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Related Experiment Video

Updated: May 14, 2026

Combining Reflectance Confocal Microscopy with Optical Coherence Tomography for Noninvasive Diagnosis of Skin Cancers via Image Acquisition
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Automated skin lesion assessment using mobile technologies and cloud platforms.

Charalampos Doukas1, Paris Stagkopoulos, Chris T Kiranoudis

  • 1University of the Aegean, Samos, Greece. doukas@ aegean.gr

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
Summary

A new smartphone system aids in self-assessing skin lesions. The mobile app identifies and classifies moles, offering initial assessments for conditions like melanoma.

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Area of Science:

  • Dermatology
  • Medical Imaging
  • Mobile Health (mHealth)

Background:

  • Skin cancer, particularly melanoma, poses a significant public health concern.
  • Early detection of skin lesions is crucial for effective treatment and improved patient outcomes.
  • Existing diagnostic methods can be resource-intensive and may not be readily accessible to all individuals.

Purpose of the Study:

  • To develop and evaluate a smartphone-based system for the self-assessment of skin lesions.
  • To create a mobile application capable of acquiring, identifying, and classifying skin moles.
  • To leverage cloud infrastructure for enhanced computational and storage capabilities in lesion analysis.

Main Methods:

  • Development of a mobile application for capturing and analyzing skin lesion images.

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  • Implementation of an image recognition algorithm to identify and classify moles (melanoma, nevus, benign).
  • Utilization of a cloud-based architecture for data storage, processing, and model enhancement.

    • Main Results:

    • The system successfully acquires and stores digital images of skin lesions.
    • The mobile application demonstrates capability in identifying and classifying moles based on severity.
    • Initial evaluations show promising results for the system's utility in preliminary skin lesion assessment.

    Conclusions:

    • The developed smartphone system offers a promising tool for the initial self-assessment of skin lesions.
    • The integration of mobile technology and cloud computing facilitates accessible and flexible dermatological analysis.
    • Further development and validation are warranted to establish the system's clinical efficacy.