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Analysis System For Early - Stage Diagnostic Of Skin Tumors

Technology Overview

The accuracy of clinical diagnosis of cutaneous melanoma is only 60% and strongly depends on the experience of the dermatologist performing the study. The use of non-visual imaging devices in clinical dermatological practice increases the accuracy of the diagnosis of melanoma (malignant skin tumor of melanocyte origin) by 10-27%.

The proposed automatic quantitative parameter evaluation and decision support system simultaneously analyzes the data recorded by several different methods (spectrophotometry, ultrasound images and data), evaluates not only the skin surface tissues and their changes, but also the depth of tumor penetration into those tissues. It helps to make a faster and better decision on the diagnosis (malignant or non-malignant tumor), to select the next tests and to plan treatment tactics.

We are seeking companies for R&D collaboration to further improve the system or for companies keen to license this technology.

Technology Features, Specifications and Advantages

Our invention includes

  • A software with post processing algorithms to view and analyze ultrasound and spectrophotometer images.
  • An AI algorithm which performs detection of skin melanoma using a set of extracted quantitative parameters automatically.

Our software and AI algorithm are compatible with most commercialize ultrasound equipment and spectrophotometers. The system is configured to provide dermatoscopic images of the distribution of hemoglobin, collagen, epidermis, and dermal melanin in the skin and find the deepest damage to the skin structure.

We have currently achieved more than 95% accuracy for our system.

Potential Applications

The system is intended for doctors of various specialties (for example, dermatologists, plastic surgeons, family doctors) and/or other medicine specialists.

Customer Benefit

  • Prompt examination of the superficial to prevent deep spread of the skin tumors;
  • Analysis is performed automatically and can be used by less experienced dermatologist or family doctor;
  • Non-invasive, user and patient -friendly solution;
  • Facilitates further choices of treatment steps / procedures.
Contact Person

Julija Kravčenko


Kaunas University of Technology

Technology Category

  • Healthcare
  • Diagnostics, Telehealth, Medical Software & Imaging
  • Infocomm
  • Artificial Intelligence, Healthcare ICT

Technology Readiness Level


Automatic system, Melanoma, Spectrophotometry, Ultrasound