About Houda
Docteur en Vision par Ordinateur (Rennes 1) et diplômée en Biométrie (UPEC), je suis Enseignante-Chercheuse passionnée par le traitement de l'image/image médicale. Mon expertise s'appuie sur la réalisation de plusieurs dizaines de projets techniques en Vision Artificielle, menés tant dans le cadre de mes recherches doctorales que de mes enseignements universitaires.
Spécialiste du Deep Learning, je maîtrise l'implémentation de solutions de pointe pour la segmentation, la détection et l'analyse d'images médicales. Mon profil académique me permet d'aborder chaque projet avec une rigueur scientifique absolue, garantissant des algorithmes précis et optimisés.
Ce que j'apporte : Une capacité éprouvée à concevoir des architectures IA complexes et à transformer des problématiques théoriques en prototypes fonctionnels et performants.
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As a University Professor with a PhD in Computer Vision from Rennes 1 and a background in Biometrics (UPEC Paris), I offer deep technical expertise in AI-driven image/medical images analysis.
Throughout my academic and research career, I have developed dozens of Computer Vision projects, mastering the end-to-end pipeline of Deep Learning—from architectural design to the final implementation of segmentation and detection models. I specialize in the high-stakes field of medical imaging, where precision and scientific validation are paramount.
My Approach: I leverage my pedagogical and research background to deliver code and models that are not only high-performing but also grounded in rigorous methodology. I excel at taking complex medical datasets and building robust, automated analysis systems
English
Native or bilingual
French
Native or bilingual
Arabic
Native or bilingual
Can work on-site
Rennes (up to 50km)
Experience
- MUST UniversityAssistant professor– Computer ScienceSeptember 2024 - Today (1 year and 9 months)Tunis, TunisiaDeliver undergraduate and master's courses in computer science and AI. Supervise internships projects.
- Université de MontpellierprofesseurDecember 2022 - August 2023 (8 months)Taught Algorithms and Python Programming for the Preparatory Cycle.Taught Python programming and UML for the Engineering Cycle.Supervised multiple student group projects (undergraduate & engineering level).Served as jury member for engineering and undergraduate thesis defenses.Prepared exercises, assignments, and evaluations ensuring rigorous academic standards.
- Therenva© & LTSI Laboratory – University of Rennes 1PhD ResearcherApril 2018 - December 2021 (3 years and 8 months)Rennes, FranceDeveloped an AI-driven intraoperative guidance strategy to simplify catheter navigation and improve procedural accuracy in liver radioembolization.Created image processing pipelines for rigid 2D/2D and 2D/3D registration between preoperative CTA and intraoperative fluoroscopy.Proposed a three-step guidance workflow:a.Assistance for celiac trunk accessb.Assistance for injection site localizationc.Automatic reproduction of the injection site during treatmentDesigned and implemented real-time medical tool detection using deep convolutional neural networks for fluoroscopic sequences.Investigated respiratory-induced hepatic motion and introduced dynamic 3D vessel overlay for fluoroscopic guidance.Conducted extensive clinical dataset acquisition, annotation, algorithm validation, and prototype evaluation in collaboration with radiologists at Eugène Marquis Cancer Center.Participated in approximately 10 interventional radiology procedures, working closely with clinical teams.Published peer-reviewed articles and presented research at international conferences.
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Education
- PhD inTherenva© Company & LTSI Laboratory – University of Rennes2021Developed an AI-driven intraoperative guidance strategy to simplify catheter navigation and improve procedural accuracy in liver radioembolization. Created image processing pipelines for rigid 2D/2D and 2D/3D registration between preoperative CTA and intraoperative fluoroscopy. Proposed a three-step guidance workflow: a.Assistance for celiac trunk access b.Assistance for injection site localization c.Automatic reproduction of the injection site during treatment Designed and implemented real-time medical tool detection using deep convolutional neural networks for fluoroscopic sequences. Investigated respiratory-induced hepatic motion and introduced dynamic 3D vessel overlay for fluoroscopic guidance. Conducted extensive clinical dataset acquisition, annotation, algorithm validation, and prototype evaluation in collaboration with radiologists at Eugène Marquis Cancer Center. Participated in approximately 10 interventional radiology procedures, working closely with clinical teams. Published peer-reviewed articles and presented research at international conferences.
- Master's Degree inUniversity of Paris-Est Créteil (UPEC)2017Master's Degree in biometrics. Final project in LIRMM, Montpellier: Development of a system for tracking fish in underwater videos using CNNs based on deep learning, implemented with MATLAB, Python, and C++, OpenCV
Certifications
- International Congress on Computer Assisted Radiology and SurgeryInternational Congress on Computer Assisted Radiology and Surgery2019
- Certificate of Attendance – IEEE EMBS International Summer School on Biomedical ImagingCertificate of Attendance – IEEE EMBS International Summer School on Biomedical Imaging2019