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Kenji Suzuki 0001
Person information
- affiliation: Tokyo Institute of Technology, Japan
- affiliation (former): University of Chicago, Division of the Biological Sciences, Chicago, IL, USA
Other persons with the same name
- Kenji Suzuki — disambiguation page
- Kenji Suzuki 0002
— University of Tsukuba, Japan
- Kenji Suzuki 0003 — KDDI Research, Inc., KDD R&D Laboratories, Saitama, Japan
- Kenji Suzuki 0004 — Waseda University, Department of Applied Physics, School of Science and Engineering, Tokyo, Japan (and 1 more)
- Kenji Suzuki 0005 — Advanced Communications Co. Ltd., KDD Research and Development Laboratories, Japan
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2020 – today
- 2024
- [j46]Wahyu Rahmaniar
, Kenji Suzuki
, Ting-Lan Lin
:
Auto-CA: Automated Cobb Angle Measurement Based on Vertebrae Detection for Assessment of Spinal Curvature Deformity. IEEE Trans. Biomed. Eng. 71(2): 640-649 (2024) - [c67]Shogo Kodera
, Wahyu Rahmaniar
, Hiroko Oshibe
, Ze Jin
, Takeyuki Watadani
, Osamu Abe
, Kenji Suzuki
:
Super-Efficient Lung Nodule Classification Using Massive-Training Artificial Neural Network (MTANN) Compact Model on LIDC-IDRI Database. IVSP 2024: 213-220 - [i1]Zhipeng Deng, Yuqiao Yang, Kenji Suzuki:
Federated Active Learning Framework for Efficient Annotation Strategy in Skin-lesion Classification. CoRR abs/2406.11310 (2024) - 2023
- [j45]Wongsakorn Preedanan
, Kenji Suzuki
, Toshiaki Kondo, Masaki Kobayashi
, Hajime Tanaka, Junichiro Ishioka, Yoh Matsuoka
, Yasuhisa Fujii, Itsuo Kumazawa:
Urinary Stones Segmentation in Abdominal X-Ray Images Using Cascaded U-Net Pipeline With Stone-Embedding Augmentation and Lesion-Size Reweighting Approach. IEEE Access 11: 25702-25712 (2023) - [j44]Srisopitsawat Pavarut
, Wongsakorn Preedanan, Itsuo Kumazawa, Kenji Suzuki
, Masaki Kobayashi, Hajime Tanaka, Junichiro Ishioka, Yoh Matsuoka
, Yasuhisa Fujii:
Improving Kidney Tumor Classification With Multi-Modal Medical Images Recovered Partially by Conditional CycleGAN. IEEE Access 11: 146250-146261 (2023) - [c66]Kraithep Sirisanwannakul, Nutchanon Siripool, Kenji Suzuki, Waree Kongprawechnon, Jessada Karnjana:
Detection and Correction of Defective Relative Humidity Data Collected from the Greenhouse Environment Using Nested Kalman Filters with Standard Deviation Analysis. APSIPA ASC 2023: 1343-1348 - [c65]Zhipeng Deng, Ze Jin, Kenji Suzuki:
Radiation Dose Reduction in Digital Breast Tomosynthesis by MTANN with Multi-scale Kernels. EMBC 2023: 1-7 - [c64]Ze Jin, Maolin Pang, Yuqiao Yang, Fahad Parvez Mahdi, Tianyi Qu, Ren Sasage, Kenji Suzuki
:
Explaining Massive-Training Artificial Neural Networks in Medical Image Analysis Task Through Visualizing Functions Within the Models. MICCAI (2) 2023: 713-722 - [c63]Kenji Suzuki, Abraham H. Dachman:
ROC-Score-Based Ensemble Training for Multiple Deep Learning Modules in Classification Between Polyps and Non-Polyps in CT Colonography. SMC 2023: 1647-1651 - 2022
- [j43]Wongsakorn Preedanan
, Kenji Suzuki
, Toshiaki Kondo, Masaki Kobayashi
, Hajime Tanaka, Junichiro Ishioka, Yoh Matsuoka
, Yasuhisa Fujii, Itsuo Kumazawa:
