Abstract
The early detection of skin cancer not only enhances survival rates but also facilitates less costly and more effective treatments, often minimizing the impact on patients' quality of life. This project proposal stems from the applicant's four years of doctoral research focused on utilizing infrared thermography for characterizing skin cancer lesions. Active infrared thermography is a non-invasive diagnostic technique that utilizes infrared radiation to measure skin temperature, enabling the detection of temperature changes and distribution on the human body's surface. Widely utilized in medical applications for decades, active thermography proves particularly effective in identifying skin cancer due to the heightened metabolic activity and angiogenesis associated with malignant cells. In the case of melanoma, it is believed to exhibit a higher temperature than the surrounding healthy skin, making it a prominent target for infrared imaging. Different skin tumor types, such as basal cell carcinoma, may exhibit distinct thermal signatures, allowing thermography to differentiate between various skin cancer types. Research indicates that thermal infrared imaging can reveal new blood vessels and chemical changes linked to tumor development and growth. Through previous research efforts, a prototype has been devised based on thermography to assess the subcutaneous area and depth of skin lesions before their removal. Collaborating with the Zurich School of Engineering, the prototype underwent preliminary measurements on a small patient cohort, yielding highly promising results. However, a comprehensive validation study with a larger patient cohort is yet to be conducted, a gap this project aims to address. The proposed research methodology seeks to validate this innovative technique and compile a substantial dataset of thermography data on skin lesions. Leveraging this dataset, machine learning algorithms will be developed, trained, and evaluated to characterize lesions accurately and discern subcutaneous areas and depths.
Researcher(s)
Research team(s)
Project type(s)