Mohammed Ridha Ali, Isa Nor Ashidi Mat, Tawfik Ayman
Department of Electrical and Computer Engineering, Ajman University, Ajman P.O. Box 346, United Arab Emirates.
School of Electrical & Electronic Engineering, Engineering Campus, Universiti Sains Malaysia, Penang 14300, Malaysia.
J Imaging. 2024 Jul 23;10(8):174. doi: 10.3390/jimaging10080174.
Acne Vulgaris is a common type of skin disease that affects more than 85% of teenagers and frequently continues even in adulthood. While it is not a dangerous skin disease, it can significantly impact the quality of life. Hyperspectral imaging (HSI), which captures a wide spectrum of light, has emerged as a tool for the detection and diagnosis of various skin conditions. However, due to the high cost of specialised HS cameras, it is limited in its use in clinical settings. In this research, a novel acne detection system that will utilise reconstructed hyperspectral (HS) images from RGB images is proposed. A dataset of reconstructed HS images is created using the best-performing HS reconstruction model from our previous research. A new acne detection algorithm that is based on reconstructed HS images and RetinaNet algorithm is introduced. The results indicate that the proposed algorithm surpasses other techniques based on RGB images. Additionally, reconstructed HS images offer a promising and cost-effective alternative to using expensive HSI equipment for detecting conditions like acne or other medical issues.
寻常痤疮是一种常见的皮肤病，超过85%的青少年受其影响，且常常持续至成年期。虽然它并非危险的皮肤病，但会对生活质量产生重大影响。能捕捉广谱光线的高光谱成像（HSI）已成为检测和诊断各种皮肤状况的一种工具。然而，由于专用高光谱相机成本高昂，其在临床环境中的应用受到限制。在本研究中，提出了一种新型痤疮检测系统，该系统将利用从RGB图像重建的高光谱（HS）图像。使用我们之前研究中表现最佳的高光谱重建模型创建了一个重建高光谱图像数据集。引入了一种基于重建高光谱图像和RetinaNet算法的新痤疮检测算法。结果表明，所提出的算法优于其他基于RGB图像的技术。此外，对于检测痤疮或其他医疗问题等情况，重建高光谱图像为使用昂贵的高光谱成像设备提供了一种有前景且经济高效的替代方案。
