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Integrating watersheds and critical point analysis for object detection in discrete 2D images

Fu, Guoyi, Hojjatoleslami, Ali, Colchester, Alan C. F. (2004) Integrating watersheds and critical point analysis for object detection in discrete 2D images. Medical Image Analysis, 8 (3). pp. 177-185. ISSN 1361-8415. (doi:10.1016/j.media.2004.06.002) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:12104)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi.org/10.1016/j.media.2004.06.002

Abstract

This paper presents an improved method for the detection of "significant" low-level objects in medical images. The method overcomes topological problems where multiple redundant saddle points are detected in digital images. Information derived from watershed regions is used to select and refine saddle points in the discrete domain and to construct the watersheds and watercourses (ridges and valleys). We also demonstrate an improved method of pruning the tessellation by which to define low level objects in zero order images. The algorithm was applied on a set of medical images with promising results. Evaluation was based on theoretical analysis and human observer experiments.

Item Type: Article
DOI/Identification number: 10.1016/j.media.2004.06.002
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing
Divisions: Divisions > Division for the Study of Law, Society and Social Justice > School of Social Policy, Sociology and Social Research
Depositing User: M.P. Stone
Date Deposited: 18 Sep 2008 15:18 UTC
Last Modified: 16 Nov 2021 09:50 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/12104 (The current URI for this page, for reference purposes)

University of Kent Author Information

Hojjatoleslami, Ali.

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CReDIT Contributor Roles:

Colchester, Alan C. F..

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