Mo1432 Smart Atlas for Supporting the Interpretation of Needle-Based Confocal LASER Endomicroscopy (nCLE) of Pancreatic Cysts: First Classification Results of a Computer-Aided Diagnosis Software Based on Image Recognition

2014 ◽  
Vol 79 (5) ◽  
pp. AB435 ◽  
Author(s):  
Marzieh Kohandani Tafreshi ◽  
Bertrand Napoleon ◽  
Anne-Isabelle Lemaistre ◽  
Marc Giovannini ◽  
Virendra Joshi ◽  
...  
Keyword(s):  
Image Recognition ◽  
Computer Aided Diagnosis ◽  
Confocal Laser Endomicroscopy ◽  
Confocal Laser ◽  
Pancreatic Cysts ◽  
Computer Aided ◽  
Aided Diagnosis

239 Computer Aided Diagnosis of Barrett's Esophagus Using Confocal Laser Endomicroscopy: Preliminary Data

2012 ◽  
Vol 75 (4) ◽  
pp. AB126 ◽  
Author(s):  
Enrico Grisan ◽  
Elisa Veronese ◽  
Giorgio Diamantis ◽  
Cristina Trovato ◽  
Cristiano Crosta ◽  
...  
Keyword(s):  
Barrett’S Esophagus ◽  
Preliminary Data ◽  
Barrett's Esophagus ◽  
Computer Aided Diagnosis ◽  
Confocal Laser Endomicroscopy ◽  
Confocal Laser ◽  
Computer Aided ◽  
Aided Diagnosis

scholarly journals Computer Aided Diagnosis for Confocal Laser Endomicroscopy in Advanced Colorectal Adenocarcinoma

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0154863 ◽  
Author(s):  
Daniela Ştefănescu ◽  
Costin Streba ◽  
Elena Tatiana Cârţână ◽  
Adrian Săftoiu ◽  
Gabriel Gruionu ◽  
...  
Keyword(s):  
Colorectal Adenocarcinoma ◽  
Computer Aided Diagnosis ◽  
Confocal Laser Endomicroscopy ◽  
Confocal Laser ◽  
Computer Aided ◽  
Aided Diagnosis

Pattern-Recognition: A Comparison of the Performance of Clinicians and Non-Clinicians - with a Note on the Performance of a Computer-Based System

1972 ◽  
Vol 11 (01) ◽  
pp. 32-37 ◽  
Author(s):  
F. T. DE DOMBAL ◽  
J. C. HORROCKS ◽  
J. R. STANILAND ◽  
P. J. GUILLOU
Keyword(s):  
Pattern Recognition ◽  
Computer System ◽  
Computer Aided Diagnosis ◽  
Clinical Interview ◽  
Computer Performance ◽  
Pattern Size ◽  
Computer Aided ◽  
Computer Based ◽  
Aided Diagnosis ◽  
Better Than

This paper describes a series of 10,500 attempts at »pattern-recognition« by two groups of humans and a computer based system. There was little difference between the performances of 11 clinicians and 11 other persons of comparable intellectual capability. Both groups’ performances were related to the pattern-size, the accuracy diminishing rapidly as the patterns grew larger. By contrast the computer system increased its accuracy as the patterns increased in size.It is suggested (a) that clinicians are very little better than others at pattem-recognition, (b) that the clinician is incapable of analysing on a probabilistic basis the data he collects during a traditional clinical interview and examination and (c) that the study emphasises once again a major difference between human and computer performance. The implications as - regards human- and computer-aided diagnosis are discussed.

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