Quantification of periventricular lesions from MR brain images /
average Mahalanobis distance and neural network, are
| Main Author: | |
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| Format: | Thesis eBook |
| Language: | English |
| Published: |
[Place of publication not identified] :
[publisher not identified] ;
1996.
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| Subjects: | |
| Online Access: | Link to OAKTrust copy |
| Summary: | average Mahalanobis distance and neural network, are clinically usable software environment. evaluated as part of the region growing algorithm. The for the medical community to quantify periventricular lesions generated and then used as the homogeneity criterion in a Graphical-User-Interface is designed in order to have a growing with the neural network stopping criterion provides lesions for the purpose of studying ways to prevent or Magnetic Resonance brain images of Acquired Immunodeficiency Periventricular lesions are associated with hyperintensity in Provisions are made for a radiologist to input lesion region growing algorithm. Two different stopping criteria, results obtained indicate that the perpendicular region reverse this disease. Basically this work has led to a tool seedpoints interactively. A comprehensive feature vector is Syndrome patients. The objective of this research has been the closest match to the manual segmentation of lesions. A the development of a user-friendly software to quantify such which are currently assessed in a qualitative manner. |
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| Item Description: | "Major subject: Electrical Engineeering". Vita. |
| Physical Description: | xi, 72 leaves : illustrations ; 28 cm. Also available online. Issued also on microfiche from Lange Micrographics. |
| Bibliography: | Includes bibliographical references: pages 58-62. |