- Title
- Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage
- Creators
- Gábor Márk Somfai - Department of Ophthalmology, Faculty of Medicine Semmelweis University, Budapest, HungaryErika Tátrai - Department of Ophthalmology, Faculty of Medicine Semmelweis University, Budapest, HungaryLenke Laurik - Department of Ophthalmology, Faculty of Medicine Semmelweis University, Budapest, HungaryBoglárka E Varga - Department of Ophthalmology, Faculty of Medicine Semmelweis University, Budapest, HungaryVera Ölvedy - Department of Ophthalmology, Faculty of Medicine Semmelweis University, Budapest, HungaryWilliam E Smiddy - Miller School of Medicine, Bascom Palmer Eye Institute, University of Miami, Miami, Florida 33136 USARobert Tchitnga - Faculty of Science, Department of Physics, University of Dschang, Dschang, CameroonAnikó Somogyi - 2nd Department of Internal Medicine, Faculty of Medicine Semmelweis University, Budapest, HungaryDelia Cabrera DeBuc - Miller School of Medicine, Bascom Palmer Eye Institute, University of Miami, Miami, Florida 33136 USA
- Publication Details
- BMC bioinformatics, Vol.15(1), pp.295-295
- Publisher
- BioMed Central; London
- Academic Unit
- Miller School of Medicine; UMMG Department of Ophthalmology
- Language
- English
- Resource Type
- Journal article
- PMID
- 25178846
- PMCID
- PMC4261615
- Record Identifier
- 991031576969602976
Journal article
Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage
BMC bioinformatics, Vol.15(1), pp.295-295
2014-09-01
PMCID: PMC4261615
PMID: 25178846
Metrics
11 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- International collaboration
- Citation topics
- 4 Electrical Engineering, Electronics & Computer Science
- 4.17 Computer Vision & Graphics
- 4.17.1752 Retinal Images
- Web Of Science research areas
- Biochemical Research Methods
- Biotechnology & Applied Microbiology
- Mathematical & Computational Biology
- ESI research areas
- Computer Science
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Source: InCites