Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:3074-3077. doi: 10.1109/EMBC46164.2021.9631047.
Melanoma is considered as one of the world's deadly cancers. This type of skin cancer will spread to other areas of the body if not detected at an early stage. Convolutional Neural Network (CNN) based classifiers are currently considered one of the most effective melanoma detection techniques. This study presents the use of recent deep CNN approaches to detect melanoma skin cancer and investigate suspicious lesions. Tests were conducted using a set of more than 36,000 images extracted from multiple datasets. The obtained results show that the best performing deep learning approach achieves high scores with an accuracy and Area Under Curve (AUC) above 99%.
黑色素瘤被认为是世界上最致命的癌症之一。如果在早期阶段没有发现，这种皮肤癌会扩散到身体的其他部位。基于卷积神经网络（CNN）的分类器目前被认为是最有效的黑色素瘤检测技术之一。本研究提出了利用最新的深度 CNN 方法来检测黑色素瘤皮肤癌并研究可疑病变。测试是使用从多个数据集提取的超过 36000 张图像的集合进行的。获得的结果表明，表现最佳的深度学习方法的准确率和 AUC 均高于 99%，达到了很高的分数。
