Abstract
We can observes a section of the body using MRI and CT . CT is suitable for the blood flow and the diagnosis of the wrong point of the bone by the computed tomograph, and MRI is suitable for the diagnosis of the cerebral brain infarction and the brain tumor. Because different nature is observed to so same the observation object, a, doctor, uses CT and an MRI image complementary, and sees a patient. The feature which appears in both images remarkably is extracted using the CT image and the MRI image by this paper. Various three-dimensional filters are generated using the ICA base in the self-histionic target from the characteristic image for that image, and how to extract a remarkable feature from the feature image which could get is proposed by this research. A remarkable feature is extracted from the CT image and the MRI image of the patient which actually has a tumor , and its effectiveness is shown.
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Morita, S. (2012). Self-Organized Three Dimensional Feature Extraction of MRI and CT. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34500-5_9
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DOI: https://doi.org/10.1007/978-3-642-34500-5_9
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