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| Content Provider | PubMed Central |
|---|---|
| Author | Braverman, Boris Tambasco, Mauro |
| Copyright Year | 2013 |
| Abstract | Fractal geometry has been applied widely in the analysis of medical images to characterize theirregular complex tissue structures that do not lend themselves to straightforward analysis with traditional Euclidean geometry. In this study, we treat the nonfractal behaviour of medical images over large-scale ranges by considering their box-counting fractal dimension as a scale-dependent parameter rather than a single number. We describe this approach in the context of the more generalized Rényi entropy, in which we can also compute the information and correlation dimensions of images. In addition, we describe and validate a computational improvement to box-counting fractal analysis. This improvement is based on integral images, which allows the speedup of any box-counting or similar fractal analysis algorithm, including estimation of scale-dependent dimensions. Finally, we applied our technique to images of invasive breast cancer tissue from 157 patients to show a relationship between the fractal analysis of these images over certain scale ranges and pathologic tumour grade (a standard prognosticator for breast cancer). Our approach is general and can be applied to any medical imaging application in which the complexity of pathological image structures may have clinical value. |
| Related Links | http://dx.doi.org/10.1155/2013/262931 |
| Starting Page | 262931 |
| File Format | |
| ISSN | 17486718 |
| e-ISSN | 17486718 |
| Journal | Computational and Mathematical Methods in Medicine |
| Volume Number | 2013 |
| Language | English |
| Publisher | Hindawi Publishing Corporation |
| Publisher Date | 2013-01-01 |
| Access Restriction | Open |
| Rights Holder | Hindawi Publishing Corporation |
| Subject Keyword | Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Immunology and Microbiology Medicine Biochemistry, Genetics and Molecular Biology Modeling and Simulation |
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