Three-Dimensional Skin CT Based on Intelligent Algorithm in the Analysis of Skin Lesion Sites Features in Children with Psoriasis.

Lina Wang,Youning Zheng,Wenfang Liu,Ran Zhou,Osamah Ibrahim Khalaf

doi:10.1155/2022/8195243

Abstract

This research was to explore the application value of three-dimensional computed tomography (CT) based on artificial intelligent algorithm in analyzing the characteristics of skin lesions in children with psoriasis. In this study, 15 children with psoriasis were selected as the observation group, and 15 children with other skin diseases were selected as the control group. The CT images were optimized, and the feature selection was carried out based on artificial intelligent algorithm. Firstly, the results were compared with the results of simple skin three-dimensional CT to determine the effectiveness. Then, the two groups of three-dimensional skin CT image features of skin psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium based on intelligent algorithms were compared. After comparison, the detection rate of psoriasis-like hyperplasia, Munro microabscess, dermal papillary vascular dilation, and squamous epithelium in the observation group was higher than that in the control group, with significant difference and statistical significance (P < 0.05). In addition, the sensitivity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 80.0%, 86.7%, 80.0%, and 93.3%, respectively. The specificity of psoriasis-like hyperplasia, Munro microabscess, dermal papilla vascular dilatation, and squamous epithelium in children with psoriasis was 86.7%, 93.3%, 60.0%, and 73.3%, respectively. The results showed that Munro microabscess and psoriasis-like hyperplasia had high sensitivity and specificity in all diagnostic items, which could be used as important features of skin lesion sites in the diagnosis of psoriasis in children. The research provides a basis for the clinical diagnosis of psoriasis in children, which is worthy of clinical promotion.

Highlights

Psoriasis is characterized by a layer of exfoliated silverwhite scales on the skin erythema, which is called “Bai Bi” in traditional Chinese medicine
In order to improve the accuracy and efficiency of clinical diagnosis of pediatric psoriasis, three-dimensional skin computed tomography (CT) based on artificial intelligent algorithm was innovatively applied to analyze the characteristics of skin lesions sites in children
15 children with psoriasis were selected as the observation object, and the characteristics of skin threedimensional CT images based on artificial intelligence were analyzed and compared

Summary

Introduction

Psoriasis is characterized by a layer of exfoliated silverwhite scales on the skin erythema, which is called “Bai Bi” in traditional Chinese medicine. The combination of artificial intelligent algorithm and feature analysis of CT images can effectively improve the deep learning of diagnostic features, so as to quickly and accurately annotate the feature tissue parts in a large number of images. The combination of 2-3-dimensional hybrid convolutional neural network-based automatic segmentation algorithm and CT image will have a good application prospect in the feature analysis of psoriasis lesions sites [19, 20]. In order to improve the accuracy and efficiency of clinical diagnosis of pediatric psoriasis, three-dimensional skin CT based on artificial intelligent algorithm was innovatively applied to analyze the characteristics of skin lesions sites in children. By comparing the diagnostic information of the two groups, the diagnostic function of CT image feature analysis in psoriasis skin lesions sites was judged. A diagnostic method is urgently needed to assist treatment [9,10,11]

Research Objects and Methods

Results

Discussion

Conclusion