Context-based segmentation of renal corpuscle from microscope renal biopsy image sequence

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

A renal biopsy is a procedure to get a small piece of kidney for microscopic examination. With the development of tissue sectioning and medical imaging techniques, microscope renal biopsy image sequences are consequently obtained for computer-aided diagnosis. This paper proposes a new context-based segmentation algorithm for acquired image sequence, in which an improved genetic algorithm (GA) patching method is developed to segment different size target. To guarantee the correctness of first image segmentation and facilitate the use of context information, a boundary fusion operation and a simplified scale-invariant feature transform (SIFT)-based registration are presented respectively. The experimental results show the proposed segmentation algorithm is effective and accurate for renal biopsy image sequence.

Original languageEnglish
Pages (from-to)1114-1121
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE98A
Issue number5
DOIs
Publication statusPublished - 2015 May 1

Fingerprint

Biopsy
Image Sequence
Microscope
Microscopes
Segmentation
Computer aided diagnosis
Computer-aided Diagnosis
Scale Invariant Feature Transform
Medical Imaging
Medical imaging
Kidney
Image segmentation
Image Segmentation
Registration
Correctness
Fusion
Microscopic examination
Fusion reactions
Genetic algorithms
Genetic Algorithm

Keywords

  • Computer-aided diagnosis
  • Genetic algorithm
  • Microscope image
  • Registration
  • Segmentation

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Signal Processing

Cite this

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AB - A renal biopsy is a procedure to get a small piece of kidney for microscopic examination. With the development of tissue sectioning and medical imaging techniques, microscope renal biopsy image sequences are consequently obtained for computer-aided diagnosis. This paper proposes a new context-based segmentation algorithm for acquired image sequence, in which an improved genetic algorithm (GA) patching method is developed to segment different size target. To guarantee the correctness of first image segmentation and facilitate the use of context information, a boundary fusion operation and a simplified scale-invariant feature transform (SIFT)-based registration are presented respectively. The experimental results show the proposed segmentation algorithm is effective and accurate for renal biopsy image sequence.

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