Improvement of Urinary Stone Segmentation Using GAN-Based Urinary Stones Inpainting Augmentation. IEEE Access 10: 115131-115142 (2022) - [c62]Kenji Suzuki
:
Small Data Deep Learning for Lung Cancer Detection in CT. BigDataService 2022: 114-118 - [c61]Lingfeng Wang, Jin Qi, Jian Cheng, Kenji Suzuki
:
Action unit detection by exploiting spatial-temporal and label-wise attention with transformer. CVPR Workshops 2022: 2469-2474 - [c60]Yuqiao Yang, Ze Jin, Kenji Suzuki
:
Federated Tumor Segmentation with Patch-Wise Deep Learning Model. MLMI@MICCAI 2022: 456-465 - [c59]Zhipeng Deng, Yuqiao Yang, Kenji Suzuki
, Ze Jin:
FedAL: An Federated Active Learning Framework for Efficient Labeling in Skin Lesion Analysis. SMC 2022: 1554-1559 - 2021
- [j42]Miguel Martínez-García
, Yu Zhang
, Kenji Suzuki
, Yudong Zhang
:
Deep Recurrent Entropy Adaptive Model for System Reliability Monitoring. IEEE Trans. Ind. Informatics 17(2): 839-848 (2021) - [c58]Lingfeng Wang, Shisen Wang, Jin Qi, Kenji Suzuki
:
A Multi-task Mean Teacher for Semi-supervised Facial Affective Behavior Analysis. ICCVW 2021: 3596-3601 - [c57]Muneyuki Sato, Ze Jin, Kenji Suzuki
:
Semantic Segmentation of Liver Tumor in Contrast-enhanced Hepatic CT by Using Deep Learning with Hessian-based Enhancer with Small Training Dataset Size. ISBI 2021: 34-37 - [c56]Maodong Xiang, Ze Jin, Kenji Suzuki
:
Massive-Training Artificial Neural Network (Mtann) With Special Kernel For Artifact Reduction In Fast-Acquisition Mri Of The Knee. ISBI 2021: 1210-1213
2010 – 2019
- 2019
- [j41]Zhenghao Shi
, Huan Hao, Minghua Zhao, Yaning Feng, Lifeng He, Yinghui Wang, Kenji Suzuki
:
A deep CNN based transfer learning method for false positive reduction. Multim. Tools Appl. 78(1): 1017-1033 (2019) - [c55]Yuchen Wang, Ze Jin, Yukiko Tokuda, Yasuto Naoi, Noriyuki Tomiyama, Kenji Suzuki
:
Development of Deep-learning Segmentation for Breast Cancer in MR Images based on Neural Network Convolution. ICCPR 2019: 187-191 - [c54]Miguel Martínez-García, Yu Zhang
, Kenji Suzuki
, Yudong Zhang
:
Measuring System Entropy with a Deep Recurrent Neural Network Model. INDIN 2019: 1253-1256 - [e6]Kenji Suzuki
, Mauricio Reyes, Tanveer F. Syeda-Mahmood, Ben Glocker, Roland Wiest, Yaniv Gur, Hayit Greenspan, Anant Madabhushi:
Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support - Second International Workshop, iMIMIC 2019, and 9th International Workshop, ML-CDS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11797, Springer 2019, ISBN 978-3-030-33849-7 [contents] - 2018
- [c53]Junchi Liu, Amin Zarshenas, Syed Ammar Qadir, Limin Yang
, Laurie Lee Fajardo, Kenji Suzuki
:
Radiation dose reduction in digital breast tomosynthesis (DBT) by means of neural network convolution (NNC) deep learning. IWBI 2018: 1071814 - [c52]Nazanin Makkinejad, Nima Tajbakhsh, Amin Zarshenas, Ashfaq Khokhar, Kenji Suzuki
:
Reduction in training time of a deep learning model in detection of lesions in CT. Medical Imaging: Computer-Aided Diagnosis 2018: 105753V - [c51]Noriaki Hashimoto, Kenji Suzuki
, Junchi Liu, Yasushi Hirano, Heber MacMahon, Shoji Kido
:
Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): Consolidation, ground-glass opacity (GGO), and normal opacity. Medical Imaging: Computer-Aided Diagnosis 2018: 1057536 - [c50]Junchi Liu, Amin Zarshenas, Ammar Qadir, Zheng Wei, Limin Yang
