## Abstract Automatic detection and quantitation of contrast‐enhanced lesions on MRI is expected to be useful in characterizing the disease state in multiple sclerosis (MS). The enhancing structures such as cerebral vasculature and regions with no blood‐brain barrier complicate automated analysis o
A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI
✍ Scribed by C. Pachai; Y.M. Zhu; J. Grimaud; M. Hermier; A. Dromigny-Badin; A. Boudraa; G. Gimenez; C. Confavreux; J.C. Froment
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 631 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0895-6111
No coin nor oath required. For personal study only.
✦ Synopsis
Quantitative assessment of Magnetic Resonance Imaging (MRI) lesion load of patients with multiple sclerosis (MS) is the most objective approach for a better understanding of the history of the pathology, either natural or modi®ed by therapies. To achieve an accurate and reproducible quanti®cation of MS lesions in conventional brain MRI, an automatic segmentation algorithm based on a multiresolution approach using pyramidal data structures is proposed. The systematic pyramidal decomposition in the frequency domain provides a robust and ¯exible low level tool for MR image analysis. Context-dependent rules regarding MRI ®ndings in MS are used as high level considerations for automatic lesion detection.
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