Tree-structured grading of pathological images of prostate

Reza Farjam, Hamid Soltanian-Zadeh, Reza A. Zoroofi, Kourosh Jafari-Khouzani

Research output: Contribution to journalConference articlepeer-review

Abstract

This paper presents a new algorithm for Gleason grading of pathological images of prostate. Structural features of the glands are extracted and used in a tree-structured (TS) algorithm to classify the images into five Gleason grades of 1 to 5. In this algorithm the image is first segmented to locate the glandular regions using texture features and a K-means clustering algorithm. The glands are then labeled from the glandular regions. In each stage of the proposed TS algorithm, shape and intensity-based features of the glands are extracted and used in a linear classifier to classify the image into two groups. Despite some proposed methods in the literature which use only texture features, this technique uses the features like roundness and shape distribution, which are related to the structure of the glands in each grade and are independent of the magnification. The proposed method is therefore robust to illumination and magnification variations. To evaluate the performance of the proposed method, we use two datasets. Data set 1 contains 91 images with similar magnifications and illuminations. Data set 2 contains 199 images with different magnifications and illuminations. Using leave-one-out technique, we achieve 95% and 85% accuracy for dataset 1 and 2, respectively.

Original languageEnglish (US)
Article number87
Pages (from-to)840-851
Number of pages12
JournalProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume5747
Issue numberII
DOIs
StatePublished - 2005
Externally publishedYes
EventMedical Imaging 2005 - Image Processing - San Diego, CA, United States
Duration: Feb 13 2005Feb 17 2005

Keywords

  • Gleason grading
  • Prostate cancer
  • Texture analysis
  • Tree-structured classification

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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