Automatic Compartment Modelling and Segmentation for Dynamical Renal Scintigraphies

Publication: Research - peer-reviewArticle in proceedings – Annual report year: 2011

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Time-resolved medical data has important applications in a large variety of medical applications. In this paper we study automatic analysis of dynamical renal scintigraphies. The traditional analysis pipeline for dynamical renal scintigraphies is to use manual or semiautomatic methods for segmentation of pixels into physical compartments, extract their corresponding time-activity curves and then compute the parameters that are relevant for medical assessment. In this paper we present a fully automatic system that incorporates spatial smoothing constraints, compartment modelling and positivity constraints to produce an interpretation of the full time-resolved data. The method has been tested on renal dynamical scintigraphies with promising results. It is shown that the method indeed produces more compact representations, while keeping the residual of fit low. The parameters of the time activity curve, such as peak-time and time for half activity from peak, are compared between the previous semiautomatic method and the method presented in this paper. It is also shown how to obtain new and clinically relevant features using our novel system.
Original languageEnglish
TitleImage Analysis : 17th Scandinavian Conference, SCIA 2011 - Ystad, Sweden, May 2011 - Proceedings
PublisherSpringer
Publication date2011
Pages557-568
DOIs
StatePublished

Conference

Conference17th Scandinavian Conference on Image Analysis (SCIA)
CountrySweden
CityYstad
Period23/05/1127/05/11
Internet addresshttp://www.maths.lth.se/vision/scia2011/
NameLecture Notes in Computer Science
Number6688
ISSN (Print)0302-9743
CitationsWeb of Science® Times Cited: No match on DOI

Keywords

  • Dynamical renal scintigraphies, Compartment modelling, Time-resolved, Medical image analysis, Segmentation
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