Location: Dijon - France

Duration: 6 months (negotiable)

Start Date: from January 2025 to March 2025

Supervisor:

Yannick Benezeth (Professor, IMVIA)

Project Description:

Chronic wounds present a significant challenge to healthcare systems worldwide. Their effective monitoring is crucial for optimizing treatment and improving patient outcomes. The French ANR Wound-rPPG project aims to develop a novel, non-invasive, method for monitoring wound healing.

In this internship, we plan to collect a multimodal database of skin tissues and employ advanced techniques to estimate microvascular perfusion on this collected data.

The data collection process will encompass a series of tasks, beginning with participant recruitment and establishing a data acquisition protocol. Multispectral video sequences of skin areas will be captured at various spectral bands, followed by pointwise spectroscopic measurements to obtain diffuse reflectance spectra. These spectra will be registered with the multispectral video data, while a portable ecography device will measure skin layer thickness and major artery locations.

Finally, microvascular perfusion estimations will be validated using existing algorithms developed in the lab [Kam11, Ham22].

[Kam11] Kamshilin et al., "Photoplethysmographic imaging of high spatial resolution, " Biomed. Opt. Express, 2011.

[Ham22] Hammer et al., Camera-based assessment of cutaneous perfusion strength in a clinical setting, Physiological Measurement, 2022.

Responsibilities:

• Acquisition of multispectral video sequences of skin tissues using a custom-developed multispectral acquisition system.
• Participate in the collection of anatomical and optical measurements (e.g., skin layer thickness and reflectance spectra).
• Evaluation of existing algorithms for microvascular perfusion estimation.

Profile:

• Currently pursuing a Master's degree in Biomedical Engineering, Computer Vision, Computer Science, or a related field.
• Strong interest in medical imaging, computer vision and experimental studies.
• Basic understanding of optical techniques, such as spectroscopy.
• Experience with data analysis and programming languages (e.g., MATLAB, Python).

Potential opportunity to extend the internship into a fully funded PhD thesis.

To Apply:

Interested candidates are encouraged to submit their applications, including a CV, a motivation letter and recent transcript to:

Yannick Benezeth: yannick.benezeth@u-bourgogne.fr