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Using curve-fitting of curvilinear features for assessing registration of clinical neuropathology with in vivo MRI.

Laissue, PP and Kenwright, C and Hojjat, SA and Colchester, AC (2008) Using curve-fitting of curvilinear features for assessing registration of clinical neuropathology with in vivo MRI. In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008, 2008-09-06 - 2008-09-10, New York, NY.

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Abstract

Traditional neuropathological examination provides information about neurological disease or injury of a patient at a high-resolution level. Correlating this type of post mortem diagnosis with in vivo image data of the same patient acquired by non-invasive tomographic scans greatly complements the interpretation of any disease or injury. We present the validation of a registration method for correlating macroscopic pathological images with MR images of the same patient. This also allows for 3-D mapping of the distribution of pathological changes throughout the brain. As the validation deals with datasets of widely differing sampling, we propose a method using smooth curvilinear anatomical features in the brain which allows interpolation between wide-spaced samples. Curvilinear features are common anatomically, and if selected carefully have the potential to allow determination of the accuracy of co-registration across large areas of a volume of interest.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008 11th International Conference, New York, NY, USA, September 6-10, 2008, Proceedings, Part II. Part of the Lecture Notes in Computer Science book series (LNCS, volume 5242)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Faculty of Science and Health > Life Sciences, School of
Depositing User: Elements
Date Deposited: 06 Mar 2018 10:21
Last Modified: 09 Sep 2019 08:15
URI: http://repository.essex.ac.uk/id/eprint/21568

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