Psoriasis is a chronic inflammatory skin disease that occurs in various forms throughout the body and is associated with certain conditions such as heart disease, diabetes, and depression. The psoriasis area severity index (PASI) score, a tool used to evaluate the severity of psoriasis, is currently used in clinical trials and clinical research. The determination of severity is based on the subjective judgment of the clinician. Thus, the disease evaluation deviations are induced. Therefore, we propose optimal algorithms that can effectively segment the lesion area and classify the severity. In addition, a new dataset on psoriasis was built, including patch images of erythema and scaling. We performed psoriasis lesion segmentation and classified the disease severity. In addition, we evaluated the best-performing segmentation method and classifier and analyzed features that are highly related to the severity of psoriasis. In conclusion, we presented the optimal techniques for evaluating the severity of psoriasis. Our newly constructed dataset improved the generalization performance of psoriasis diagnosis and evaluation. It proposed an optimal system for specific evaluation indicators of the disease and a quantitative PASI scoring method. The proposed system can help to evaluate the severity of localized psoriasis more accurately.
On the cover: The cover image is based on the Research Article Synchrotron radiation-based analysis of fatigue in dental restorative materials by Hyunjong Yoo et al., https://doi.
Until now, studies on nail disease have been performed through microscopic diagnosis and microscopic computed tomography (micro-CT). However, these kinds of conventional methods have some limitations. Firstly, the microscopic method is considered the gold standard for medical diagnosis. However, due to the use of fluorescent materials, the sample is damaged and it takes a long time to get results. Secondly, while micro-CT is a non-invasive method to get inner structure images of the sample with high resolution, the penetration and spatial resolution are insufficient for studying the microstructures of the sample, such as the sponge bone and the muscle fibers. In contrast, synchrotron radiation (SR) X-ray imaging technology has the advantage of very vividly demonstrating the anatomic structure of the sample with high penetration, sensitivity, and resolution. In this study, we compared the optical microscopic method using hematoxylin and eosin (H&E) staining and SR imaging to analyze the nail tissue in a mouse model. The results showed that SR could depict the inner structures of a mouse nail without physical damage. Additionally, we could divide the important anatomical structures nail unit into three parts with three-dimensional images: the nail bed, nail matrix, and hyponychium. The images showed that SR could be used for analyzing nails by visualizing the relatively clear and medically semantic structures in a three-dimensional section. We expect that the results of this study will be applied to study nail diseases and pharmaceutical research on their treatment.
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