WITA
Wound tissue analysis is required for the assessment of the healing of skin wounds. Percentage of the granulation tissue, fibrin and necrosis in the wound, and their change during treatment gives to the medical doctor important information required to decide how to proceed with the wound treatment. WITA implements advanced statistical pattern recognition algorithm to classify individual pixels of the wound image based on wound image colors and classification parameters learned from examples presented to the application during the learning process. Learning process is straightforward. To train WITA an expert shows different parts of the wound images representing different tissue types. Therefore WITA gains knowledge about the wounds directly from the medical expert. WITA has also the capability to propose therapy for the analyzed wound. In addition to the tissue distribution at the wound the user needs to specify the degree of the wound exudation, the depth and the infection. Therapy proposition module is implemented as the fuzzy expert system with 36 rules. Described features makes WITA more advanced than any competitive product at the market.
Highlights:
- Adjust command enables tuning classification parameters for non-standard wound images
- Support for multiple core processors (image analysis is performed at multiple cores)
How to get Wita
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