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- 034009

Subject Categories

Dermatology and Venereal Diseases

DOI

10.1117/1.1925650

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4/5/2022 7