A comprehensive review of optic disc segmentation methods in adult and pediatric retinal images: from conventional methods to artificial intelligence (CR-ODSeg-AP-CM2AI)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10256890" target="_blank" >RIV/61989100:27240/25:10256890 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/article/10.1007/s10462-024-11056-y" target="_blank" >https://link.springer.com/article/10.1007/s10462-024-11056-y</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10462-024-11056-y" target="_blank" >10.1007/s10462-024-11056-y</a>
Alternative languages
Result language
angličtina
Original language name
A comprehensive review of optic disc segmentation methods in adult and pediatric retinal images: from conventional methods to artificial intelligence (CR-ODSeg-AP-CM2AI)
Original language description
This review, titled CR-ODSeg-AP-CM2AI (Comprehensive Review of Optic Disc Segmentation in Adult and Pediatric Retinal Images: From Conventional Methods to Artificial Intelligence), explores optic disc segmentation techniques for adult and pediatric retinal images. It emphasizes the clinical implications of these techniques in diagnosing and monitoring retinal diseases across diverse populations. We systematically categorize each segmentation method, comparing traditional approaches with advancements in artificial intelligence (AI) to highlight innovative hybrid techniques that enhance segmentation accuracy and efficiency. This review also discusses evaluation metrics and the use of larger datasets to provide insights into the effectiveness and robustness of these methods.
Czech name
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Czech description
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Classification
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Artificial Intelligence Review
ISSN
0269-2821
e-ISSN
1573-7462
Volume of the periodical
58
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
66
Pages from-to
nestránkováno
UT code for WoS article
001412339600001
EID of the result in the Scopus database
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