A method for automatic segmentation of nuclei in phase-contrast images based on intensity, convexity and texture

M. Ali Akber Dewan, M. Omair Ahmad, M. N.S. Swamy

Research output: Contribution to journalJournal Articlepeer-review

13 Citations (Scopus)

Abstract

This paper presents a method for automatic segmentation of nuclei in phase-contrast images using the intensity, convexity and texture of the nuclei. The proposed method consists of three main stages: preprocessing, h-maxima transformation-based marker controlled watershed segmentation (h-TMC), and texture analysis. In the preprocessing stage, a top-hat filter is used to increase the contrast and suppress the non-uniform illumination, shading, and other imaging artifacts in the input image. The nuclei segmentation stage consists of a distance transformation, h-maxima transformation and watershed segmentation. These transformations utilize the intensity information and the convexity property of the nucleus for the purpose of detecting a single marker in every nucleus; these markers are then used in the h-TMC watershed algorithm to obtain segments of the nuclei. However, dust particles, imaging artifacts, or prolonged cell cytoplasm may falsely be segmented as nuclei at this stage, and thus may lead to an inaccurate analysis of the cell image. In order to identify and remove these non-nuclei segments, in the third stage a texture analysis is performed, that uses six of the Haralick measures along with the AdaBoost algorithm. The novelty of the proposed method is that it introduces a systematic framework that utilizes intensity, convexity, and texture information to achieve a high accuracy for automatic segmentation of nuclei in the phase-contrast images. Extensive experiments are performed demonstrating the superior performance ({\rm precision} = 0.948; {\rm recall} = 0.924; F-{1}\hbox{-}{\rm measure} = 0.936; validation based on {\sim}4850 manually-labeled nuclei) of the proposed method.

Original languageEnglish
Article number6762958
Pages (from-to)716-728
Number of pages13
JournalIEEE Transactions on Biomedical Circuits and Systems
Volume8
Issue number5
DOIs
Publication statusPublished - 1 Oct. 2014

Keywords

  • AdaBoost algorithm
  • Haralick features
  • nuclei clustering
  • phase-contrast image
  • segmentation of nuclei

Fingerprint

Dive into the research topics of 'A method for automatic segmentation of nuclei in phase-contrast images based on intensity, convexity and texture'. Together they form a unique fingerprint.

Cite this