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Image databases in medical applications

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Koikkalainen, Juha
dc.date.accessioned 2012-02-17T07:33:29Z
dc.date.available 2012-02-17T07:33:29Z
dc.date.issued 2006-03-17
dc.identifier.isbn 951-22-8084-1
dc.identifier.issn 1795-4584
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/2674
dc.description.abstract The number of medical images acquired yearly in hospitals increases all the time. These imaging data contain lots of information on the characteristics of anatomical structures and on their variations. This information can be utilized in numerous medical applications. In deformable model-based segmentation and registration methods, the information in the image databases can be used to give a priori information on the shape of the object studied and the gray-level values in the image, and on their variations. On the other hand, by studying the variations of the object of interest in different populations, the effects of, for example, aging, gender, and diseases on anatomical structures can be detected. In the work described in this Thesis, methods that utilize image databases in medical applications were studied. Methods were developed and compared for deformable model-based segmentation and registration. Model selection procedure, mean models, and combination of classifiers were studied for the construction of a good a priori model. Statistical and probabilistic shape models were generated to constrain the deformations in segmentation and registration so that only the shapes typical to the object studied were accepted. In the shape analysis of the striatum, both volume and local shape changes were studied. The effects of aging and gender, and also the asymmetries were examined. The results proved that the segmentation and registration accuracy of deformable model-based methods can be improved by utilizing the information in image databases. The databases used were relatively small. Therefore, the statistical and probabilistic methods were not able to model all the population-specific variation. On the other hand, the simpler methods, the model selection procedure, mean models, and combination of classifiers, gave good results also with the small image databases. Two main applications were the reconstruction of 3-D geometry from incomplete data and the segmentation of heart ventricles and atria from short- and long-axis magnetic resonance images. In both applications, the methods studied provided promising results. The shape analysis of the striatum showed that the volume of the striatum decreases in aging. Also, the shape of the striatum changes locally. Asymmetries in the shape were found, too, but any gender-related local shape differences were not found. en
dc.format.extent 45, [72]
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries TKK dissertations en
dc.relation.ispartofseries 25 en
dc.relation.haspart Koikkalainen, J. and Lötjönen, J. (2004). Reconstruction of 3-D Head Geometry from Digitized Point Sets: An Evaluation Study. IEEE Transactions on Information Technology in Biomedicine, 8 (3): 377-386. [article1.pdf] © 2004 IEEE. By permission.
dc.relation.haspart Lötjönen, J., Kivistö, S., Koikkalainen, J., Smutek, D., and Lauerma, K. (2004). Statistical Shape Model of Atria, Ventricles and Epicardium from Short- and Long-Axis MR Images. Medical Image Analysis, 8 (3): 371-386. [article2.pdf] © 2004 Elsevier Science. By permission.
dc.relation.haspart Koikkalainen, J., Nyman, M., Hietala, J., Lötjönen, J., and Ruotsalainen, U. (2005). Ageand Gender-Related Shape Changes and Asymmetry of Striatum. Helsinki University of Technology, Publications in Engineering Physics, Report A839 (TKK-F-A839).
dc.relation.haspart Koikkalainen, J., Pollari, M., Lötjönen, J., Kivistö, S., and Lauerma, K. (2004). Segmentation of Cardiac Structures Simultaneously from Short- and Long-Axis MR Images. In: Barillot, C., Haynor, D. R., and Hellier, P., editors, Proceedings of the 7th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2004), Lecture Notes in Computer Science, volume 3216, pages 427-434. [article4.pdf] © 2004 Springer Science+Business Media. By permission.
dc.relation.haspart Lötjönen, J., Antila, K., Lamminmäki, E., Koikkalainen, J., Lilja, M., and Cootes, T. F. (2005). Artificial Enlargement of a Training Set for Statistical Shape Models: Application to Cardiac Images. In: Frangi, A. F., Radeva, P., Santos, A., and Hernandez, M., editors, Proceedings of the Third International Workshop on Functional Imaging and Modeling of the Heart (FIMH 2005), Lecture Notes in Computer Science, volume 3504, pages 92-101. [article5.pdf] © 2005 Springer Sc ience+Business Media. By permission.
dc.relation.haspart Koikkalainen, J. and Lötjönen, J. (2003). Individualized Geometric Model from Unorganized 3-D Points: An Application to Thorax Modeling. In: Ellis, R. E. and Peters, T. M., editors, Proceedings of the 6th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2003), Lecture Notes in Computer Science, volume 2878, pages 91-98. [article6.pdf] © 2003 Springer Science+Business Media. By permission.
dc.relation.haspart Koikkalainen, J. and Lötjönen, J. (2002). Model Library for Deformable Model-Based Segmentation of 3-D Brain MR-Images. In: Dohi, T. and Kikinis, R., editors, Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2002), Lecture Notes in Computer Science, volume 2488, pages 540-547. [article7.pdf] © 2002 Springer Science+Business Media. By permission.
dc.subject.other Medical sciences en
dc.title Image databases in medical applications en
dc.type G5 Artikkeliväitöskirja fi
dc.description.version reviewed en
dc.contributor.department Department of Engineering Physics and Mathematics en
dc.contributor.department Teknillisen fysiikan ja matematiikan osasto fi
dc.subject.keyword medical image processing en
dc.subject.keyword deformable-models en
dc.subject.keyword statistical and probabilistic shape models en
dc.subject.keyword shape analysis en
dc.identifier.urn urn:nbn:fi:tkk-006610
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.lab Laboratory of Biomedical Engineering en
dc.contributor.lab Lääketieteellisen tekniikan laboratorio fi
local.aalto.digifolder Aalto_67007
local.aalto.digiauth ask


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