Melanoma image segmentation method based on edge key points and edge attention
10.3969/j.issn.1005-202X.2024.10.006
- VernacularTitle:基于边缘关键点和边缘注意力的黑色素瘤图像分割方法
- Author:
Na WANG
1
;
Wei JIA
;
Xuefen ZHAO
;
Hongjuan GAO
Author Information
1. 宁夏大学信息工程学院,宁夏 银川 750021
- Keywords:
melanoma;
image segmentation;
multi-scale;
edge attention;
edge key point selection
- From:
Chinese Journal of Medical Physics
2024;41(10):1225-1236
- CountryChina
- Language:Chinese
-
Abstract:
High-precision segmentation of melanoma images is crucial for early diagnosis and improving patient survival.However,the blurring of the edge region of melanoma,which presents irregular shapes,makes it difficult for existing segmentation methods to obtain edge feature information,affecting the accuracy of melanoma image segmentation.To solve this problem,a melanoma image segmentation method based on edge key points and edge attention is proposed.An edge key point selection module for point rendering and a combined convolution transformer block are designed in the encoder to guide the acquisition of local and global features of the edge by selecting edge key points.Then,the edge refinement module is designed in the encoder to refine the edge features of the deep network,and finally,the multi-scale edge attention module is designed in the skip connection,which enables the capture of the edge shape features at multiple scales.The tests on two datasets(ISIC 2018 and PH2)demonstrate that the proposed method has better segmentation performance than the existing segmentation methods.
