Related Experiment Video
Updated: Oct 17, 2025
Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
Published on: August 18, 2022
Improving dermal level images from reflectance confocal microscopy using wavelet-based transformations and adaptive
Katharine L Hanlon1,2, Grace Wei2, Jonathan Braue1
1Department of Cutaneous Oncology, Cleveland Clinic Indian River Hospital, Scully Welsh Cancer Center, Vero Beach, Florida, USA.
Objectives:
Reflectance confocal microscopy (RCM) generates scalar image data from serial depths in the skin, allowing in vivo examination of cellular features. The maximum imaging depth of RCM is approximately 250 µm, to the papillary dermis, or upper reticular dermis. Frequently, important diagnostic features are present in the dermis, hence improved visualization of deeper levels is advantageous.
Methods:
Low contrast and noise in dermal images were improved by employing a combination of wavelet-based transformations and contrast-limited adaptive histogram equalization.
Results:
Preserved details, noise reduction, increased contrast, and feature enhancement were observed in the resulting processed images.
Conclusions:
Complex and combined wavelet-based enhancement approaches for dermal level images yielded reconstructions of higher quality than less sophisticated histogram-based strategies. Image optimization may improve the diagnostic accuracy of RCM, especially for entities with dermal findings.
