title: Automated analysis of confocal laser endomicroscopy images to detect head and neck cancer.
abstract: The purpose of this study was to develop an automated image analysis algorithm to discriminate between head and neck cancer and nonneoplastic epithelium in confocal laser endomicroscopy (CLE) images.
  
  
  
  CLE was applied to image head and neck cancer epithelium in vivo. Histopathologic diagnosis from biopsies was used to classify the CLE images offline as cancer or noncancer tissue. The classified images were used to train automated software based on distance map histograms. The performance of the final algorithm was confirmed by "leave 2 patients out" cross-validation and area under the curve (AUC)/receiver operating characteristic (ROC) analysis.
  
  
  
  Ninety-two CLE videos and 92 biopsies were analyzed from 12 patients. One hundred two frames of classified neoplastic tissue and 52 frames of nonneoplastic tissue were used for cross-validation of the developed algorithm. AUC varied from 0.52 to 0.92.
  
  
  
  The proposed software allows an objective classification of CLE images of head and neck cancer and adjacent nonneoplastic epithelium. © 2015 Wiley Periodicals, Inc. Head Neck 38: E1419-E1426, 2016.
authors.affiliation: Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.|Department of Otorhinolaryngology, Head and Neck Surgery, University of Erlangen-Nuremberg, Erlangen, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Dittberner
authors.affiliation: Department of Computer Science, Friedrich Schiller University, Jena, Germany.
authors.forename: Erik
authors.initials: E
authors.lastname: Rodner
authors.affiliation: Department of Computer Science, Friedrich Schiller University, Jena, Germany.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Ortmann
authors.affiliation: Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.|Department of Otorhinolaryngology, Heinrich-Braun-Klinikum, Zwickau, Germany.
authors.forename: Joachim
authors.initials: J
authors.lastname: Stadler
authors.affiliation: Division of Gastroenterology, Hepatology and Infectious Diseases, Department of Internal Medicine IV, Jena University Hospital, Jena, Germany.
authors.forename: Carsten
authors.initials: C
authors.lastname: Schmidt
authors.affiliation: Institute of Pathology, Jena University Hospital, Jena, Germany.
authors.forename: Iver
authors.initials: I
authors.lastname: Petersen
authors.affiliation: Division of Gastroenterology, Hepatology and Infectious Diseases, Department of Internal Medicine IV, Jena University Hospital, Jena, Germany.
authors.forename: Andreas
authors.initials: A
authors.lastname: Stallmach
authors.affiliation: Department of Computer Science, Friedrich Schiller University, Jena, Germany.
authors.forename: Joachim
authors.initials: J
authors.lastname: Denzler
authors.affiliation: Department of Otorhinolaryngology, Jena University Hospital, Jena, Germany.
authors.forename: Orlando
authors.initials: O
authors.lastname: Guntinas-Lichius
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D019540:Area Under Curve; D001706:Biopsy; D004724:Endoscopy; D005260:Female; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D000069550:Machine Learning; D008297:Male; D018613:Microscopy, Confocal; D008875:Middle Aged; D011446:Prospective Studies; D012372:ROC Curve; D012984:Software
keywords: confocal microscopy; diagnostics; head and neck cancer; image analysis; segmentation