New PDF release: Medical Image Computing and Computer-Assisted Intervention –

By M. R. Kaus, S. K. Warfield, A. Nabavi, E. Chatzidakis, P. M. Black, F. A. Jolesz (auth.), Chris Taylor, Alain Colchester (eds.)

ISBN-10: 3540482326

ISBN-13: 9783540482321

ISBN-10: 354066503X

ISBN-13: 9783540665038

This e-book constitutes the refereed complaints of the second one overseas convention on scientific picture Computing and Computer-Assisted Intervention, MICCAI'99, held in Cambridge, united kingdom, in September 1999.
The 133 revised complete papers offered have been rigorously reviewed and chosen from a complete of 213 full-length papers submitted. The booklet is split into topical sections on data-driven segmentation, segmentation utilizing structural versions, photo processing and have detection, surfaces and form, dimension and interpretation, spatiotemporal and diffusion tensor research, registration and fusion, visualization, image-guided intervention, robot platforms, and biomechanics and simulation.

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Read Online or Download Medical Image Computing and Computer-Assisted Intervention – MICCAI’99: Second International Conference, Cambridge, UK, September 19-22, 1999. Proceedings PDF

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Additional resources for Medical Image Computing and Computer-Assisted Intervention – MICCAI’99: Second International Conference, Cambridge, UK, September 19-22, 1999. Proceedings

Example text

For 3 patients, we therefore calculated measures which assess this degree of correspondence between two human experts and between each of the experts with the automatic algorithm. Although the inter-observer variability for the experts was very large, the average overall agreement between the two experts was still better than the agreement between any of the experts and the automated algorithm. However, the average overall agreement between expert 2 and the automatic method was comparable to that between the experts.

European project on brain morphometry (BIOMORPH, EU-BIOMED2 project nr. BMH4-CT96-0845, 1996–1998). 16 13. F. Maes, A. Collignon, D. Vandermeulen, G. Marchal, and P. Suetens. Multimodality image registration by maximization of mutual information. IEEE Transactions on Medical Imaging, 16(2):187–198, April 1997. 16 14. F. F. Colchester. Measuring global and local spatial correspondence using information theory. In Proceedings of Medical Image Computing and Computer-Assisted Intervention – MICCAI’98, volume 1496 of Lecture Notes in Computer Science, pages 964–973.

Medical Physics, Queens Medical Centre, Nottingham, NG7 2UH, UK 2 Dept. Clinical Neurology, University of Nottingham, NG7 2UH, UK 3 Dept. of Academic Radiology, University of Nottingham, NG7 2UH, UK Abstract. This paper describes a semi-automatic method of determining the infarct volume, an important parameter in the assessment of stroke patients, from MRI Diffusion Weighted Images (DWI). An adaptive thresholding algorithm incorporating a spatial constraint was used to segment the images. The relationship between adjacent pixels was modeled using a Markov Random Field (MRF) and the Iterative Conditional Modes (ICM) method was used to find a locally optimum solution.

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Medical Image Computing and Computer-Assisted Intervention – MICCAI’99: Second International Conference, Cambridge, UK, September 19-22, 1999. Proceedings by M. R. Kaus, S. K. Warfield, A. Nabavi, E. Chatzidakis, P. M. Black, F. A. Jolesz (auth.), Chris Taylor, Alain Colchester (eds.)


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