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Plus grande école de santé de Suisse romande, la HEdS-Genève est la seule à réunir cinq des sept filières du domaine Santé.
Professeur HES ordinaire
Technique en radiologie médicale IR-HEdS
jerome.schmid@hesge.ch
+41 22 558 58 74
Haute école de santé - Genève
Avenue de Champel 47, 1206 Genève, CH
Prof. Jérôme Schmid has been working for many years in medical image processing and understanding, focusing on segmentation and registration. He specialized in physically-based deformable models applied to the modeling of the human musculoskeletal system. Prof. Schmid also explored the combination of deformable models with machine learning, as well as the use of deep learning for computer-assisted diagnosis such as bone fracture recognition in wrist radiographs, Parkinson’s disease detection in SPECT imaging or breast lesion detection in dynamic MRI. Application of artificial intelligence for pedagogic purpose were also explored by his team when devising the AIRx training prototype to simulate the realistic generation of radiographs.
Since 2011, Prof. Schmid and his team at HES-SO have built up a strong expertise in computer-assisted diagnosis and image-guided surgery in several research projects funded by public and private sectors, including the Swiss National Science Foundation, the Swiss Innovation Agency and various swiss foundations.
Orcid
ResearchGate
Scholar.google.fr
Domaine :
Santé
Filière principale :
Technique en radiologie médicale
Intelligence artificielle et médecine assistée par ordinateur
Acquisition et post-traitement des images radiologiques
Systèmes informatisés de santé
Mathématiques appliquées à l'imagerie radiologique
Propriétés de l'image numérique
Reconstruction, traitement et visualisation d'images radiologiques
Etude de cas multimodalités
Méthodologie de recherche
Intelligence artificielle et médecine assistée par ordinateur
Mendes, L. F., Lago, L. P., Egger, C., Schmid, J.
(2025). Characterization of fluid in facial sinuses on post-mortem CT in case of death by drowning : International journal of legal medicine .https://doi.org/10.1007/s00414-025-03493-3
Auteur(s) : Jérôme Schmid
Petit, M. A., Piguet, J., Lokaj, B., Schmid, J., Gaignot, C.
(2025). Learning MRI with ImmeRgaMe : exploring the pedagogical potential of an innovative serious game for radiographer training : Radiography.https://doi.org/10.1016/j.radi.2025.102921
Auteur(s) : Marie-Anaïs Petit, Joël Piguet, Belinda Mataj-Lokaj, Jérôme Schmid, Céline Gaignot
Lokaj, B., Durand de Gevigney, V., Djema, D. A., Zaghir, J., Goldman, J. P., Bjelogrlic, M., Turbe, H., Kinkel, K., Lovis, C., Schmid, J.
(2025). Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification : Computers in biology and medicine.https://doi.org/10.1016/j.compbiomed.2025.109721
Auteur(s) : Belinda Mataj-Lokaj, Jérôme Schmid, Valentin Durand De Gevigney
Lokaj, B., Pugliese, M. T., Kinkel, K., Lovis, C., Schmid, J.
(2024). Barriers and facilitators of artificial intelligence conception and implementation for breast imaging diagnosis in clinical practice: a scoping review : European radiology.https://doi.org/10.1007/s00330-023-10181-6
Auteur(s) : Belinda Mataj-Lokaj, Marie-Therese Pugliese, Jérôme Schmid
Lokaj, B., Pugliese, M.-P., Kinkel, K., Lovis, C., Schmid, J.
(2024). Barriers and facilitators of implementation of AI : Annual Scientific Meeting 2024, European Society of Breast Imaging (EUSOBI).https://www.eusobi.org/congress/
Auteur(s) : Belinda Mataj-Lokaj, Marie-Therese Pugliese, Jérôme Schmid
Zaghir, J., Lokaj, B., Kinkel, K., Djema, A. D., Turbe, H., Bjelogrlic, M., Durand de Gevigney, V., Schmid, J., Lovis, C., Goldman, J. P.
(2024). Efficient clinical information extraction from breast radiology reports in French : Studies in health technology and informatics.https://doi.org/10.3233/SHTI240776
Auteur(s) : Belinda Mataj-Lokaj, Valentin Durand De Gevigney, Jérôme Schmid
Zaghir, J., Lokaj, B., Kinkel, K., Djema, A.-D., Turbé, H., Bjelogrlic, M., Durand De Gevigney, V., Schmid, J., Lovis, C., Goldman, J.-P.
(2024). Efficient clinical information extraction from breast radiology reports in French : Medical Informatics Europe.Auteur(s) : Belinda Mataj-Lokaj, Valentin Durand De Gevigney, Jérôme Schmid
Lokaj, B., Durand de Gevigney, V., Goldman, J.-P., Kinkel, K., Lovis, C., Zaghir, J., Djema, D.-A., Schmid, J.
(2024). Enhancing breast lesion classification by integrating lesion characteristics and clinical data information with ultrafast MRI : European Congress of Radiology 2024 (EPOS).Auteur(s) : Belinda Mataj-Lokaj, Valentin Durand De Gevigney, Jérôme Schmid
Schmid, J., Assassi, L., Chenes, C.
(2023). A novel image augmentation based on statistical shape and intensity models: application to the segmentation of hip bones from CT images : European radiology experimental.https://doi.org/10.1186/s41747-023-00357-6
Auteur(s) : Jérôme Schmid, Christophe Chênes
Chavarria, M. A., Huser, M. , Blanc, S. , Monnin, P. , Schmid, J., Chênes, C. , Assassi, L. , Blanchard, H., Sahli, R., Thiran, J. P. , Salathé, R. , Schönenberger, K.
(2022). X-ray imaging detector for radiological applications adapted to the context and requirements of low- and middle-income countries : Review of Scientific Instruments.https://doi.org/10.1063/5.0077985
Auteur(s) : Jérôme Schmid, Christophe Chênes
