Abstract
Recent research trends focus on how multiscale biomedical information can be modeled and transformed into knowledge, in order to lead to a less interfering but also more individualized diagnosis and therapy. In order to assess the clinical importance of models of human pathology (e.g. cancer), it is necessary to validate them with prior and post treatment clinical data which in turn requires the determination of the tumor size and shape with high resolution, accuracy and precision, as well as structural and physiological information. This paper discusses some of the most important image analysis challenges in order to define an optimal method for extracting more accurate and precise anatomical and functional information related to the underlying pathology, which can be used for initializing and validating models of pathophysiology as well as simulations/predictions of the response to therapeutical regimes.
Chapter PDF
Similar content being viewed by others
References
Behrenbruch, C.P., Marias, K., Armitage, P.A., Yam, M., Moore, N.R., English, R.E., Clarke, P.J., Leong, F.J., Sir Brady, J.M.: Fusion of contrast-enhanced breast MR and mammographic imaging data. British Journal of Radiology 77, 201–208 (2004)
Behrenbruch, C.P., Marias, K., Armitage, P.A., Yam, M., Moore, N., English, R.E., Clarke, P.J., Brady, M.: Fusion of Contrast-Enhanced Breast MR and Mammographic Imaging Data. In: Medical Image Analysis (MedIA), vol. 7(3), pp. 311–340. Elsevier, Amsterdam (2003)
Guimond, A., Roche, A., Ayache, N., Meunier, J.: Multimodal Brain Warping Using the Demons Algorithm and Adaptative Intensity Corrections. IEEE Transaction on Medical Imaging 20(1), 58–69 (2001)
McInerney, T., Terzopolous, D.: Deformable models in medical image analysis: a survey. In: Medical Image Analysis, pp. 91–108. Oxford University Press, New York (1996)
Penney, G.P., Weese, J., Little, J.A., Hill, D.L.G., Hawkes, D.J.: A comparison of similarity measures for use in 2D-3D medical image registrtation. IEEE Transactions in Medical Imaging 17, 586–595 (1998)
Marias, K., Ripoll, J., Meyer, H., Ntziachristos, V., Orphanoudakis, S.: Image Analysis for Assessing Molecular Activity Changes in Time-Dependent Geometries. IEEE Transactions on Medical Imaging, Special issue on Molecular Imaging 24(7) (July 2005)
Margaritis, T., Marias, K., Kafetzopoulos, D.: Improved Microarray Spot Segmentation by Combining two Information Channels. In: proceedings of the 2006 IEEE Engineering in Medicine and Biology Society (EMBS) Annual International Conference, IEEE. 2006, New York, USA (2006)
Bhujwalla, Z.M., Artemov, D., Glockner, J.: Tumor angiogenesis, vascularization,and contrast-enhanced magnetic resonance imaging. Top Magn Reson Imaging 10, 92–103 (1999)
Highnam, R.P., Brady, J.M.: Mammographic Image Analysis. Kluwer Academic Publishers, Dordrecht (1999)
Chen, Y., Dougherty, E.R, Bittner, M.L: Ratio-based decisions and the quantitative analysis of cDNA microarray images. J. Biomed. Optics 2, 364–374 (1997)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Marias, K. et al. (2007). Multi-level Analysis and Information Extraction Considerations for Validating 4D Models of Human Function. In: Duffy, V.G. (eds) Digital Human Modeling. ICDHM 2007. Lecture Notes in Computer Science, vol 4561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73321-8_81
Download citation
DOI: https://doi.org/10.1007/978-3-540-73321-8_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73318-8
Online ISBN: 978-3-540-73321-8
eBook Packages: Computer ScienceComputer Science (R0)