Quaternion neural networks applied to prostate cancer gleason grading

Aaron Greenblatt, Clara Mosquera-Lopez, Sos Agaian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

28 Scopus citations

Abstract

Diagnosis of prostate cancer currently involves visual examination of samples for the assignment of Gleason grades using a microscope, a time-consuming and subjective process. Computer-aided diagnosis (CAD) of histopathology images has become an important research area in diagnostic pathology. This paper presents a scheme to improve the accuracy of existing CAD systems for Gleason grading on digital biopsy slides by combining color and multi-scale information using quaternion algebra. The distinguishing features of presented algorithm are: 1) use of the quaternion wavelet transform and modified local binary patterns for the analysis of image texture in regions of interest; 2) A two-stage classification method: (a) a quaternion neural network with a new high-speed learning algorithm used for multiclass classification, and (b) several binary Support Vector Machine (SVM) classifiers used for classification refinement. In order to evaluate performance, hold-one-out cross validation is applied to a data set of 71 images of prostatic carcinomas belonging to Gleason grades 3, 4 and 5. The developed system assigns the correct Gleason grade in 98.87% of test cases and outperforms other published automatic Gleason grading systems. Moreover, averaged over all the classes, testing of the proposed method shows a specificity rate of 0.990 and a sensitivity rate of 0.967. Experimental results demonstrate the proposed scheme can help pathologists and radiologists diagnose prostate cancer more efficiently and with better reproducability.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Pages1144-1149
Number of pages6
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013 - Manchester, United Kingdom
Duration: Oct 13 2013Oct 16 2013

Publication series

NameProceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013

Conference

Conference2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Country/TerritoryUnited Kingdom
CityManchester
Period10/13/1310/16/13

Keywords

  • Automated gleason grading
  • Neural network
  • Prostate cancer
  • Quaternion
  • Wavelet transform

ASJC Scopus subject areas

  • Human-Computer Interaction

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