Kevin T. Chen

发表

Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning

Osama Sabri, Greg Zaharchuk, Kevin T. Chen, 2020, European Journal of Nuclear Medicine and Molecular Imaging.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity

Guobao Wang, Ciprian Catana, Kuang Gong, 2018, IEEE Transactions on Medical Imaging.

Probabilistic atlas-based segmentation of combined T1-weighted and DUTE MRI for calculation of head attenuation maps in integrated PET/MRI scanners.

Kevin T. Chen, R. Gollub, T. Batchelor, 2014, American journal of nuclear medicine and molecular imaging.

An SPM8-Based Approach for Attenuation Correction Combining Segmentation and Nonrigid Template Formation: Application to Simultaneous PET/MR Brain Imaging

Kevin T. Chen, S. Fürst, A. Hansen, 2014, The Journal of Nuclear Medicine.

Ultra-Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

John M Pauly, Junshen Xu, Enhao Gong, 2019, Radiology.

MR‐assisted PET motion correction in simultaneous PET/MRI studies of dementia subjects

Ciprian Catana, Bradford C. Dickerson, Kevin T. Chen, 2018, Journal of Magnetic Resonance Imaging.

New SPM8-based MRAC method for simultaneous PET/MR brain images: comparison with state-of-the-art non-rigid registration methods

Ciprian Catana, David Izquierdo-Garcia, Stefan Förster, 2014, EJNMMI Physics.

On the accuracy and reproducibility of a novel probabilistic atlas-based generation for calculation of head attenuation maps on integrated PET/MR scanners

Ciprian Catana, David Izquierdo-Garcia, Kevin T. Chen, 2016, European Journal of Nuclear Medicine and Molecular Imaging.

Multi-task Deep Learning for Cerebrovascular Disease Classification and MRI-to-PET Translation

Kevin T. Chen, Moss Y. Zhao, G. Davidzon, 2022, 2022 26th International Conference on Pattern Recognition (ICPR).

Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss.

Greg Zaharchuk, Kevin T. Chen, John Pauly, 2019, Medical physics.

Assessment of motion and model bias on the detection of dopamine response to behavioral challenge

Finnegan J. Calabro, Kevin T. Chen, J. Mandeville, 2022, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

Anatomically-aided PET reconstruction using the kernel method

Guobao Wang, Ciprian Catana, Jinyi Qi, 2016, Physics in medicine and biology.

True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation

Kevin T. Chen, G. Davidzon, G. Zaharchuk, 2021, European Journal of Nuclear Medicine and Molecular Imaging.

Predicting FDG‐PET Images From Multi‐Contrast MRI Using Deep Learning in Patients With Brain Neoplasms

Kevin T. Chen, G. Davidzon, G. Zaharchuk, 2023, Journal of magnetic resonance imaging : JMRI.

An Efficient Approach to Perform MR-Assisted PET Data Optimization in Simultaneous PET/MR Neuroimaging Studies

Ciprian Catana, Kuang Gong, David Izquierdo-Garcia, 2018, The Journal of Nuclear Medicine.

Reproducibility of cerebrovascular reactivity measurements: A systematic review of neuroimaging techniques*

Kevin T. Chen, Moss Y. Zhao, G. Zaharchuk, 2021, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity

Kevin T. Chen, J. Qi, C. Catana, 2018, IEEE Transactions on Medical Imaging.

Ultra-Low-Dose 18F-Florbetaben Amyloid PET Imaging Using Deep Learning with Multi-Contrast MRI Inputs.

Kevin T. Chen, J. Pauly, M. Greicius, 2020, Radiology.