Selective Ultrasound Sensor Networks with AI Algorithms for Early Detection and Monitoring of Breast Cancer
Selective Ultrasound Sensor Networks with AI Algorithms for Early Detection and Monitoring of Breast Cancer
Despite major progress in the understanding of oncogenesis, cancer in general and breast cancer in particular remains one of the greatest public health challenges in the world.
Like other countries, Morocco has paid great interest to activities related to the early diagnosis of breast cancer, in particular by the Cancer Research Institute (IRC), and the Hassan II University Hospital Center in Fez. . This public health issue is also a concern of several national associations and foundations, in particular the Lalla Salma Foundation. Also, the relevance of cancer research no longer needs to be demonstrated.
Several screening techniques are common but only in clinics, such as mammography or MRI. An important alternative to overcome the limitations of these two techniques is ultrasound imaging. Current developments in ultrasound techniques show that ultrasound will play an increasingly important role not only for diagnosis but also for therapy. As for quantitative ultrasound imaging, new practices have emerged. However, these techniques represent a disadvantage since the diagnosis is strongly linked to the mechanical properties of the tissues. An alternative solution, independent of the mechanical properties of the tissues, is currently recommended. This technique has strong potential to distinguish benign tumors from malignant tumors with high precision. To meet these challenges, we propose, as part of this thesis work, to develop a network of innovative sensors composed of a set of very fine trasonic transducers deposited on a flexible substrate in order to detect possible tumors in the breast. . This innovative system can collect, communicate remotely and interpret the information available in real time, thanks to Artificial Intelligence (AI). The device developed will also be able to participate in decision-making.
The association of AI with a device based on ultrasound and their interaction with biological tissues is an emerging discipline that is not yet widespread and that we are proposing as part of a multidisciplinary research project with a National and International dimension.
Eligible are candidates with a Master's degree (Bac+5 or equivalent) in: Physics, Electronics, knowledge of computer science (Python, Matlab) and an appetite for new technologies would be a plus.
Registration procedure
- Application file: Curriculum vitae, cover letter, end-of-studies project, diplomas and transcripts
- Working conditions: The thesis is part of the Al-Khawarizmi Program to support research in the field of Artificial Intelligence and its Applications. It will be carried out as part of a tripartite collaboration between the EPS of the Euromed University of Fez, the ENSAM of the Hassan II University of Casablanca and the INSA of Lyon - Université Lyon 1. Stays in the three establishments are considered
NB: During the thesis period, the doctoral student must devote himself full-time to his research work.
File to be sent to m.zekriti@ueuromed.org before October 8, 2023