DTI data modeling for unlimited query support

Mohammad-Reza Siadat; Rafat Hammad; Anil Shetty; Hamid Soltanian-Zadeh; Ishwar K. Sethi; Ameen Eetemadi; Kost V. Elisevich

doi:10.1117/12.813748

13 March 2009 DTI data modeling for unlimited query support

Mohammad-Reza Siadat, Rafat Hammad, Anil Shetty, Hamid Soltanian-Zadeh, Ishwar K. Sethi, Ameen Eetemadi, Kost V. Elisevich

Author Affiliations +

Proceedings Volume 7264, Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications; 726415 (2009) https://doi.org/10.1117/12.813748
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

This paper describes Data Modeling for unstructured data of Diffusion Tensor Imaging (DTI). Data Modeling is an essential first step for data preparation in any data management and data mining procedure. Conventional Entity- Relational (E-R) data modeling is lossy, irreproducible, and time-consuming especially when dealing with unstructured image data associated with complex systems like the human brain. We propose a methodological framework for more objective E-R data modeling with unlimited query support by eliminating the structured content-dependent metadata associated with the unstructured data. The proposed method is applied to DTI data and a minimum system is implemented accordingly. Eventually supported with navigation, data fusion, and feature extraction modules, the proposed system provides a content-based support environment (C-BASE). Such an environment facilitates an unlimited query support with a reproducible and efficient database schema. Switching between different modalities of data, while confining the feature extractors within the object(s) of interest, we supply anatomically specific query results. The price of such a scheme is relatively large storage and in some cases high computational cost. The data modeling and its mathematical framework, behind the scene of query executions and the user interface of the system are presented in this paper.

Citation Download Citation

Mohammad-Reza Siadat, Rafat Hammad, Anil Shetty, Hamid Soltanian-Zadeh, Ishwar K. Sethi, Ameen Eetemadi, and Kost V. Elisevich "DTI data modeling for unlimited query support", Proc. SPIE 7264, Medical Imaging 2009: Advanced PACS-based Imaging Informatics and Therapeutic Applications, 726415 (13 March 2009); https://doi.org/10.1117/12.813748

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
10 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Data modeling

Databases

Diffusion tensor imaging

Image segmentation

Brain

Medical imaging

Neuroimaging

Show All Keywords

Keywords/Phrases

Search In:

Publication Years