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Classification of human knee data from magnetic resonance images
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Reyes-Aldasoro, Constantino Carlos and Bhalerao, Abhir (2002) Classification of human knee data from magnetic resonance images. Department of Computer Science. (Department of Computer Science Research Report). (Unpublished)
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PDF (Department of Computer Science Research Report)
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Abstract
This report considers the general problem of segmentation of Magnetic Resonance Images. The final objective is to correctly assign a unique label or class which represents an anatomical structure to every pixel or voxel in a data set. The images analysed describe a human knee scanned by Magnetic Resonance (MR). A brief description of the anatomy of the knee and physics of MR imaging is given. A review of image segmentation approaches, focusing on multiresolution and texture segmentation, follows. The first segmentation technique implemented here is grey level thresholding, which is later improved by adding two other descriptors of the images: standard deviation and a moment from the co-occurrence matrix. Frequency analysis through sub-band filtering is proposed as a way to improve the description of the textural regions and boundaries between anatomical regions. Comparative results of the different techniques are presented and finally conclusions and future work is proposed.
| Item Type: | Report | ||||
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| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QC Physics R Medicine > RC Internal medicine R Medicine > RD Surgery T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science > Computer Science | ||||
| Library of Congress Subject Headings (LCSH): | Magnetic resonance imaging, Knee -- Magnetic resonance imaging, Image segmentation , Image processing -- Digital techniques | ||||
| Series Name: | Department of Computer Science Research Report | ||||
| Publisher: | Department of Computer Science | ||||
| Official Date: | March 2002 | ||||
| Dates: |
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| Number: | Number 388 | ||||
| Number of Pages: | 31 | ||||
| DOI: | CS-RR-388 | ||||
| Institution: | University of Warwick | ||||
| Theses Department: | Department of Computer Science | ||||
| Status: | Not Peer Reviewed | ||||
| Publication Status: | Unpublished | ||||
| Related URLs: |
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