| Binary coordinate ascent: An efficient optimization technique for feature subset selection for machine learning A Zarshenas, K Suzuki Knowledge-Based Systems 110, 191-201, 2016 | 53 | 2016 |
| 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, 89-97, 2018 | 45 | 2018 |
| 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 14th international workshop on breast imaging (IWBI 2018) 10718, 291-300, 2018 | 8 | 2018 |
| Deep neural network convolution for natural image denoising A Zarshenas, K Suzuki 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2018 | 5 | 2018 |
| A novel depth estimation method for uncalibrated stereo images M Loghman, A Zarshenas, KH Chung, Y Lee, J Kim 2014 International SoC Design Conference (ISOCC), 186-187, 2014 | 5 | 2014 |
| Massive-Training Support Vector Regression With Feature Selection in Application of Computer-Aided Detection of Polyps in CT Colonography J Xu, A Zarshenas, Y Chen, K Suzuki Emerging Developments and Practices in Oncology, 153-190, 2018 | 4 | 2018 |
| Introduction to Binary Coordinate Ascent: New Insights into Efficient Feature Subset Selection for Machine Learning A Zarshenas, K Suzuki Artificial Intelligence in Decision Support Systems for Diagnosis in Medical …, 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 |
| Reduction in training time of a deep learning model in detection of lesions in CT N Makkinejad, N Tajbakhsh, A Zarshenas, A Khokhar, K Suzuki Medical Imaging 2018: Computer-Aided Diagnosis 10575, 875-885, 2018 | 2 | 2018 |
| Fast depth estimation using spatio-temporal prediction for stereo-based pedestrian detection A Zarshenas, M Mesmakhosroshahi, J Kim 2015 Visual Communications and Image Processing (VCIP), 1-4, 2015 | 2 | 2015 |
| 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 |
| Deep Learning for Image Processing with Applications to Medical Imaging A Zarshenas Illinois Institute of Technology, 2019 | | 2019 |
| Jianwu Xu A Zarshenas, Y Chen, K Suzuki Emerging Developments and Practices in Oncology, 153, 2018 | | 2018 |
| Improvement of human feature descriptors for pedestrian detection M Zarshenas Illinois Institute of Technology, 2015 | | 2015 |
Kenji SuzukiProfessor of Biomedical AI, Institute of Innovative Research, Tokyo Institute of TechnologyZweryfikowany adres z m.titech.ac.jp
