/AI-assisted Real-time Surgical Hyperspectral Image Analysis

AI-assisted Real-time Surgical Hyperspectral Image Analysis

PhD - Gent | More than two weeks ago

Help surgeons save lives using cutting-edge hyperspectral imaging technology

Hyperspectral imaging (HSI) is an emerging biomedical imaging modality, which makes use of spectral signatures to identify specific substances, such as the measurement of tissue oxygenation, detection of tumors, and perfusion quantification in a non-invasive way. The success of laparoscopic surgical procedures depends to a great extent on good tissue oxygenation (anastomotic leakage, which occurs in approximately 1 of 6 patients and carries up to 28% mortality rate) and the existing techniques are not able to assess whole tissue oxygenation during surgery. Perfusion imaging proves critical in surgeries involving blood vessel manipulation such as Coronary Artery Bypass Grafting (CABG) and oxygenation measurements can accurately detect dead heart tissue, which is all achievable in a non-invasive way using HSI, unlike the current state-of-the-art methods which are invasive and cumbersome. Experiments conducted in small animal surgeries focused on improving tissue oxygenation and perfusion of the liver (for small dogs), show a clear benefit of using HSI-based non-invasive imaging compared to the state-of-the-art method invasive methods.

Both open-body and laparoscopic HSI-guided surgery require near-to-real-time processing in order to provide feedback to the physicians and help guide the surgical procedure and prognose the outcome. Therefore, accurate quantification models for tissue oxygenation measurements, perfusion measurements, tumor and critical structure detection, and image analysis are of essential importance.

The IMEC-Solutions group has vast experience in the development of HSI sensors and cameras for a wide variety of application fields (agriculture, machine vision, medicine, remote sensing, etc.). The Image Processing and Interpretation group of IMEC has been working on a number of biomedical and medical image processing and analysis applications and has long-standing experience in the field. The Experimental Surgery Research group of Ghent University Hospital (the clinical partner) focuses on small and large animal models of colorectal and ovarian cancer and has considerable experience with the design, GCP-compliant execution, and analysis of investigator-driven clinical trials with translational research endpoints. Soft Tissue Surgery group (Small Animal Department) of the Faculty of Veterinary Medicine at Ghent University conducts clinical scientific research related to small animals of multidisciplinary character. International collaboration on this topic includes the Institute of Cardiovascular Diseases in Sremska Kamenica (Serbia), focusing on research in cardiovascular surgery.

We are looking for a motivated Ph.D. Candidate who is interested in pushing the HSI technology to clinical practice. You will: (1) conduct experiments to design the optimal HSI setup for various surgical procedures (open-body and laparoscopic in-vivo imaging) (2) develop novel image processing and analysis methods using AI-based tissue modeling, segmentation, and classification to allow for efficient tumor detection, critical structure identification, tissue oxygenation and perfusion measurements and (3) validate the whole setup on 3-step clinical validation including blood samples, animal and patient studies.

Surgical HSI

Required background: Computer Science or equivalent

Type of work: 70% modeling, 20% experimental, 10% literature

Supervisor: Hiep Luong

Co-supervisor: Wouter Charle

Daily advisor: Danilo Babin

The reference code for this position is 2024-024. Mention this reference code on your application form.

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