Title
NCRNet: Neighborhood Context Refinement Network for skin lesion segmentation
Abstract
Accurate skin lesion segmentation plays a fundamental role in computer-aided melanoma analysis. Recently, some FCN-based methods have been proposed and achieved promising results in lesion segmentation tasks. However, due to the variable shapes, different scales, noise interference, and ambiguous boundaries of skin lesions, the capabilities of lesion location and boundary delineation of these works are still insufficient. To overcome the above challenges, in this paper, we propose a novel Neighborhood Context Refinement Network (NCRNet) by using the coarse-to-fine strategy to achieve accurate skin lesion segmentation. The proposed NCRNet contains a shared encoder and two different but closely related decoders for locating the skin lesions and refining the lesion boundaries. Specifically, we first design the Parallel Attention Decoder (PAD), which can effectively extract and fuse the local detail information and global semantic information on multiple levels to locate skin lesions of different sizes and shapes. Then, based on the initial lesion location, we further design the Neighborhood Context Refinement Decoder (NCRD), aiming at leveraging the fine-grained multi-stage neighborhood context cues to refine the lesion boundaries continuously. Furthermore, the neighborhood-based deep supervision used in the NCRD can make the shared encoder pay more attention to the lesion boundary areas and promote convergence of the segmentation network. The public skin lesion segmentation dataset ISIC2017 is adopted to validate the effectiveness of the proposed NCRNet. Comprehensive experiments prove that the proposed NCRNet reaches the state-of-the-art performance than the other nine competitive methods and gets 78.62%, 86.55%, and 94.01% on Jaccard, Dice, and Accuracy, respectively.
Year
DOI
Venue
2022
10.1016/j.compbiomed.2022.105545
Computers in Biology and Medicine
Keywords
DocType
Volume
Skin lesion segmentation,Coarse-to-fine,Parallel attention decoder,Neighborhood context refinement decoder
Journal
146
ISSN
Citations 
PageRank 
0010-4825
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Liu Qi11027106.48
Jingkun Wang200.34
Mengying Zuo300.34
Weiwei Cao400.34
Jian Zheng5233.19
Hui Zhao6169.22
Jing Xie700.34