A Weighted K-means Algorithm applied to Brain Tissue Classification
Fuente:
Redalyc
Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Artículo científico |
| Lingua: | en |
| Pubblicazione: |
Universidad Nacional de La Plata
2005
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1876477329126981632 |
|---|---|
| author | Guillermo N. Abras |
| author_facet | Guillermo N. Abras |
| contents | A Weighted K-means Algorithm applied to Brain Tissue Classification Guillermo N. Abras Virginia L. Ballarin Computación Brain Images Tissue Pattern Recognition Tissue classification in Magnetic Resonance (MR) brain images is an important issue in the analysis of several brain dementias. This paper presents a modification of the classical K-means algorithm taking into account the number of times specific features appear in an image, employing, for that purpose, a weighted mean to calculate the centroid of every cluster. Pattern Recognition techniques allow grouping pixels based on features similarity. In this paper, multispectral gray-level intensity MR brain images are used. T1, T2 and PD-weighted images provide different and complementary information about the tissues. Segmentation is performed in order to classify each pixel of the resulting image according to four possible classes: cerebro-spinal fluid (CSF), white matter (WM), gray matter (GM) and background. T1, T2 and PD-weighted images are used as patterns. The proposed algorithm weighs the number of pixels corresponding to each set of gray levels in the feature vector. As a consequence, an automatic segmentation of the brain tissue is obtained. The algorithm provides faster results if compared with the traditional K-means, thereby retrieving complementary information from the images. 2005 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067344005 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.03 Vol.5 |
| format | Artículo científico |
| id | redalyc_638067344005 |
| institution | Redalyc |
| language | en |
| publishDate | 2005 |
| publisher | Universidad Nacional de La Plata |
| spellingShingle | A Weighted K-means Algorithm applied to Brain Tissue Classification Guillermo N. Abras Computación Brain Images Tissue Pattern Recognition A Weighted K-means Algorithm applied to Brain Tissue Classification Guillermo N. Abras Virginia L. Ballarin Computación Brain Images Tissue Pattern Recognition Tissue classification in Magnetic Resonance (MR) brain images is an important issue in the analysis of several brain dementias. This paper presents a modification of the classical K-means algorithm taking into account the number of times specific features appear in an image, employing, for that purpose, a weighted mean to calculate the centroid of every cluster. Pattern Recognition techniques allow grouping pixels based on features similarity. In this paper, multispectral gray-level intensity MR brain images are used. T1, T2 and PD-weighted images provide different and complementary information about the tissues. Segmentation is performed in order to classify each pixel of the resulting image according to four possible classes: cerebro-spinal fluid (CSF), white matter (WM), gray matter (GM) and background. T1, T2 and PD-weighted images are used as patterns. The proposed algorithm weighs the number of pixels corresponding to each set of gray levels in the feature vector. As a consequence, an automatic segmentation of the brain tissue is obtained. The algorithm provides faster results if compared with the traditional K-means, thereby retrieving complementary information from the images. 2005 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067344005 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.03 Vol.5 |
| title | A Weighted K-means Algorithm applied to Brain Tissue Classification |
| topic | Computación Brain Images Tissue Pattern Recognition |
| url | https://www.redalyc.org/articulo.oa?id=638067344005 |