Fotouhi, Javad

DeepDRR – A Catalyst for Machine Learning in Fluoroscopy-Guided Procedures

Unberath, M., Zaech, J.-N., Lee, S. C., Bier, B., Fotouhi, J., Armand, M., & Navab, N. (2018) · Lecture Notes in Computer Science

Medical Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 145

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation

Unberath, M., Zaech, J.-N., Gao, C., Bier, B., Goldmann, F., Lee, S. C., Fotouhi, J., Taylor, R., Armand, M., & Navab, N. (2019) · International Journal of Computer Assisted Radiology and Surgery

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 63

Learning to detect anatomical landmarks of the pelvis in X-rays from arbitrary views

Bier, B., Goldmann, F., Zaech, J.-N., Fotouhi, J., Hegeman, R., Grupp, R., Armand, M., Osgood, G., Navab, N., Maier, A., et al. (2019) · International Journal of Computer Assisted Radiology and Surgery

Medical Imaging and AnalysisMedical Image Segmentation Techniques

Cited by 43

Towards clinical translation of augmented orthopedic surgery: from pre-op CT to intra-op x-ray via RGBD sensing

Tucker, E. W., Fotouhi, J., Lee, S. C., Unberath, M., Fuerst, B., Johnson, A., Armand, M., Osgood, G. M., & Navab, N. (2018) · Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications

Augmented Reality ApplicationsAnatomy and Medical Technology

Cited by 19

Extended Capture Range of Rigid 2D/3D Registration by Estimating Riemannian Pose Gradients

Gu, W., Gao, C., Grupp, R., Fotouhi, J., & Unberath, M. (2020) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 16