, Laurie Lee Fajardo, Kenji Suzuki
:
Radiation dose reduction in digital breast tomosynthesis (DBT) by means of deep-learning-based supervised image processing. Medical Imaging: Image Processing 2018: 105740F - [c49]Amin Zarshenas, Junchi Liu, Paul Forti, Kenji Suzuki
:
Mixture of Deep-Learning Experts for Separation of Bones from Soft Tissue in Chest Radiographs. SMC 2018: 1321-1326 - [c48]Amin Zarshenas, Kenji Suzuki
:
Deep Neural Network Convolution for Natural Image Denoising. SMC 2018: 2534-2539 - 2017
- [j40]Hieu Trung Huynh
, Ngoc Le-Trong
, Pham The Bao
, Aytek Oto, Kenji Suzuki
:
Fully automated MR liver volumetry using watershed segmentation coupled with active contouring. Int. J. Comput. Assist. Radiol. Surg. 12(2): 235-243 (2017) - [j39]Ayman El-Baz
, Georgy L. Gimel'farb, Kenji Suzuki
:
Machine Learning Applications in Medical Image Analysis. Comput. Math. Methods Medicine 2017: 2361061:1-2361061:2 (2017) - [j38]Yisong Chen, Antoni B. Chan
, Zhouchen Lin, Kenji Suzuki
, Guoping Wang:
Efficient tree-structured SfM by RANSAC generalized Procrustes analysis. Comput. Vis. Image Underst. 157: 179-189 (2017) - [j37]Lifeng He, Xiao Zhao, Bin Yao, Yun Yang, Yuyan Chao, Zhenghao Shi, Kenji Suzuki
:
A combinational algorithm for connected-component labeling and Euler number computing. J. Real Time Image Process. 13(4): 703-712 (2017) - [j36]Kenji Suzuki
, Luping Zhou
, Qian Wang:
Machine learning in medical imaging. Pattern Recognit. 63: 465-467 (2017) - [j35]Nima Tajbakhsh, Kenji Suzuki
:
Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs. Pattern Recognit. 63: 476-486 (2017) - [c47]Kenji Suzuki
, Junchi Liu, Amin Zarshenas, Toru Higaki
, Wataru Fukumoto, Kazuo Awai:
Neural Network Convolution (NNC) for Converting Ultra-Low-Dose to "Virtual" High-Dose CT Images. MLMI@MICCAI 2017: 334-343 - [e5]Qian Wang, Yinghuan Shi, Heung-Il Suk, Kenji Suzuki
:
Machine Learning in Medical Imaging - 8th International Workshop, MLMI 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings. Lecture Notes in Computer Science 10541, Springer 2017, ISBN 978-3-319-67388-2 [contents] - 2016
- [j34]Amin Zarshenas
, Kenji Suzuki
:
Binary coordinate ascent: An efficient optimization technique for feature subset selection for machine learning. Knowl. Based Syst. 110: 191-201 (2016) - 2015
- [j33]Dinggang Shen, Guorong Wu, Daoqiang Zhang, Kenji Suzuki
, Fei Wang, Pingkun Yan
:
Machine learning in medical imaging. Comput. Medical Imaging Graph. 41: 1-2 (2015) - [c46]Kenji Suzuki
, Mohammadamin Zarshenas, Junchi Liu, Yonghui Fan, Nazanin Makkinejad, Paul Forti, Abraham H. Dachman
:
Development of Computer-Aided Diagnostic (CADx) System for Distinguishing Neoplastic from Nonneoplastic Lesions in CT Colonography (CTC): Toward CTC beyond Detection. SMC 2015: 2262-2266 - 2014
- [j32]Fei Zuo, Jungong Han, Pingkun Yan
, Hans C. van Assen
, Kenji Suzuki
:
Guest Editorial: Special issue on advanced computing for image-guided intervention. Neurocomputing 144: 1-2 (2014) - [j31]Lifeng He, Xiao Zhao, Yuyan Chao, Kenji Suzuki
:
Configuration-Transition-Based Connected-Component Labeling. IEEE Trans. Image Process. 23(2): 943-951 (2014) - [j30]Jianwu Xu, Kenji Suzuki
:
