Artificial Intelligence-Based Image Classification for Diagnosis of Skin Cancer: Challenges and Opportunities.
Artificial Intelligence-Based Image Classification for Diagnosis of Skin Cancer: Challenges and Opportunities.
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发表时间：
2019-11
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通讯作者：
M. Goyal;T. Knackstedt;Shaofeng Yan;Amanda Oakley;S. Hassanpour
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作者：
M. Goyal;T. Knackstedt;Shaofeng Yan;Amanda Oakley;S. Hassanpour
最近，人们对开发用于诊断皮肤癌的人工智能（AI）计算机辅助诊断解决方案产生了极大的兴趣。随着皮肤癌发病率的增加，越来越多的人对皮肤癌的认识不足，以及缺乏足够的临床专业知识和服务，迫切需要人工智能系统来帮助这一领域的临床医生。大量的皮肤病变数据集是公开的，研究人员已经开发出基于AI的图像分类解决方案，特别是深度学习算法，以区分不同图像模式（如皮肤镜、临床和组织病理学图像）中的恶性皮肤病变和良性病变。尽管人工智能系统在不同皮肤病变的分类方面比皮肤科医生实现了更高的准确性，但这些人工智能系统在帮助临床医生诊断皮肤癌方面仍处于临床应用的早期阶段。在这篇综述中，我们讨论了基于数字图像的皮肤癌诊断AI解决方案的进展，沿着一些挑战和未来的机会，以改善这些AI系统，以支持皮肤科医生，提高他们诊断皮肤癌的能力。
Recently, there has been great interest in developing Artificial Intelligence (AI) enabled computer-aided diagnostics solutions for the diagnosis of skin cancer. With the increasing incidence of skin cancers, low awareness among a growing population, and a lack of adequate clinical expertise and services, there is an immediate need for AI systems to assist clinicians in this domain. A large number of skin lesion datasets are available publicly, and researchers have developed AI-based image classification solutions, particularly deep learning algorithms, to distinguish malignant skin lesions from benign lesions in different image modalities such as dermoscopic, clinical, and histopathology images. Despite the various claims of AI systems achieving higher accuracy than dermatologists in the classification of different skin lesions, these AI systems are still in the very early stages of clinical application in terms of being ready to aid clinicians in the diagnosis of skin cancers. In this review, we discuss advancements in the digital image-based AI solutions for the diagnosis of skin cancer, along with some challenges and future opportunities to improve these AI systems to support dermatologists and enhance their ability to diagnose skin cancer.