I-Corps: Developing A 3D Total Body Imaging and Analysis System for Early Detection of Skin Cancer

The broader impact/commercial potential of this I-Corps project is the development of a high-speed and high-precision 3D imaging and skin analysis system. Skin cancer is the most common cancer in the US, with 5.5 million new cases diagnosed in 2019. Research shows that skin cancers are highly treatable if detected early.

Early detection of melanoma saves lives and improves the treatment outcomes by reducing the risk of spreading cancer to other parts of the body. Early detection of nonmelanoma skin cancers minimizes disfigurement and enhances the quality of life and productivity for many patients. The proposed technology may be a new tool for dermatologists and make skin cancer screening more affordable by optimizing the skin evaluation process, supporting teledermatology services, and lowering the overall costs of care.

In addition, there may be other applications of this 3D imaging technology in skin evaluation for cosmetic product development, planning and evaluation of orthodontic and cosmetic procedures, real-time monitoring of radiotherapy patients, facial expression and virtual character creation for movie and virtual reality game productions, and dynamic facial recognition for identity and property protection.

This I-Corps project is based on the development of a high-speed, high-accuracy 3D scanner using multi-wavelength, phase-shifting structured light and an automated skin analysis software using computational conformal geometry. The proposed 3D scanner is designed to capture the human body’s geometry at high speed (up to 180 frames/second) and with high precision (depth resolution of 0.2mm).

Visual identification of skin changes in 2D is impractical. When the viewing angle is altered, the individual’s posture varies, or the surface is deformed, image registration becomes challenging and unstable. The proposed solution is based on extensive research in computational conformal geometry.

Due to the shape-preserving property of conformal mapping, 3D geometric analysis may be accomplished by processing 2D conformal images, which is easier and faster. Independent of their geometric or topological complexities, shapes in real physical worlds may be conformally transformed into one of three canonical shapes (i.e., unit sphere, Euclidean plane, or planar disk).

Because of the uniformity, the design of all geometric algorithms can be simplified, resulting in dramatically improved efficiency, accuracy, and robustness. By combining high-performance 3D scanning and advanced conformal mapping techniques, this foundational platform technology may enable many applications.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.