Max-AUC Feature Selection in Computer-Aided Detection of Polyps in CT Colonography. IEEE J. Biomed. Health Informatics 18(2): 585-593 (2014) - [j29]Sheng Chen, Kenji Suzuki
:
Separation of Bones From Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined With Total Variation Minimization Smoothing. IEEE Trans. Medical Imaging 33(2): 246-257 (2014) - [c45]Kenji Suzuki
:
Mining of Training Samples for Multiple Learning Machines in Computer-Aided Detection of Lesions in CT Images. ICDM Workshops 2014: 982-989 - [c44]Guo Cao, Yazhou Liu, Kenji Suzuki
:
A new method for false-positive reduction in detection of lung nodules in CT images. DSP 2014: 474-479 - [c43]Rie Tanaka, Shigeru Sanada, Makoto Oda, M. Mitsutaka, Kenji Suzuki
, Keita Sakuta, Hiroki Kawashima:
Quantitative analysis of rib movement based on dynamic chest bone images: preliminary results. Medical Imaging: Image Processing 2014: 903437 - [p1]Kenji Suzuki
:
Pixel-based Machine Learning in Computer-Aided Diagnosis of Lung and Colon Cancer. Machine Learning in Healthcare Informatics 2014: 81-112 - 2013
- [j28]Kenji Suzuki
:
Machine Learning in Computer-Aided Diagnosis of the Thorax and Colon in CT: A Survey. IEICE Trans. Inf. Syst. 96-D(4): 772-783 (2013) - [j27]Ayman El-Baz
, Garth M. Beache, Georgy L. Gimel'farb
, Kenji Suzuki
, Kazunori Okada
:
Lung Imaging Data Analysis. Int. J. Biomed. Imaging 2013: 618561:1-618561:2 (2013) - [j26]Ayman El-Baz
, Garth M. Beache, Georgy L. Gimel'farb
, Kenji Suzuki
, Kazunori Okada
, Ahmed Elnakib
, Ahmed Soliman
, Behnoush Abdollahi:
Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies. Int. J. Biomed. Imaging 2013: 942353:1-942353:46 (2013) - [j25]Lifeng He, Yuyan Chao, Kenji Suzuki
:
An Algorithm for Connected-Component Labeling, Hole Labeling and Euler Number Computing. J. Comput. Sci. Technol. 28(3): 468-478 (2013) - [j24]Pingkun Yan
, Kenji Suzuki
, Fei Wang, Dinggang Shen:
Machine learning in medical imaging. Mach. Vis. Appl. 24(7): 1327-1329 (2013) - [j23]Sheng Chen, Kenji Suzuki
:
Computerized Detection of Lung Nodules by Means of "Virtual Dual-Energy" Radiography. IEEE Trans. Biomed. Eng. 60(2): 369-378 (2013) - [c42]Kenji Suzuki
, Hieu Trung Huynh, Yi-Peng Liu, Dominic Calabrese, Karen Zhou, Aytekin Oto, Masatoshi Hori:
Computerized segmentation of liver in hepatic CT and MRI by means of level-set geodesic active contouring. EMBC 2013: 2984-2987 - [c41]Kenji Suzuki
, Masatoshi Hori, Gen Iinuma, Abraham H. Dachman
:
Effect of CADe on radiologists' performance in detection of "difficult" polyps in CT colonography. Medical Imaging: Computer-Aided Diagnosis 2013: 86700U - [e4]Guorong Wu, Daoqiang Zhang, Dinggang Shen, Pingkun Yan, Kenji Suzuki
, Fei Wang:
Machine Learning in Medical Imaging - 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings. Lecture Notes in Computer Science 8184, Springer 2013, ISBN 978-3-319-02266-6 [contents] - 2012
- [j22]Lifeng He, Yuyan Chao, Kenji Suzuki
:
A New First-Scan Method for Two-Scan Labeling Algorithms. IEICE Trans. Inf. Syst. 95-D(8): 2142-2145 (2012) - [j21]Kenji Suzuki
, Pingkun Yan
, Fei Wang, Dinggang Shen:
Machine Learning in Medical Imaging. Int. J. Biomed. Imaging 2012: 123727:1-123727:2 (2012) - [j20]Kenji Suzuki
:
