Classification Method for Kashin-Beck Disease Based on Multi-view Medical Imaging
LIU Ziyi
LI Meng
SONG Yuhang
Abstract：Kaschin-Beck Disease(KBD)is a chronic localized bone and joint disorder that primarily affects children and young adults,leading to joint deformities,stiffness,and pain.However,due to a shortage of specialized physicians and medical equipment,patients often face delays in diagnosis.Furthermore,the lack of datasets related to KBD has resulted in limited research in this area.To address these issues,a classification method for KBD is proposed based on multi-view medical imaging.First,this paper constructs a dataset for KBD and preprocesses the original data,removing backgrounds,ensuring uniform sizing,and stan-dardizing brightness and contrast distributions.Next,this paper introduces an innovative multi-view medical imaging fusion module that uses a progressive fusion strategy to effectively combine complementary and common features from multi-view images.Finally,the fused features are put into a classification network to obtain the ultimate diagnostic results.Experimental results show that the proposed algorithm achieves fast convergence and high diagnostic accuracy.
Keywords：kaschin-beck diseasedeep learningdeep neural networkimage processing
Publication Date：2025-09-20
Online Publishing Date：2025-12-23(First online date of this platform, not the publication date of the document)
Pages：5( 46-50 )