The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Image Databases in Medical Applications

Juha Koikkalainen

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Engineering Physics and Mathematics for public examination and debate in Auditorium F1 at Helsinki University of Technology (Espoo, Finland) on the 17th of March, 2006, at 12 noon.

Overview in PDF format (ISBN 951-22-8084-1)   [2128 KB]
Dissertation is also available in print (ISBN 951-22-8083-3)

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.

This thesis consists of an overview and of the following 7 publications:

  1. 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. © 2004 IEEE. By permission.
  2. 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. © 2004 Elsevier Science. By permission.
  3. Koikkalainen, J., Nyman, M., Hietala, J., Lötjönen, J., and Ruotsalainen, U. (2005). Age- and Gender-Related Shape Changes and Asymmetry of Striatum. Helsinki University of Technology, Publications in Engineering Physics, Report A839 (TKK-F-A839).
  4. 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. © 2004 Springer Science+Business Media. By permission.
  5. 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. © 2005 Springer Science+Business Media. By permission.
  6. 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. © 2003 Springer Science+Business Media. By permission.
  7. 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. © 2002 Springer Science+Business Media. By permission.

Keywords: medical image processing, deformable-models, statistical and probabilistic shape models, shape analysis

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© 2006 Helsinki University of Technology

Last update 2011-05-26