Pixel-Based Machine Learning in Medical Imaging. Int. J. Biomed. Imaging 2012: 792079:1-792079:18 (2012) - [j19]Qian Yu, Lifeng He, Tsuyoshi Nakamura, Yuyan Chao, Kenji Suzuki
:
A Mutual-Information-Based Global Matching Method for Chest-Radiography Temporal Subtraction. J. Adv. Comput. Intell. Intell. Informatics 16(7): 841-850 (2012) - [c40]Sheng Chen, Kenji Suzuki:
Bone suppression in chest radiographs by means of anatomically specific multiple massive-training ANNs. ICPR 2012: 17-20 - [c39]Lifeng He, Yuyan Chao, Kenji Suzuki:
A new algorithm for labeling connected-components and calculating the Euler number, connected-component number, and hole number. ICPR 2012: 3099-3102 - [c38]Jianwu Xu, Kenji Suzuki
:
Maximal partial AUC feature selection in computer-aided detection of hepatocellular carcinoma in contrast-enhanced hepatic CT. Medical Imaging: Computer-Aided Diagnosis 2012: 83150H - [c37]Jianwu Xu, Kenji Suzuki
:
Computer-aided detection of polyps in CT colonography by means of AdaBoost. Medical Imaging: Computer-Aided Diagnosis 2012: 83150V - [e3]Fei Wang, Dinggang Shen, Pingkun Yan, Kenji Suzuki
:
Machine Learning in Medical Imaging - Third International Workshop, MLMI 2012, Held in Conjunction with MICCAI 2012, Nice, France, October 1, 2012, Revised Selected Papers. Lecture Notes in Computer Science 7588, Springer 2012, ISBN 978-3-642-35427-4 [contents] - 2011
- [j18]Lifeng He, Yuyan Chao, Kenji Suzuki
:
Two Efficient Label-Equivalence-Based Connected-Component Labeling Algorithms for 3-D Binary Images. IEEE Trans. Image Process. 20(8): 2122-2134 (2011) - [c36]Francis O. Ferraro, Emily Kawaler
, Kenji Suzuki
:
A spinning tangent based CAD system for detection of flat lesions in CT colonography. ISBI 2011: 156-159 - [c35]Jianwu Xu, Kenji Suzuki
:
Computer-aided detection of hepatocellular carcinoma in hepatic CT: False positive reduction with feature selection. ISBI 2011: 1097-1100 - [c34]Sophia Chen, Kenji Suzuki
, Heber MacMahon:
Improved computerized detection of lung nodules in chest radiographs by means of 'virtual dual-energy' radiography. Medical Imaging: Computer-Aided Diagnosis 2011: 79630C - [c33]Kenji Suzuki
, Samuel G. Armato III, Roger Engelmann, Philip Caligiuri, Heber MacMahon:
Temporal subtraction of 'virtual dual-energy' chest radiographs for improved conspicuity of growing cancers and other pathologic changes. Medical Imaging: Computer-Aided Diagnosis 2011: 79630F - [c32]Jianwu Xu, Kenji Suzuki
, Masatoshi Hori, Aytekin Oto, Richard Baron:
Computer-aided detection of hepatocellular carcinoma in multiphase contrast-enhanced hepatic CT: a preliminary study. Medical Imaging: Computer-Aided Diagnosis 2011: 79630S - [c31]Jianwu Xu, Kenji Suzuki
:
Computer-Aided Detection of Polyps in CT Colonography with Pixel-Based Machine Learning Techniques. MLMI 2011: 360-367 - [e2]Kenji Suzuki
, Fei Wang, Dinggang Shen, Pingkun Yan:
Machine Learning in Medical Imaging - Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings. Lecture Notes in Computer Science 7009, Springer 2011, ISBN 978-3-642-24318-9 [contents] - 2010
- [j17]Lifeng He, Yuyan Chao, Kenji Suzuki
:
A Run-Based One-and-a-Half-Scan Connected-Component Labeling Algorithm. Int. J. Pattern Recognit. Artif. Intell. 24(4): 557-579 (2010) - [j16]Lifeng He, Yuyan Chao, Kenji Suzuki
