Vision transformer introduces a new vitality to the classification of renal pathology

doi:10.1186/s12882-024-03800-x

科研成果详情

题名	Vision transformer introduces a new vitality to the classification of renal pathology
作者	Zhang, Ji2; Lu, Jia Dan 1; Chen, Bo 2; Pan, ShuFang1; Jin, LingWei1; Zheng, Yu 1; Pan, Min1
发表日期	2024-12-01
发表期刊	BMC Nephrology 影响因子和分区
语种	英语
原始文献类型	Article
关键词	Artificial Intelligence Convolutional neural networks Renal pathology Vision transformers Whole-slide imaging
摘要	Recent advancements in computer vision within the field of artificial intelligence (AI) have made significant inroads into the medical domain. However, the application of AI for classifying renal pathology remains challenging due to the subtle variations in multiple renal pathological classifications. Vision Transformers (ViT), an adaptation of the Transformer model for image recognition, have demonstrated superior capabilities in capturing global features and providing greater explainability. In our study, we developed a ViT model using a diverse set of stained renal histopathology images to evaluate its effectiveness in classifying renal pathology. A total of 1861 whole slide images (WSI) stained with HE, MASSON, PAS, and PASM were collected from 635 patients. Renal tissue images were then extracted, tiled, and categorized into 14 classes on the basis of renal pathology. We employed the classic ViT model from the Timm library, utilizing images sized 384 × 384 pixels with 16 × 16 pixel patches, to train the classification model. A comparative analysis was conducted to evaluate the performance of the ViT model against traditional convolutional neural network (CNN) models. The results indicated that the ViT model demonstrated superior recognition ability (accuracy: 0.96–0.99). Furthermore, we visualized the identification process of the ViT models to investigate potentially significant pathological ultrastructures. Our study demonstrated that ViT models outperformed CNN models in accurately classifying renal pathology. Additionally, ViT models are able to focus on specific, significant structures within renal histopathology, which could be crucial for identifying novel and meaningful pathological features in the diagnosis and treatment of renal disease.
资助项目	Medical Health Science and Technology Project of Zhejiang Provincial Health Commission[2020377868];Wenzhou Science & Technology Bureau[Y20210150];
ISSN	1471-2369
卷号	25 期号:1
DOI	10.1186/s12882-024-03800-x
收录类别	SCOPUS ; PUBMED
URL	查看原文
PubMed ID	39385124
SCOPUSEID	2-s2.0-85205982417
通讯作者地址	[Pan, Min]Department of Nephrology,The Second Affiliated Hospital,Yuying Children’s Hospital of Wenzhou Medical University,109 Xueyuan Road, Zhejiang,Wenzhou,China
Scopus学科分类	Nephrology
SCOPUS_ID	SCOPUS_ID:85205982417
引用统计
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/220878
专题	附属第二医院第一临床医学院（信息与工程学院）、附属第一医院附属第一医院附属第二医院_肾内科附属第一医院_肾内科
通讯作者	Pan, Min
作者单位	1.Department of Nephrology,The Second Affiliated Hospital,Yuying Children’s Hospital of Wenzhou Medical University,109 Xueyuan Road, Zhejiang,Wenzhou,China; 2.Department of Nephrology,The First Affiliated Hospital of Wenzhou Medical University,Zhejiang,Wenzhou,China
第一作者单位	附属第一医院; 第一临床医学院（信息与工程学院）、附属第一医院; 肾内科
通讯作者单位	附属第二医院; 肾内科
第一作者的第一单位	附属第一医院
推荐引用方式 GB/T 7714	Zhang, Ji,Lu, Jia Dan,Chen, Bo,et al. Vision transformer introduces a new vitality to the classification of renal pathology[J]. BMC Nephrology,2024,25(1).
APA	Zhang, Ji., Lu, Jia Dan., Chen, Bo., Pan, ShuFang., Jin, LingWei., ... & Pan, Min. (2024). Vision transformer introduces a new vitality to the classification of renal pathology. BMC Nephrology, 25(1).
MLA	Zhang, Ji,et al."Vision transformer introduces a new vitality to the classification of renal pathology".BMC Nephrology 25.1(2024).