2025-2028

Of the 5 projects awarded in 2025:

• 2 projects awarded with the AI Cluster ENACT through a joint call for PhD proposals
• 1 project awarded in affiliation with the BETA (Bureau of Theoretical and Applied Economics) laboratory, marking the second awarded PhD project with the BETA since the start of HealthTech
• 1 project awarded as the first co-funded PhD project with a company (Image-Guided Therapy
• 2 projects (of which one is an ENACT co-funded project) awarded as the continuation of PhD projects completed in 2024 from the 2021 call (E. Martins Seromenho, V. Scarponi)

Of the PhD candidates:

• 2 are graduates of the HealthTech Master's
• 1 is a graduate of Télécom Physique Strasbourg and interned on the awarded PhD project
• 1 is a graduate of the FSEG, the Department of Economics and Management at the University of Strasbourg
• 1 is an external candidate

The precise navigation of catheters during endovascular procedures is essential for the treatment of various cardiovascular diseases. To reduce the duration of these procedures and minimize patient exposure to X-rays and contrast agents, we aim to develop control algorithms for the automatic navigation of both catheters and guidewires. Our approach integrates real-time catheter simulation with 3D shape measurements and deep reinforcement learning techniques.

• PhD student: Ahmed Moustafa
• Supervisors: S. Cotin (INRIA), F. Nageotte (ICube)

Innovation in healthcare encompasses not only technological advancement but also social innovation. This is exemplified by the role of informal caregivers and the entrepreneurial dynamics around this subject. By analysing the complex interplay between technological and social innovation, this research aims to shape the future of innovation in healthcare, where innovation is driven by both technological advancements and social transition.

• PhD student: Natalie Flämig
• Supervisor: V. Schaeffer (BETA), G. Facchi (Opencare Lab)

Images from FFOCT are very similar to histological imaging but without the need to cut or stain the
tissues. Nevertheless, despite very good results, FFOCT still lack of specificity. One way to tackle this
limitation is to use the cellular motility as an imaging contrast (indicator of the cellular type), this
method is call dynamic FFOCT. The objective of this thesis is to adapt the dynamic FFOCT approach to
SO-FF-OCT in order to perform real-time, in vivo dynamic FFOCT images and to apply this approach to artificial skin in culture and grafted.

• PhD student: Julie Blon
• Supervisors: A. Nahas (ICube), S. Facca (HUS, ICube)

Transcranial focused ultrasound (tFUS) noninvasively targets deep brain structures for complex treatments such as tremor reduction in Parkinson’s Disease, blood-brain barrier disruption for targeted drug delivery and neuromodulation for epilepsy. This project will develop innovative methods to precisely assess and control the focal spot within the brain by using adaptive nonlinear optimization of ultrasonic waves in the complex, heterogeneous intracranial environment.

• PhD student: Louis Joly
• Supervisors: E. Van Houten (ICube), J. Vappou (ICube)

IKONA aims to develop a multimodal and explainable artificial intelligence system for diagnosing rare diseases with oro-dental anomalies. By integrating heterogeneous data (clinical texts, imaging,
keywords and genetic data) and leveraging neurosymbolic approaches, the system will enable the
identification of these anomalies, provide detailed explanations of their causes, and establish links
between clinical manifestations and genomic data. The project is designed to address the challenges of diagnosing rare diseases by supporting specialists with an innovative tool tailored to their needs.

• PhD student: Socrates Onyando
• Supervisors: C. Wemmert (ICube), A. Ayadi (ICube), A. Bloch-Zupan (HUS)