:
An efficient first-scan method for label-equivalence-based labeling algorithms. Pattern Recognit. Lett. 31(1): 28-35 (2010) - [j15]Kenji Suzuki
, Jun Zhang
, Jianwu Xu:
Massive-Training Artificial Neural Network Coupled With Laplacian-Eigenfunction-Based Dimensionality Reduction for Computer-Aided Detection of Polyps in CT Colonography. IEEE Trans. Medical Imaging 29(11): 1907-1917 (2010) - [c30]Kenji Suzuki
, Mark L. Epstein, Ryan Kohlbrenner, Ademola Obajuluwa, Jianwu Xu, Masatoshi Hori, Richard Baron:
CT liver volumetry using geodesic active contour segmentation with a level-set algorithm. Medical Imaging: Computer-Aided Diagnosis 2010: 76240R - [c29]Kenji Suzuki
, Mark L. Epstein, Jianwu Xu, Piotr Obara, Don C. Rockey, Abraham H. Dachman
:
Automated scheme for measuring polyp volume in CT colonography using Hessian matrix-based shape extraction and 3D volume growing. Medical Imaging: Computer-Aided Diagnosis 2010: 762423 - [c28]Kenji Suzuki
:
Recent Advances in Reduction of False Positives in Computerized Detection of Polyps in CT Colonography. Virtual Colonoscopy and Abdominal Imaging 2010: 32-39 - [c27]Jianwu Xu, Kenji Suzuki
:
False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography: A Massive-Training Support Vector Regression Approach. Virtual Colonoscopy and Abdominal Imaging 2010: 47-52 - [c26]Kenji Suzuki
, Jianwu Xu, Jun Zhang, Ivan Sheu:
Principal-Component Massive-Training Machine-Learning Regression for False-Positive Reduction in Computer-Aided Detection of Polyps in CT Colonography. MLMI 2010: 182-189 - [e1]Fei Wang, Pingkun Yan, Kenji Suzuki
, Dinggang Shen:
Machine Learning in Medical Imaging, First International Workshop, MLMI 2010, Held in Conjunction with MICCAI 2010, Beijing, China, September 20, 2010. Proceedings. Lecture Notes in Computer Science 6357, Springer 2010, ISBN 978-3-642-15947-3 [contents]
2000 – 2009
- 2009
- [j14]Takeshi Inaba, Lifeng He, Kenji Suzuki
, Kazuhito Murakami, Yuyan Chao:
A Genetic-Algorithm-Based Temporal Subtraction for Chest Radiographs. J. Adv. Comput. Intell. Intell. Informatics 13(3): 289-296 (2009) - [j13]Kesheng Wu
, Ekow J. Otoo, Kenji Suzuki
:
Optimizing two-pass connected-component labeling algorithms. Pattern Anal. Appl. 12(2): 117-135 (2009) - [j12]Lifeng He, Yuyan Chao, Kenji Suzuki
, Kesheng Wu
:
Fast connected-component labeling. Pattern Recognit. 42(9): 1977-1987 (2009) - [c25]Lifeng He, Yuyan Chao, Kenji Suzuki
, Hidenori Itoh:
A Run-Based One-Scan Labeling Algorithm. ICIAR 2009: 93-102 - [c24]Kenji Suzuki
, Ivan Sheu, Don C. Rockey, Abraham H. Dachman
:
A CAD utilizing 3D massive-training ANNs for detection of flat lesions in CT colonography: preliminary results. Medical Imaging: Computer-Aided Diagnosis 2009: 72601A - 2008
- [j11]Lifeng He, Yuyan Chao, Kenji Suzuki
:
A Run-Based Two-Scan Labeling Algorithm. IEEE Trans. Image Process. 17(5): 749-756 (2008) - [c23]Kenji Suzuki
:
Segmentation of Lesions with Improved Specificity in Computer-Aided Diagnosis Using a Massive-Training Artificial Neural Network (MTANN). ICMLA 2008: 523-527 - [c22]Kenji Suzuki, Zhenghao Shi
, Jun Zhang
:
Supervised enhancement of lung nodules by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD). ICPR 2008: 1-4 - [c21]Kenji Suzuki
