



@book {2221,
	title = {Classification-based segmentation of the region of interest in chromatographic images},
	series = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci.},
	volume = {6754 LNCS},
	year = {2011},
	note = {Conference code: 85546Export Date: 21 November 2012Source: Scopusdoi: 10.1007/978-3-642-21596-4_8Language of Original Document: EnglishCorrespondence Address: Sousa, A.V.; Instituto de Engenharia Biom{\'e}dica, Universidade Do Porto, Rua Roberto Frias, s/n, 4200-465 Porto, Portugal; email: asousa@eu.ipp.ptReferences: Zarate, Y., Hopkin, R., Fabry{\textquoteright}s Disease (2008) The Lancet, 372 (9647), pp. 1427-1435;Linthorst, G.E., Vedder, A., Aerts, J.M., Hollak, C.E., Screening for Fabry Disease Using Whole Blood Spots Fails to Identify One-third of Female Carriers (2005) Clinica Chimica Acta, 353 (1-2), pp. 201-203; 
Eng, C.M., Germain, D.P., Banikazemi, M., Warnock, D.G., Wanner, C., Hopkin, R.J., Bultas, J., Wilcox, W.R., Fabry Disease: Guidelines for the Evaluation and Management of Multi-organ System Involvement (2006) Genetics in Medicine, 8 (9), pp. 539-548; 
Gerasimov, A.V., Use of the Software Processing of Scanned Chromatogram Images in Quantitative Planar Chromatography (2004) J. of Anal. Chem., 59 (4), pp. 348-353; 
Bajla, I., Hollander, I., Fluch, S., Burg, K., Kollar, M., An Alternative Method for Electrophoretic Gel Image Analysis in the Gelmaster Software (2005) Comput. Methods Programs Biomed., 77 (3), pp. 209-231; 
Sousa, A.V., Mendon{\c c}a, A.M., Campilho, A., Chromatographic Pattern Classification (2008) IEEE Trans. on Biomedical Engineering, 55 (6), pp. 1687-1696; 
Bajla, I., Rubl{\'\i}k, F., Arendack{\'a}, B., Farka{\v s}, I., Horni{\v s}ov{\'a}, K., {\v S}tolc, S., Witkovsk{\'y}, V., Segmentation and Supervised Classification of Image Objects in Epo Doping-control (2009) Machine Vision and Applications, 20 (4), pp. 243-259; 
Sousa, A.V., Aguiar, R., Mendon{\c c}a, A.M., Campilho, A., Automatic Lane and Band Detection in Images of Thin Layer Chromatography (2004) LNCS, 3212, pp. 158-165. , Campilho, A.C., Kamel, M.S. (eds.) ICIAR 2004. Springer, Heidelberg; 
Mendon{\c c}a, A.M., Sousa, A.V., S{\'a}-Miranda, M.C., Campilho, A., Automatic segmentation of chromatographic images for region of interest delineation (2011) SPIE Medical Imaging; 
Dempster, A., Laird, N., Rubin, D., Maximum Likelihood from Incomplete Data via the EM Algorithm (1997) J. of the Royal Statistical Society. Series B, 39 (1), pp. 1-38; 
Heijden, F., Robert, P.W.D., Ridder, D., Tax, D.M.J., (2004) Classification, Parameter Estimation and State Estimation, , John Wiley \& Sons, Chichester
},
	month = {2011///},
	pages = {68 - 78},
	address = {Burnaby, BC},
	abstract = {This paper proposes a classification-based method for automating the segmentation of the region of interest (ROI) in digital images of chromatographic plates. Image segmentation is performed in two phases. In the first phase an unsupervised learning method classifies the image pixels into three classes: frame, ROI or unknown. In the second phase, distance features calculated for the members of the three classes are used for deciding on the new label, ROI or frame, for each individual connected segment previously classified as unknown.The segmentation result is post-processed using a sequence of morphological operators before obtaining the final ROI rectangular area. The proposed methodology, which is the initial step for the development of a screening tool for Fabry disease, was successfully evaluated in a dataset of 58 chromatographic images. {\textcopyright} 2011 Springer-Verlag.},
	keywords = {Chromatographic images, Chromatographic plates, Chromatography, Data sets, Digital image, Distance feature, Fabry disease, Image analysis, Image pixels, Image segmentation, Morphological operator, Rectangular area, Region of interest, Region of interest delineation, Screening tool, Second phase, Segmentation results, Unsupervised learning, Unsupervised learning method},
	isbn = {03029743 (ISSN); 9783642215957 (ISBN)},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-79960331409\&partnerID=40\&md5=c248f56c8a7bda71832c4b569e32164b},
	author = {Sousa, A.V. and Mendon{\c c}a, A.M. and S{\'a}-Miranda, M.C. and Campilho, A.}
}
