Complexity-Based Analysis in Biomedical Image Analysis: A Review

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F29142890%3A_____%2F24%3A00048981" target="_blank" >RIV/29142890:_____/24:00048981 - isvavai.cz</a>
Result on the web
<a href="https://www-worldscientific-com.ezproxy.lib.cas.cz/doi/10.1142/S0218348X24300022" target="_blank" >https://www-worldscientific-com.ezproxy.lib.cas.cz/doi/10.1142/S0218348X24300022</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0218348X24300022" target="_blank" >10.1142/S0218348X24300022</a>

Result language
angličtina
Original language name
Complexity-Based Analysis in Biomedical Image Analysis: A Review
Original language description
This review paper provides an overview of complexity-based analysis techniques in biomedical image analysis, examining their theoretical foundations, computational methodologies, and practical applications across various medical imaging modalities. Through a synthesis of relevant literature, we explore the utility of complexity-based metrics such as fractal dimension, entropy measures, and network analysis in characterizing the complexity of biomedical images (e.g. magnetic resonance imaging (MRI), computed tomography (CT) scans, X-ray images). Additionally, we discuss the clinical implications of complexity-based analysis in areas such as cancer detection, neuroimaging, and cardiovascular imaging, highlighting its potential to improve diagnostic accuracy, prognostic assessment, and treatment outcomes. The review concludes that complexity-based analysis significantly enhances the interpretability and diagnostic power of biomedical imaging, paving the way for more personalized and precise medical care. By elucidating the role of complexity-based analysis in biomedical image analysis, this review aims to provide insights into current trends, challenges, and future directions in this rapidly evolving field.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10200 - Computer and information sciences

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Fractals - Complex Geometry Patterns and Scaling in Nature and Society
ISSN
0218-348X
e-ISSN
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Volume of the periodical
32
Issue of the periodical within the volume
6
Country of publishing house
SG - SINGAPORE
Number of pages
12
Pages from-to
1-12
UT code for WoS article
001276315600001
EID of the result in the Scopus database
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