, Mark L. Epstein, Ivan Sheu, Ryan Kohlbrenner, Don C. Rockey, Abraham H. Dachman
:
Massive-training artificial neural networks for CAD for detection of polyps in CT colonography: False-negative cases in a large multicenter clinical trial. ISBI 2008: 684-687 - [c20]Zachary B. Rodgers, Martin King, Maryellen L. Giger
, Michael W. Vannier
, Dianna M. E. Bardo, Kenji Suzuki
, Li Lan:
Computerized assessment of coronary calcified plaques in CT images of a dynamic cardiac phantom. Medical Imaging: Computer-Aided Diagnosis 2008: 69150M - [c19]Kenji Suzuki
, Ivan Sheu, Mark L. Epstein, Ryan Kohlbrenner, Antonella Lostumbo, Don C. Rockey, Abraham H. Dachman
:
An MTANN CAD for detection of polyps in false-negative CT colonography cases in a large multicenter clinical trial: preliminary results. Medical Imaging: Computer-Aided Diagnosis 2008: 69150F - 2007
- [j10]Yuyan Chao, Lifeng He, Tsuyoshi Nakamura, Zhenghao Shi, Kenji Suzuki
, Hidenori Itoh:
An Improvement of Herbrand's Theorem and Its Application to Model Generation Theorem Proving. J. Comput. Sci. Technol. 22(4): 541-553 (2007) - [c18]Lifeng He, Yuyan Chao, Kenji Suzuki
:
A Run-Based Two-Scan Labeling Algorithm. ICIAR 2007: 131-142 - [c17]Lifeng He, Yuyan Chao, Kenji Suzuki
:
A Linear-Time Two-Scan Labeling Algorithm. ICIP (5) 2007: 241-244 - [c16]Kenji Suzuki
, Lifeng He, Shweta Khankari, Liang Ge, Joel Verceles, Abraham H. Dachman
:
Mixture of expert artificial neural networks with ensemble training for reduction of various sources of false positives in CAD. Medical Imaging: Computer-Aided Diagnosis 2007: 65140I - [c15]Martin King, Maryellen L. Giger
, Kenji Suzuki
, Xiaochuan Pan:
Computer-aided assessment of cardiac computed tomographic images. Medical Imaging: Computer-Aided Diagnosis 2007: 65141B - [c14]Chisako Muramatsu, Qiang Li, Robert A. Schmidt, Junji Shiraishi, Kenji Suzuki
, Gillian M. Newstead, Kunio Doi:
Determination of subjective and objective similarity for pairs of masses on mammograms for selection of similar images. Medical Imaging: Computer-Aided Diagnosis 2007: 65141I - 2006
- [j9]Kenji Suzuki
, Hiroyuki Abe, Heber MacMahon, Kunio Doi:
Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN). IEEE Trans. Medical Imaging 25(4): 406-416 (2006) - [c13]Hui Li, Maryellen L. Giger, Yading Yuan, Li Lan, Kenji Suzuki
, Andrew R. Jamieson, Laura Yarusso, Robert M. Nishikawa
, Charlene A. Sennett:
Comparison of Computerized Image Analyses for Digitized Screen-Film Mammograms and Full-Field Digital Mammography Images. Digital Mammography / IWDM 2006: 569-575 - [c12]Yading Yuan, Maryellen L. Giger
, Kenji Suzuki
, Hui Li, Andrew R. Jamieson
:
A two-stage method for lesion segmentation on digital mammograms. Medical Imaging: Image Processing 2006: 61443W - 2005
- [j8]Kenji Suzuki
, Feng Li, Shusuke Sone, Kunio Doi:
Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network. IEEE Trans. Medical Imaging 24(9): 1138-1150 (2005) - [c11]Kenji Suzuki
, Junji Shiraishi, Feng Li, Hiroyuki Abe, Heber MacMahon, Kunio Doi:
Effect of massive training artificial neural networks for rib suppression on reduction of false positives in computerized detection of nodules on chest radiographs. Medical Imaging: Image Processing 2005 - 2004
