Title

Set-based Cascading Approaches for Magnetic Resonance (MR) Image Segmentation (SCAMIS).

Publication Type

Conference Proceeding Article

Publication Date

12-2006

Abstract

This paper introduces Set-based Cascading Approach for Medical Image Segmentation (SCAMIS), a new methodology for segmentation of medical imaging by integrating a number of algorithms. Existing approaches typically adopt the pipeline methodology. Although these methods provide promising results, the results generated are still susceptible to over-segmentation and leaking. In our methodology, we describe how set operations can be utilized to better overcome these problems. To evaluate the effectiveness of this approach, Magnetic Resonance Images taken from a teaching hospital research programme have been utilised, to reflect the real world quality needed for testing in patient datasets. A comparison between the pipeline and set-based methodology is also presented.

Discipline

Computer Sciences

Research Areas

Intelligent Systems and Decision Analytics

Publication

American Medical Informatics Association Annual Symposium (AMIA)

First Page

504

Last Page

508

City or Country

Washington DC, USA

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