jianhai, Luo, Zhizeng
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.06.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Asymmetric codec asymmetric convolution Asymmetry Coders Convolution Convolutional codes Datasets Deep learning Encoders-Decoders Feature extraction Floating point arithmetic Lesions Lightweight lightweight segmentation Modules Parameters Picture archiving and communication systems Segmentation Skin Skin diseases skin lesion segmentation Skin lesions Training
ISSN:	2168-2194, 2168-2208, 2168-2208
Online Access:	Get full text
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