A multichannel watershed-based segmentation method for multispectral chromosome classification
| dc.contributor.author | Karvelis, P. S. | en |
| dc.contributor.author | Tzallas, A. T. | en |
| dc.contributor.author | Fotiadis, D. I. | en |
| dc.contributor.author | Georgiou, I. | en |
| dc.date.accessioned | 2015-11-24T17:33:58Z | |
| dc.date.available | 2015-11-24T17:33:58Z | |
| dc.identifier.issn | 0278-0062 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/13914 | |
| dc.rights | Default Licence | - |
| dc.subject | bayes classification | en |
| dc.subject | chromosome images | en |
| dc.subject | karyotyping | en |
| dc.subject | multichannel segmentation | en |
| dc.subject | multiplex fluorescent in situ hybridization (m-fish) | en |
| dc.subject | watershed transform | en |
| dc.subject | in-situ hybridization | en |
| dc.subject | m-fish | en |
| dc.subject | joint segmentation | en |
| dc.subject | images | en |
| dc.subject | algorithm | en |
| dc.subject | binarization | en |
| dc.subject | gradient | en |
| dc.title | A multichannel watershed-based segmentation method for multispectral chromosome classification | en |
| heal.abstract | Multiplex fluorescent in situ hybridization (M-FISH) is a recently developed chromosome imaging technique where each chromosome class appears to have a distinct color. This technique not only facilitates the detection of subtle chromosomal aberrations but also makes the analysis of chromosome images easier; both for human inspection and computerized analysis. In this paper, a novel method for segmentation and classification of M-FISH chromosome images is presented. The segmentation is based on the multichannel watershed transform in order to define regions of similar spatial and spectral characteristics. Then, a Bayes classifier, task-specific on region classification, is applied. Our method consists of four basic steps: 1) computation of the gradient magnitude of the image, 2) application of the watershed transform to decompose the image into a set of homogenous regions, 3) classification of each region, and 4) merging of similar adjacent regions. The method is evaluated using a publicly available chromosome image database and the obtained overall accuracy is 82.4%. By introducing the classification of each watershed region, the proposed method achieves substantially better results compared to other methods at a lower computational cost. The combination of the multichannel segmentation and the region-based classification is found to improve the overall classification accuracy compared to pixel-by-pixel approaches. | en |
| heal.access | campus | - |
| heal.fullTextAvailability | TRUE | - |
| heal.identifier.primary | Doi 10.1109/Tmi.2008.916962 | - |
| heal.identifier.secondary | <Go to ISI>://000255433500011 | - |
| heal.journalName | IEEE Trans Med Imaging | en |
| heal.journalType | peer reviewed | - |
| heal.language | en | - |
| heal.publicationDate | 2008 | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Επιστήμης Υλικών | el |
| heal.type | journalArticle | - |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.type.en | Journal article | en |
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