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Context-Based Segmentation of Renal Corpuscle from Microscope Renal Biopsy Image Sequence

Jun ZHANG, Jinglu HU

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Jun ZHANG
Information, Production and Systems Research Center, Waseda University
Jinglu HU
Graduate School of Information, Production and Systems, Waseda University

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Keywords:computer-aided diagnosis,microscope image,segmentation,registration,genetic algorithm

JOURNALRESTRICTED ACCESS

2015 Volume E98.AIssue 5Pages 1114-1121

DOIhttps://doi.org/10.1587/transfun.E98.A.1114

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Published: May 01, 2015Manuscript Received: September 19, 2014Released on J-STAGE: May 01, 2015Accepted: -Advance online publication: -Manuscript Revised: December 31, 2014

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Article overview

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.

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