title: [The simulation of histopathological diagnosis with the help of an automated image analysis system (VISIAC)].
abstract: Simulation of the diagnostic algorithm in histopathology at 2 different light microscopical magnifications (x4, x40) for separating 7 diagnostic groups in lung pathology (healthy lung, healthy bronchus, lymphocytic inflammation, epidermoid-, adeno-, small cell, and large cell carcinoma) is presented. 140 cases were tested as a teaching set, 105 cases as learning set. Gray value distribution discriminates between healthy parenchyma and the diseases in all cases tested; minimum spanning tree discriminates between inflammation and carcinoma in all cases, and in between the carcinoma with 70% to 80% accuracy. The measurements may be used as additional aid in difficult diagnostic cases.
authors.affiliation: Thoraxklinik Heidelberg-Rohrbach, BRD.
authors.forename: K
authors.initials: K
authors.lastname: Kayser
authors.forename: H
authors.initials: H
authors.lastname: Stute
authors.forename: M
authors.initials: M
authors.lastname: Noetel
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008168:Lung / Q000473:pathology*; D008171:Lung Diseases / Q000175:diagnosis / Q000473:pathology*; D008175:Lung Neoplasms / Q000175:diagnosis / Q000473:pathology*; D011446:Prospective Studies; D012189:Retrospective Studies
vernacular_title: Simulation der histopathologischen Diagnostik mit Hilfe eines automatischen Bildanalysesystems (VISIAC).