Journal
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
Volume 43, Issue -, Pages 36-43Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2015.02.010
Keywords
CARS; Image analysis; Texture analysis; Perceptron algorithm
Funding
- European Union via 'Europaischer Fonds fur Regionale Entwicklung (EFRE)'
- 'Thuringer Ministerium fur Bildung, Wissenschaft und Kultur' (TMBWK) [B578-06001, 14.90 HWP, B714-07037]
- European Network of Excellence p4l (photonics4life)
- German Federal Ministry for Science and Education (BMBF) MediCARS [FKZ: 13N10774]
- German Federal Ministry for Science and Education (BMBF) Fiber Health Probe [FKZ: 13N12525]
- Abbe School of Photonics Scholarship
- German Optics & Photonics industry
- Federal Ministry of Education and Research
- County of Thuringia
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Coherent anti-Stokes Raman scattering (CARS) microscopy is a powerful tool for fast label-free tissue imaging, which is promising for early medical diagnostics. To facilitate the diagnostic process, automatic image analysis algorithms, which are capable of extracting relevant features from the image content, are needed. In this contribution we perform an automated classification of healthy and tumor areas in CARS images of basal cell carcinoma (BCC) skin samples. The classification is based on extraction of texture features from image regions and subsequent classification of these regions into healthy and cancerous with a perceptron algorithm. The developed approach is capable of an accurate classification of texture types with high sensitivity and specificity, which is an important step towards an automated tumor detection procedure. (C) 2015 Elsevier Ltd. All rights reserved.
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