Model-based processing scheme for quantitative 4-D cardiac MRI analysis

Stalidis, George/ Pappas, Costas/ Dimitriadis, Alexis/ Efstratiadis, Sotiris/ Maglaveras, Nicos/ Σταλίδης, Γιώργος/ Παππάς, Κωνσταντίνος/ Δημητριάδης, Αλέξης/ Ευστρατιάδης, Σωτήρης/ Μαγκλαβέρας, Νίκος


Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Keywords: Medical Image Processing;Biomedical MRI;Cardiology;Image Classification;Neural Nets;Parameter Estimation;Image Segmentation;Learning (artificial intelligence)
Issue Date: Mar-2002
Publisher: IEEE
Citation: Journal: Information Technology in Biomedicine, vol.6, no.1, 2002
Maglaveras, Efstratiadis, Dimitriadis,Pappas,Stalidis, N. (2002). Model-based processing scheme for quantitative 4-D cardiac MRI analysis. Διαθέσιμο σε: http://ieeexplore.ieee.org/xpl/abstractAuthors.jsp?tp=&arnumber=992164&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D992164 (Ανακτήθηκε 8 Ιουλίου, 2015).
Abstract: Presents an integrated model-based processing scheme for cardiac magnetic resonance imaging (MRI), embedded in an interactive computing environment suitable for quantitative cardiac analysis, which provides a set of functions for the extraction, modeling, and visualization of cardiac shape and deformation. The methods apply 4-D processing (three spatial and one temporal) to multiphase multislice MRI acquisitions and produce a continuous 4-D model of the myocardial surface deformation. The model is used to measure diagnostically useful parameters, such as wall motion, myocardial thickening, and myocardial mass measurements. The proposed model-based shape extraction method has the advantage of integrating local information into an overall representation and produces a robust description of cardiac cavities. A learning segmentation process that incorporates a generating-shrinking neural network is combined with a spatiotemporal parametric modeling method through functional basis decomposition. A multiscale approach is adopted, which uses at each step a coarse-scale model defined at the previous step in order to constrain the boundary detection. The main advantages of the proposed methods are efficiency, lack of uncertainty about convergence, and robustness to image artifacts.
Description: Δημοσιεύσεις μελών--ΣΔΟ--Τμήμα Εμπορίας και Διαφήμισης,2002
URI: http://195.251.240.227/jspui/handle/123456789/4617
ISSN: 1089-7771
Other Identifiers: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=992164&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D992164
10.1109/4233.992164
Item type: other
Submission Date: 2018-02-27T18:19:37Z
Item language: el
Item access scheme: free
Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Appears in Collections:Δημοσιεύσεις σε Περιοδικά

Files in This Item:
There are no files associated with this item.



 Please use this identifier to cite or link to this item:
http://195.251.240.227/jspui/handle/123456789/4617
  This item is a favorite for 0 people.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.