Automatic method for quantitative automatic evaluation in dynamic renal scintilography images

Renal insufficiency is one of the most frequent health problems in Brazil and in the world. In some cases, the renal insufficiency symptoms are not easily perceived, and the disease may evolute to a more serious stage. Nuclear medicine is a specialty for human body image acquisition based on the use...

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Bibliographic Details
Published in:Multimedia tools and applications 2017-09, Vol.76 (18), p.19291-19315
Main Authors: dos Santos, Wallas Henrique S., Ataky, Steve Tsham Mpinda, Silva, Aristófanes C., de Paiva, Anselmo C., Gattass, Marcelo
Format: Article
Language:English
Subjects:
Algorithms
Aorta
Computer Communication Networks
Computer Science
Coronary vessels
Creatinine
Data Structures and Information Theory
Image acquisition
Image segmentation
Kidneys
Medical imaging
Multimedia Information Systems
Nuclear medicine
Patients
Quantitative analysis
Radiation
Radioisotopes
Scintigraphy
Special Purpose and Application-Based Systems
Transit time
Transplants & implants
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Summary:Renal insufficiency is one of the most frequent health problems in Brazil and in the world. In some cases, the renal insufficiency symptoms are not easily perceived, and the disease may evolute to a more serious stage. Nuclear medicine is a specialty for human body image acquisition based on the use of radioisotopes for the analysis of some organ functionalities. Renal scintigraphy is an image based examination used for the diagnosing of problems in renal functions. This work presents an automatic method for quantitative analysis based on renal scintigraphy. The proposed methodology is capable of segmenting regions in the image associated with kidney, background, and aorta. Based on parameters obtained from these segmented images, it is possible to compute the glomerular filtration rate, renogram and renal transit time by deconvolution. The result obtained by the methodology were compared with results of a manual analysis made by a specialist, reaching promising results to be used in a clinical use.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-017-4715-9