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Updated: Aug 8, 2026

Quantitative Visualization and Detection of Skin Cancer Using Dynamic Thermal Imaging
Published on: May 5, 2011
Technical Note: Noninvasive mid-IR fiber-optic evanescent wave spectroscopy (FEWS) for early detection of skin
Svetlana Basov1, Yair Dankner2, Marcelo Weinstein3
1Department of Biomedical Engineering, Tel Aviv University, 30 Haim Levanon, Tel Aviv, 6997801, Israel.
Purpose:
Melanoma is the most lethal of the three primary skin cancers, including also basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), which are less lethal. The accepted diagnosis process involves manually observing a suspicious lesion through a Dermascope (i.e., a magnifying glass), followed by a biopsy. This process relies on the skill and the experience of a dermatologist. However, to the best of our knowledge, there is no accepted automatic, noninvasive, and rapid method for the early detection of the three types of skin cancer, distinguishing between them and noncancerous lesions, and identifying each of them. It is our aim to develop such a system.
Methods:
We developed a fiber-optic evanescent wave spectroscopy (FEWS) system based on middle infrared (mid-IR) transmitting AgClBr fibers and a Fourier-transform infrared spectrometer (FTIR). We used the system to perform mid-IR spectral measurements on suspicious lesions in 90 patients, before biopsy, in situ, and in real time. The lesions were then biopsied and sent for pathology. The spectra were analyzed and the differences between pathological and healthy tissues were found and correlated.
Results:
Five of the lesions measured were identified as melanomas, seven as BCC, and three as SCC. Using mathematical analyses of the spectra of these lesions we were able to tell that all were skin cancers and we found specific and easily identifiable differences between them.
Conclusions:
This FEWS method lends itself to rapid, automatic and noninvasive early detection and characterization of skin cancers. It will be easily implemented in community clinics and has the potential to greatly simplify the diagnosis process.
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