PhD thesis on AI for the segmentation of biomarkers of cardiovascular Risk on 3D-CT

France Life Imaging; Paris; Sur place; EUR 25 000 - 35 000; Plein temps

Résumé du poste

A leading medical imaging company is seeking a candidate for a PhD thesis on AI for the segmentation of cardiovascular biomarkers. The role involves collaboration with Siemens Healthineers and academic centers to develop and validate AI methods in medical imaging. Candidates should have skills in programming (C++, Python), image processing, and a keen interest in cardiac physiology. This position is located in Paris, with involvement in innovative research in healthcare.

Prestations

Remuneration through CIFRE contract

Qualifications

• Skillful in programming and image processing with AI solutions.
• High interest in medical fields, especially heart physiology.

Responsabilités

• Conduct a study on the segmentation of biomarkers using AI methods.
• Participate in manual segmentation of cardiac images.
• Validate conventional methods and collaborate with academic partners.

Connaissances

Object programming (C++, Python)

Image processing including AI solutions

Deep learning and machine learning

Analysis of scientific papers

Formation

Master's degree in a relevant field

Description du poste

Job Title: PhD thesis on AI for the segmentation of biomarkers of cardiovascular Risk on 3D-CT

Context and Mission: Ischemic heart disease, heart failure, and atrial fibrillation are conditions responsible for a very high cardiovascular mortality. The cardiac scanner is an imaging method that is increasingly used in these conditions, even if its analysis remains subjective, sometimes long and dependent on the expertise of the operator. Artificial intelligence methods offer new perspectives in this field because they are potentially fast, partially or even totally automated to quantitatively analyze conventional or complex and new biomarkers by using radiomics concepts. However, all these post-treatment methods in full development today need to be rigorously validated before being used in daily patient care.

The project that we propose to carry out here within the framework of a PhD thesis in medical imaging (University of Paris) is located at the interface of the development and the validation of these new approaches, hence the collaboration between the company Siemens Healthineers which develops these new approaches of AI and an academic center which has a big expertise of cardiac imaging, particularly in scanner because this center carries out more than 2500 cardiac scans per annum since more than 10 years.

To conduct such a study, we propose the following steps:

• Identification and collection of a base of more than 12,000 patients having benefited from a scanner during a hospitalization in our institution during the last 15 years in order to constitute a base of development and deep learning of the various methods of AI (CAVIAR cohort).
• Semi-manual segmentation of cardiac structures of interest with conventional tools proposed by Siemens and/or internal to our research institution for the labeling of various biomarkers, candidate for the estimation of cardiovascular risk (coronary, valvular, aortic calcification, size of the left atrium and other cardiac cavities, mediastinal fat ...).
• Analysis, validation of conventional methods of post-treatment of these biomarkers insufficiently validated by the scanner on these deep learning data bases.
• Participation in the development of AI methods with Siemens and academic partners.
• Analysis and validation of AI methods in the estimation of conventional and new biomarkers brought by the AI method itself.

Location: Assistance Publique Hôpitaux de Paris (APHP) & INSERM PARCC (Paris). The chosen candidate will be enrolled as a CIFRE PhD employee of Siemens Healthineers. Most of the PhD work will take place at HEGP in collaboration with INSERM (PARCC) in Paris and Siemens Healthineers (France & Princeton, USA).

Remuneration: PhD Thesis with a CIFRE contract with Siemens Healthineers

Required Skills: The candidate should be skillful in: object programming (C++, Python), image processing including AI solution (deep learning and machine learning), and analysis of scientific papers. A high interest in the medical fields and heart physiology is expected, since the candidate will participate in manual segmentation of cardiac images dedicated for development and deep learning data sets of AI methods.

Contact: CVs must be sent to [e-mail] & [e-mail]