Kijowski, Richard

Deep Learning MR Imaging–based Attenuation Correction for PET/MR Imaging

Liu, F., Jang, H., Kijowski, R., Bradshaw, T., & McMillan, A. B. (2018) · Radiology

Medical Imaging Techniques and ApplicationsAdvanced MRI Techniques and Applications

Cited by 412

Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging

Liu, F., Zhou, Z., Jang, H., Samsonov, A., Zhao, G., & Kijowski, R. (2018) · Magnetic Resonance in Medicine

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 319

Deep learning approach for evaluating knee MR images: achieving high diagnostic performance for cartilage lesion detection.

Liu, F., Zhou, Z., Samsonov, A., Blankenbaker, D., Larison, W., Kanarek, A., Lian, K., Kambhampati, S., & Kijowski, R. (2018) · Radiology

Medical Imaging and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 297

Deep convolutional neural network for segmentation of knee joint anatomy

Zhou, Z., Zhao, G., Kijowski, R., & Liu, F. (2018) · Magnetic Resonance in Medicine

Medical Image Segmentation TechniquesMedical Imaging and Analysis

Cited by 202

Comparison of 1.5- and 3.0-T MR Imaging for Evaluating the Articular Cartilage of the Knee Joint

Kijowski, R., Blankenbaker, D. G., Davis, K. W., Shinki, K., Kaplan, L. D., & De Smet, A. A. (2009) · Radiology

Knee injuries and reconstruction techniquesOsteoarthritis Treatment and Mechanisms

Cited by 170

Vastly Undersampled Isotropic Projection Steady-State Free Precession Imaging of the Knee: Diagnostic Performance Compared with Conventional MR

Kijowski, R., Blankenbaker, D. G., Klaers, J. L., Shinki, K., De Smet, A. A., & Block, W. F. (2009) · Radiology

Knee injuries and reconstruction techniquesAdvanced MRI Techniques and Applications

Cited by 101