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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Plissiti, M. E. | en |
| dc.contributor.author | Nikou, C. | en |
| dc.contributor.author | Charchanti, A. | en |
| dc.date.accessioned | 2015-11-24T17:02:36Z | - |
| dc.date.available | 2015-11-24T17:02:36Z | - |
| dc.identifier.issn | 1089-7771 | - |
| dc.identifier.uri | https://olympias.lib.uoi.gr/jspui/handle/123456789/11074 | - |
| dc.rights | Default Licence | - |
| dc.subject | cell nuclei detection | en |
| dc.subject | fuzzy c-means (fcm) | en |
| dc.subject | morphological reconstruction | en |
| dc.subject | pap smear images | en |
| dc.subject | support vector machines (svms) | en |
| dc.subject | segmentation | en |
| dc.subject | cytoplast | en |
| dc.title | Automated Detection of Cell Nuclei in Pap Smear Images Using Morphological Reconstruction and Clustering | en |
| heal.type | journalArticle | - |
| heal.type.en | Journal article | en |
| heal.type.el | Άρθρο Περιοδικού | el |
| heal.identifier.primary | Doi 10.1109/Titb.2010.2087030 | - |
| heal.language | en | - |
| heal.access | campus | - |
| heal.recordProvider | Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικής | el |
| heal.publicationDate | 2011 | - |
| heal.abstract | In this paper, we present a fully automated method for cell nuclei detection in Pap smear images. The locations of the candidate nuclei centroids in the image are detected with morphological analysis and they are refined in a second step, which incorporates a priori knowledge about the circumference of each nucleus. The elimination of the undesirable artifacts is achieved in two steps: the application of a distance-dependent rule on the resulted centroids; and the application of classification algorithms. In our method, we have examined the performance of an unsupervised (fuzzy C-means) and a supervised (support vector machines) classification technique. In both classification techniques, the effect of the refinement step improves the performance of the clustering algorithm. The proposed method was evaluated using 38 cytological images of conventional Pap smears containing 5617 recognized squamous epithelial cells. The results are very promising, even in the case of images with high degree of cell overlapping. | en |
| heal.journalName | Ieee Transactions on Information Technology in Biomedicine | en |
| heal.journalType | peer reviewed | - |
| heal.fullTextAvailability | TRUE | - |
| Appears in Collections: | Άρθρα σε επιστημονικά περιοδικά ( Ανοικτά) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| nikou-2011-Automated Detection of Cell Nuclei in Pap Smear Images Using Morphological Reconstruction and Clustering.pdf | 996.58 kB | Adobe PDF | View/Open Request a copy |
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