DocumentCode
1465250
Title
Three-dimensional tumor perfusion reconstruction using fractal interpolation functions
Author
Craciunescu, Oana I. ; Das, Shiva K. ; Poulson, Jean M. ; Samulski, Thaddeus V.
Author_Institution
Dept. of Radiat. Oncology, Duke Univ. Med. Center, Durham, NC, USA
Volume
48
Issue
4
fYear
2001
fDate
4/1/2001 12:00:00 AM
Firstpage
462
Lastpage
473
Abstract
It has been shown that the perfusion of blood in tumor tissue can be approximated using the relative perfusion index determined from dynamic contrast-enhanced magnetic resonance imaging (DE-MRI) of the tumor blood pool. Also, it was concluded in a previous report that the blood perfusion in a two-dimensional (2-D) tumor vessel network has a fractal structure and that the evolution of the perfusion front can be characterized using invasion percolation. Here, the three-dimensional (3-D) tumor perfusion is reconstructed from the 2-D slices using the method of fractal interpolation functions (FIF), i.e., the piecewise self-affine fractal interpolation model (PSAFIM) and the piecewise hidden variable fractal interpolation model (PHVFIM). The fractal models are compared to classical interpolatlon techniques (linear, spline, polynomial) by means of determining the 2-D fractal dimension of the reconstructed slices. Using FIFs instead of classical interpolation techniques better conserves the fractal-like structure of the perfusion data. Among the two FIF methods, PHVFIM conserves the 3-D fractality better due to the cross correlation that exists between the data in the 2-D slices and the data along the reconstructed direction. The 3-D structures resulting from PHVFIM have a fractal dimension within 3%-5% of the one reported in literature for 3-D percolation. It is, thus, concluded that the reconstructed 3-D perfusion has a percolation-like scaling. As the perfusion term from bio-heat equation is possibly better described by reconstruction via fractal interpolation, a more suitable computation of the temperature field induced during hyperthermia treatments is expected.
Keywords
biomedical MRI; fractals; haemorheology; image reconstruction; interpolation; medical image processing; tumours; bioheat equation; blood perfusion; dynamic contrast-enhanced magnetic resonance imaging; fractal interpolation functions; hyperthermia treatments; invasion percolation; model discrete sequences; polynomials; reconstructed direction; reconstructed slices; relative perfusion index; splines; temperature field computation; three-dimensional tumor perfusion reconstruction; Blood; Equations; Fractals; Image reconstruction; Interpolation; Magnetic resonance imaging; Neoplasms; Polynomials; Spline; Two dimensional displays; Animals; Contrast Media; Dogs; Fibrosarcoma; Forelimb; Fractals; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Models, Cardiovascular;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/10.915713
Filename
915713
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