title: Automated labeling of cancer textures in larynx histopathology slides using quasi-supervised learning.
abstract: OBJECTIVE
  To evaluate the performance of a quasi-supervised statistical learning algorithm, operating on datasets having normal and neoplastic tissues, to identify larynx squamous cell carcinomas. Furthermore, cancer texture separability measures against normal tissues are to be developed and compared either for colorectal or larynx tissues.
  
  
  METHODS
  Light microscopic digital images from histopathological sections were obtained from laryngectomy materials including squamous cell carcinoma and nonneoplastic regions. The texture features were calculated by using co-occurrence matrices and local histograms. The texture features were input to the quasi-supervised learning algorithm.
  
  
  RESULTS
  Larynx regions containing squamous cell carcinomas were accurately identified, having false and true positive rates up to 21% and 87%, respectively.
  
  
  CONCLUSIONS
  Larynx squamous cell carcinoma versus normal tissue texture separability measures were higher than colorectal adenocarcinoma versus normal textures for the colorectal database. Furthermore, the resultant labeling performances for all larynx datasets are higher than or equal to that of colorectal datasets. The results in larynx datasets, in comparison with the former colorectal study, suggested that quasi-supervised texture classification is to be a helpful method in histopathological image classification and analysis.
authors: Devrim
authors: D
authors: Onder
authors: Sulen
authors: S
authors: Sarioglu
authors: Bilge
authors: B
authors: Karacali
mesh_terms: D000465:Algorithms; D002294:Carcinoma, Squamous Cell / Q000473:pathology; D015179:Colorectal Neoplasms / Q000473:pathology; D006258:Head and Neck Neoplasms / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007822:Laryngeal Neoplasms / Q000473:pathology; D007830:Larynx / Q000166:cytology; D010363:Pattern Recognition, Automated; D000077195:Squamous Cell Carcinoma of Head and Neck