Detection of objects by integrating watersheds and critical point analysis

Fu, Guoyi and Hojjatoleslami, Ali and Colchester, Alan C. F. (2003) Detection of objects by integrating watersheds and critical point analysis. In: Ellis, Randy E. and Peters, Terry M., eds. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. Lecture Notes in Computer Science, 2879. Springer, Berlin 109 -116. ISBN 3540204644. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1007/978-3-540-39903-2_14

Abstract

This paper presents an improved method for detection of "significant" low-level objects in medical images. Information derived from watershed regions is used to select and refine saddle points in the discrete domain and to construct the watersheds & watercourses (ridges and valleys). The method overcomes previous topological problems where multiple redundant saddle points are detected in digital images. We also demonstrate an improved method of pruning the tessellation from which salient objects are defined. Preliminary evaluation was based on theoretical analysis, visual inspection of a set of medical images, and human observer experiments with promising result.

Item Type: Conference or workshop item (Paper)
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
Divisions: Faculties > Science Technology and Medical Studies > Kent Institute of Medicine and Health Sciences (KIMHS)
Depositing User: M.P. Stone
Date Deposited: 10 Sep 2008 09:39
Last Modified: 14 May 2014 13:48
Resource URI: http://kar.kent.ac.uk/id/eprint/12103 (The current URI for this page, for reference purposes)
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