Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing J Liu, A Zarshenas, A Qadir, Z Wei, L Yang, L Fajardo, K Suzuki
Medical Imaging 2018: Image Processing 10574 (105740F), 2018
45 2018 Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images T Liu, J Liu, Y Ma, J He, J Han, X Ding
Med. Phys., 2020
44 2020 Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB) J Liu, M Kocak, M Supanich, J Deng
Magnetic Resonance Imaging 71, 69-79, 2020
39 2020 Deep learning with noise‐to‐noise training for denoising in SPECT myocardial perfusion imaging Junchi Liu, Yongyi Yang, Miles N. Wernick, P. Hendrik Pretorius, Michael A. King
Medical Physics 48 (1), 156-168, 2020
35 * 2020 Separation of bones from soft tissue in chest radiographs: Anatomy‐specific orientation‐frequency‐specific deep neural network convolution A Zarshenas, J Liu, P Forti, K Suzuki
Medical physics 46 (5), 2232-2242, 2019
25 2019 Neural network convolution (nnc) for converting ultra-low-dose to “virtual” high-dose ct images K Suzuki, J Liu, A Zarshenas, T Higaki, W Fukumoto, K Awai
Machine Learning in Medical Imaging: 8th International Workshop, MLMI 2017 …, 2017
25 2017 Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning J Liu, A Zarshenas, SA Qadir, L Yang, L Fajardo, K Suzuki
Proc. of SPIE Vol 10718 (14th Intl Workshop on Breast Imaging), 1071814-1, 2018
8 2018 Improving detection accuracy of perfusion defect in standard dose SPECT-myocardial perfusion imaging by deep-learning denoising J Liu, Y Yang, MN Wernick, PH Pretorius, PJ Slomka, MA King
Journal of Nuclear Cardiology 29 (5), 2340-2349, 2022
7 2022 Development of computer-aided diagnostic (CADx) system for distinguishing neoplastic from nonneoplastic lesions in CT Colonography (CTC): toward CTC beyond detection K Suzuki, M Zarshenas, J Liu, Y Fan, N Makkinejad, P Forti, AH Dachman
2015 IEEE International Conference on Systems, Man, and Cybernetics, 2262-2266, 2015
7 2015 Observer studies of image quality of denoising reduced-count cardiac single photon emission computed tomography myocardial perfusion imaging by three-dimensional Gaussian post … PH Pretorius, J Liu, KS Kalluri, Y Jiang, JA Leppo, ST Dahlberg, J Kikut, ...
Journal of Nuclear Cardiology 30 (6), 2427-2437, 2023
3 2023 Improving diagnostic accuracy of reduced-dose studies with full-dose noise-to-noise learning in cardiac spect J Liu, Y Yang, MN Wernick, PH Pretorius, MA King
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1173-1176, 2021
3 2021 Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): consolidation, ground-glass opacity (GGO … N Hashimoto, K Suzuki, J Liu, Y Hirano, H MacMahon, S Kido
Medical Imaging 2018: Computer-Aided Diagnosis 10575, 706-712, 2018
3 2018 Quantitative radiology: automated measurement of polyp volume in computed tomography colonography using Hessian matrix-based shape extraction and volume growing ML Epstein, PR Obara, Y Chen, J Liu, A Zarshenas, N Makkinejad, ...
Quantitative Imaging in Medicine and Surgery 5 (5), 673, 2015
3 2015 Image-based motion artifact reduction on liver dynamic contrast enhanced MRI Y Wu, J Liu, GM White, J Deng
Physica Medica 105, 102509, 2023
2 2023 Accounting For Inter-Subject Variations in Deep Learning for Reduced-Dose Studies in Cardiac SPECT J Liu, Y Yang, MN Wernick, PH Pretorius, MA King
2021 IEEE International Conference on Image Processing (ICIP), 2913-2917, 2021
2 2021 Dose-Blind Denoising With Deep Learning in Cardiac Spect J Liu, Y Yang, MN Wernick, PH Pretorius, MA King
2022 IEEE International Conference on Image Processing (ICIP), 1666-1670, 2022
1 2022 Assessment of defect detection in post-filtering and deep learning denoising strategies for reduced dose myocardial perfusion spect employing human and polar map observers PH Pretorius, J Liu, K Kalluri, MA King, B Auer, C Lindsay, A Konik, ...
2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC …, 2021
1 2021 Mixture of deep-learning experts for separation of bones from soft tissue in chest radiographs A Zarshenas, J Liu, P Forti, K Suzuki
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018
1 2018 Mixed N Cai, Q Ye, J Wang, G Cen, J Liu, H Wang, B Wing-Kuen
Signal, Image and Video Processing 12 (1), 133-140, 2018
1 2018 Artifact reduction in brain magnetic resonance imaging (MRI) by means of a dense residual network with K-space blending (DRN-KB) J Liu, J Deng
Medical Imaging 2020: Image Processing 11313, 127-132, 2020
2020 
Kenji SuzukiProfessor of Biomedical AI, Institute of Innovative Research, Tokyo Institute of TechnologyZweryfikowany adres z m.titech.ac.jp
