Multimodality medical image database for temporal lobe epilepsy

Mohammad-Reza Siadat; Hamid Soltanian-Zadeh; Farshad A. Fotouhi; Kost Elisevich

doi:10.1117/12.481936

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19 May 2003 Multimodality medical image database for temporal lobe epilepsy

Mohammad-Reza Siadat, Hamid Soltanian-Zadeh, Farshad A. Fotouhi, Kost Elisevich

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Proceedings Volume 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation; (2003) https://doi.org/10.1117/12.481936
Event: Medical Imaging 2003, 2003, San Diego, California, United States

Abstract

This paper presents the development of a human brain multi-modality database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted and FLAIR MRI and ictal/interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as non-verbal Wechsler memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication matches the neurosurgeons expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

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Mohammad-Reza Siadat, Hamid Soltanian-Zadeh, Farshad A. Fotouhi, and Kost Elisevich "Multimodality medical image database for temporal lobe epilepsy", Proc. SPIE 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation, (19 May 2003); https://doi.org/10.1117/12.481936

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