Optimal feature extraction for the segmentation of medical images
Optimal feature extraction for the segmentation of medical images
- Author(s): R. Porter ; S. Huckett ; C.N. Canagarajah
- DOI: 10.1049/cp:19971009
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- Author(s): R. Porter ; S. Huckett ; C.N. Canagarajah Source: 6th International Conference on Image Processing and its Applications, 1997 p. 814 – 818
- Conference: 6th International Conference on Image Processing and its Applications
- DOI: 10.1049/cp:19971009
- ISBN: 0 85296 692 X
- Location: Dublin, Ireland
- Conference date: 14-17 July 1997
- Format: PDF
Many image segmentation algorithms use a small local area around each pixel for the extraction of features, in order to minimise the effect of image anomalies. The main drawback of this approach is its generation of classification errors at region boundaries, where the local area can contain pixels from more than one region. In this paper, a novel method of determining the optimal position of the local area for feature extraction is presented. The proposed technique avoids overlap into adjacent regions by examining the intensity gradients of neighbouring pixels and shifting the area for feature extraction accordingly. The improvement obtained using this technique is demonstrated on a variety of MRI medical images.
Inspec keywords: image segmentation; biomedical NMR; feature extraction; medical image processing; image classification
Subjects: Radiation and radioactivity applications in biomedicine; Computer vision and image processing techniques; Medical magnetic resonance imaging and spectroscopy; Patient diagnostic methods and instrumentation; Biomagnetism; Biology and medical computing; Optical information, image and video signal processing
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