Your browser doesn't support javascript.
loading
CRCS: An automatic image processing pipeline for hormone level analysis of Cushing's disease.
Li, Haiyue; Xie, Jing; Song, Jialin; Jin, Cheng; Xin, Hongyi; Pan, Xiaoyong; Ke, Jing; Yuan, Ye; Shen, Hongbin; Ning, Guang.
Afiliação
  • Li H; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
  • Xie J; Department of Pathology, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, 197 Ruijin 2nd Road, Shanghai 200025, China.
  • Song J; The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiao Tong University, Xi'an 710049, China.
  • Jin C; Medical Robot Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Xin H; University of Michigan - Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University, Shanghai 200240, China.
  • Pan X; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
  • Ke J; Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Yuan Y; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China.
  • Shen H; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China. Electronic address: hbshen@sjtu.edu.cn.
  • Ning G; State Key Laboratory of Medical Genomes, National Clinical Research Center for Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Laboratory of Endocrinology and Metabolism, Institute of Health Sciences, Shanghai Institutes for Biolo
Methods ; 222: 28-40, 2024 Feb.
Article em En | MEDLINE | ID: mdl-38159688
ABSTRACT
Due to the abnormal secretion of adreno-cortico-tropic-hormone (ACTH) by tumors, Cushing's disease leads to hypercortisonemia, a precursor to a series of metabolic disorders and serious complications. Cushing's disease has high recurrence rate, short recurrence time and undiscovered recurrence reason after surgical resection. Qualitative or quantitative automatic image analysis of histology images can potentially in providing insights into Cushing's disease, but still no software has been available to the best of our knowledge. In this study, we propose a quantitative image analysis-based pipeline CRCS, which aims to explore the relationship between the expression level of ACTH in normal cell tissues adjacent to tumor cells and the postoperative prognosis of patients. CRCS mainly consists of image-level clustering, cluster-level multi-modal image registration, patch-level image classification and pixel-level image segmentation on the whole slide imaging (WSI). On both image registration and classification tasks, our method CRCS achieves state-of-the-art performance compared to recently published methods on our collected benchmark dataset. In addition, CRCS achieves an accuracy of 0.83 for postoperative prognosis of 12 cases. CRCS demonstrates great potential for instrumenting automatic diagnosis and treatment for Cushing's disease.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Hipersecreção Hipofisária de ACTH Limite: Humans Idioma: En Revista: Methods Assunto da revista: BIOQUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Hipersecreção Hipofisária de ACTH Limite: Humans Idioma: En Revista: Methods Assunto da revista: BIOQUIMICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China