Bispectral fluorescence imaging combined with texture analysis and linear discrimination for correlation with histopathologic extent of basal cell carcinoma
Journal article, 2005
Fluorescence imaging has been shown to be a potential complement to visual inspection for demarcation of basal cell carcinoma (BCC), which is the most common type of skin cancer. Earlier studies have shown promising results when combining autofluorescence with protoporphyrin IX (Pp IX) fluorescence, induced by application of delta-5-aminolaevulinic acid (ALA). In this work, we have tried to further improve the ability of this technique to discriminate between areas of tumor and normal skin by implementing texture analysis and Fisher linear discrimination (FLD) on bispectral fluorescence data of BCCs located on the face. Classification maps of the lesions have been obtained from histopathologic mapping of the excised tumors. The contrast feature obtained from co-occurrence matrices was found to provide useful information, particularly for the ALA-induced Pp IX fluorescence data. Moreover, the neighborhood average features of both autofluorescence and Pp IX fluorescence were preferentially included in the analysis. The algorithm was trained by using a training set of images with good agreement with histopathology, which improved the discriminability of the validation set. In addition, cross validation of the training set showed good discriminability. Our results imply that FLD and texture analysis are preferential for correlation between bispectral fluorescence images and the histopathologic extension of the tumors.
Adult
Middle Aged
Carcinoma
Humans
Female
Severity of Illness Index
Aged
Sensitivity and Specificity
Basal Cell/classification/*pathology
Spectrometry
Linear Models
Statistical
Skin Neoplasms/classification/*pathology
80 and over
Discriminant Analysis
Statistics
Male
Aged
*Artificial Intelligence
Biological
Reproducibility of Results
Models
Neoplasm Invasiveness
Fluorescence/methods
Image Interpretation
Fluorescence/*methods
Data Interpretation
Computer-Assisted/*methods
Microscopy
Neoplasm Staging/methods
*Algorithms
Computer Simulation
Author
Marica B Ericson
University of Gothenburg
Chalmers, Applied Physics
Bo Stenquist
University of Gothenburg
Arne Rosen
University of Gothenburg
Olle Larkö
University of Gothenburg
J. Uhre
Sahlgrenska University Hospital
C. Strandeberg
Sahlgrenska University Hospital
Arne Rosen
University of Gothenburg
Journal of Biomedical Optics
1083-3668 (ISSN) 15602281 (eISSN)
Vol. 10 3 034009- 034009Subject Categories
Dermatology and Venereal Diseases
DOI
10.1117/1.1925650