A Set-based Hybrid Approach (SHA) for MRI Segmentation

A Set-based Hybrid Approach (SHA) for MRI Segmentation

This paper describes a new hybrid approach set-based hybrid approach (SHA) for magnetic resonance (MR) image segmentation by integrating two existing techniques, region-grow and threshold level set. To evaluate the proposed approach in performing real world image segmentation task, instead of using...

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Bibliographische Detailangaben
Hauptverfasser: Jiang Liu, Tze-Yun Leong, Kin Ban Chee, Boon Pin Tan, Shuter, B., Shih-Chang Wang
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Biomedical imaging
Computer science
Differential equations
Image edge detection
Image segmentation
Level set
Magnetic resonance
Magnetic resonance imaging
Medical diagnostic imaging
Radiology
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Beschreibung
Zusammenfassung:This paper describes a new hybrid approach set-based hybrid approach (SHA) for magnetic resonance (MR) image segmentation by integrating two existing techniques, region-grow and threshold level set. To evaluate the proposed approach in performing real world image segmentation task, instead of using well-taken MR-images, we use real-life images collected in a hospital. Comparison of the performance between the two individual techniques and the new hybrid technique demonstrates the effectiveness of the latter
DOI:10.1109/ICARCV.2006.345358