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Image-based retrieval system and computer-aided diagnosis system for renal cortical scintigraphy images
Date
2008-02-19
Author
Mumcuoglu, Erkan
Nar, Fatih
Ugur, Oemer
BOZKURT, MURAT FANİ
Aslan, Mehmet
Metadata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
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Cortical renal (kidney) scintigraphy images are 2D images (256x256) acquired in three projection angles (posterior, right-posterior-oblique and left-posterior-oblique). These images are used by nuclear medicine specialists to examine the functional morphology of kidney parenchyma. The main visual features examined in reading the images are: size, location, shape and activity distribution (pixel intensity distribution within the boundary of each kidney). Among the above features, activity distribution (in finding scars if any) was found to have the least interobserver reproducibility. Therefore, in this study, we developed an image-based retrieval (IBR) and a computer-based diagnosis (CAD) system, focused on this feature in particular. The developed IBR and CAD algorithms start with automatic segmentation, boundary and landmark detection. Then, shape and activity distribution features are computed. Activity distribution feature is obtained using the acquired image and image set-statistics of the normal patients. Active Shape Model (ASM) technique is used for more accurate kidney segmentation. In the-training step of ASM, normal patient images are used. Retrieval performance is evaluated by calculating precision and recall. CAD performance is evaluated by specificity and sensitivity. To our knowledge, this paper is the first IBR or CAD system reported in the literature on renal cortical scintigraphy images.
Subject Keywords
CAD
,
Renal cortical scintigraphy
,
Active shape model
,
Content based image retrieval;
URI
https://hdl.handle.net/11511/68077
DOI
https://doi.org/10.1117/12.770880
Collections
Graduate School of Informatics, Conference / Seminar