| Title | Feature extraction for classification of thin-layer chromatography images |
| Publication Type | Book |
| Year of Publication | 2005 |
| Authors | Sousa, AV, Mendonça, AM, Campilho, A, Aguiar, R, Sá Miranda, C |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 3656 LNCS |
| Number of Pages | 974 - 981 |
| City | Toronto |
| ISBN Number | 03029743 (ISSN); 3540290699 (ISBN); 9783540290698 (ISBN) |
| Keywords | Edge detection, Feature extraction, Image analysis, Image segmentation, Oligosaccharides, Thin layer chromatography, Thin-Layer Chromatography images |
| Abstract | Thin-Layer Chromatography images are used to detect and identify the presence of specific oligosaccharides, expressed by the existence, at different positions, of bands in the gel image. ID gaussian deconvolution, commonly used for band detection, does not produce good results due to the large curvature observed in the bands. To overcome this uncertainty on the band position, we propose a novel feature extraction methodology that allows an accurate modeling of curved bands. The features are used to classify the data into two different classes, to differentiate normal from pathologic cases. The paper presents the developed methodology together with the analysis and discussion of the results. © Springer-Verlag Berlin Heidelberg 2005. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-33645996661&partnerID=40&md5=6ef97f4dfec52add55258aec9e98bb52 |
