Automatic Robot-Driven 3D Reconstruction System for Chronic Wounds.
Damir FilkoDomagoj MarijanovićEmmanuel Karlo NyarkoPublished in: Sensors (Basel, Switzerland) (2021)
Chronic wounds, or wounds that are not healing properly, are a worldwide health problem that affect the global economy and population. Alongside with aging of the population, increasing obesity and diabetes patients, we can assume that costs of chronic wound healing will be even higher. Wound assessment should be fast and accurate in order to reduce the possible complications, and therefore shorten the wound healing process. Contact methods often used by medical experts have drawbacks that are easily overcome by non-contact methods like image analysis, where wound analysis is fully or partially automated. This paper describes an automatic wound recording system build upon 7 DoF robot arm with attached RGB-D camera and high precision 3D scanner. The developed system presents a novel NBV algorithm that utilizes surface-based approach based on surface point density and discontinuity detection. The system was evaluated on multiple wounds located on medical models as well as on real patents recorded in clinical medical center.
Keyphrases
- wound healing
- deep learning
- machine learning
- healthcare
- type diabetes
- end stage renal disease
- cardiovascular disease
- public health
- chronic kidney disease
- metabolic syndrome
- ejection fraction
- newly diagnosed
- mental health
- insulin resistance
- prognostic factors
- high throughput
- health information
- peritoneal dialysis
- neural network
- patient reported outcomes
- high resolution
- social media
- adipose tissue
- drug induced
- climate change