黑色素瘤图像分割和边缘细化研究

兰州理工大学学报 ›› 2024, Vol. 50 ›› Issue (4): 77-85.

• 自动化技术与计算机技术 • 上一篇下一篇

黑色素瘤图像分割和边缘细化研究

赵宏^*, 王奡隆, 张陈鹏

兰州理工大学计算机与通信学院, 甘肃兰州 730050

收稿日期:2022-03-05 出版日期:2024-08-28 发布日期:2024-08-30
通讯作者: 赵宏(1971-),男,甘肃西和人,博士,教授,博导.Email:zhaoh@lut.edu.cn
基金资助:
国家自然科学基金(62166025),甘肃省重点研发计划(21YF5GA073)

Research on segmentation and edge refinement of melanoma image

ZHAO Hong, WANG Ao-long, ZHANG Chen-peng

School of Computer and Communication, Lanzhou Univ. of Tech., Lanzhou 730050, China

Received:2022-03-05 Online:2024-08-28 Published:2024-08-30

摘要/Abstract

摘要： 黑色素瘤图像分割在皮肤病的诊断与治疗中具有重要的临床价值.但由于数据集缺乏标注、类别严重不均衡等原因,使得图像分割的精度低,边缘粗糙.因此,提出一种黑色素瘤分割和边缘细化方法,分三个阶段实现.第一阶段,对黑色素瘤数据集进行分类后,使用弱监督方法提取多个层级类激活图并处理;第二阶段,搭建UNet网络模型对黑色素瘤数据集中的恶性样本进行分割;第三阶段,使用第一阶段增强、叠加得到的类激活图边缘对第二阶段的结果进行边缘细化.在ISIC黑色素瘤数据集上的实验结果表明,经过三个阶段的处理,得到的分割图边缘更加细致,平均交并比(mIoU)为86.04％,戴斯相似性系数(Dice)为0.937,杰卡德系数(Jaccard)为0.885.

关键词: 图像分类, 医学图像分割, 弱监督学习, 黑色素瘤, 图像边缘细化

Abstract: Segmentation of melanoma image has important clinical value in the diagnosis and treatment of skin diseases. However, due to the lack of annotation and serious category imbalance of data set, the accuracy of the segmentation map is low and the edge is rough. Therefore, a melanoma segmentation and edge refinement method is proposed, which can be implemented in three stages. In the first stage, after classifying the melanoma data set, multiple hierarchical class activation maps are extracted and processed by weakly supervised method. In the second stage, a UNet model is built to segment malignant samples in melanoma data set. In the third stage, the edge refinement of the results of the second stage is carried out by using the enhanced and overlaid class activation map obtained in the first stage. Experimental results on the ISIC melanoma dataset show that after three stages of processing, the segmentation map has finer edges, with a mean intersection over union value of 86.04%, a Dice similarity coefficient of 0.937, and a Jaccard similarity coefficient of 0.885.

Key words: image classification, medical image segmentation, weakly supervised learning, melanoma, image edge refinement

中图分类号:

TP389.1

赵宏, 王奡隆, 张陈鹏. 黑色素瘤图像分割和边缘细化研究[J]. 兰州理工大学学报, 2024, 50(4): 77-85.

ZHAO Hong, WANG Ao-long, ZHANG Chen-peng. Research on segmentation and edge refinement of melanoma image[J]. Journal of Lanzhou University of Technology, 2024, 50(4): 77-85.

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黑色素瘤图像分割和边缘细化研究

Research on segmentation and edge refinement of melanoma image

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