- [j7]Kenji Suzuki
, Isao Horiba, Noboru Sugie, Michio Nanki:
Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector. IEEE Trans. Medical Imaging 23(3): 330-339 (2004) - [c10]Kenji Suzuki, Kunio Doi:
Characteristics of a massive training artificial neural network in the distinction between lung nodules and vessels in CT images. CARS 2004: 923-928 - [c9]Feng Li, Qiang Li, Masahito Aoyama, Junji Shiraishi, Hiroyuki Abe, Kenji Suzuki, Roger Engelmann, Shusuke Sone, Heber MacMahon, Kunio Doi:
Usefulness of computerized scheme for differentiating benign from malignant lung nodules on high-resolution CT. CARS 2004: 946-951 - [c8]Kenji Suzuki
, Hiroyuki Abe, Feng Li, Kunio Doi:
Suppression of the contrast of ribs in chest radiographs by means of massive training artificial neural network. Medical Imaging: Image Processing 2004 - 2003
- [j6]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
Linear-time connected-component labeling based on sequential local operations. Comput. Vis. Image Underst. 89(1): 1-23 (2003) - [j5]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
Neural Edge Enhancer for Supervised Edge Enhancement from Noisy Images. IEEE Trans. Pattern Anal. Mach. Intell. 25(12): 1582-1596 (2003) - [j4]Kenji Suzuki
, Isao Horiba, Noboru Sugie, Michio Nanki:
Contour extraction of left ventricular cavity from digital subtraction angiograms using a neural edge detector. Syst. Comput. Jpn. 34(2): 55-69 (2003) - [c7]Kenji Suzuki
, Samuel G. Armato, Feng Li, Shusuke Sone, Kunio Doi:
Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT. Medical Imaging: Image Processing 2003 - 2002
- [j3]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
Efficient approximation of neural filters for removing quantum noise from images. IEEE Trans. Signal Process. 50(7): 1787-1799 (2002) - 2001
- [j2]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
A Simple Neural Network Pruning Algorithm with Application to Filter Synthesis. Neural Process. Lett. 13(1): 43-53 (2001) - [c6]Kazuhiro Ninagawa, Takashi Umeyama, Kenji Suzuki, Noboru Sugie:
Sound Source Separation in the Frequency Domain with Image Processing. INTERACT 2001: 781-782 - [c5]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
Neural Edge Detector - A Good Mimic of Conventional One Yet Robuster against Noise. IWANN (2) 2001: 303-310 - [c4]Kenji Suzuki
, Isao Horiba, Noboru Sugie, Michio Nanki:
Extraction of the contours of left ventricular cavity according with those traced by medical doctors from left ventriculograms using a neural edge detector. Medical Imaging: Image Processing 2001 - [c3]Kenji Suzuki
, Isao Horiba, Noboru Sugie, Michio Nanki:
Computer-aided diagnosis system for coronary artery stenosis using a neural network. Medical Imaging: Image Processing 2001 - 2000
- [c2]Kenji Suzuki
, Isao Horiba, Noboru Sugie:
Fast Connected-Component Labeling Based on Sequential Local Operations in the Course of Forward Raster Scan Followed by Backward Raster Scan. ICPR 2000: 2434-2437
1990 – 1999
- 1998
- [c1]Kenji Suzuki, Isao Horiba, Noboru Sugie, Michio Nanki:
A Recurrent Neural Filter for Reducing Noise in Medical X-Ray Image Sequences. ICONIP 1998: 157-160 - 1995
- [j1]Kenji Suzuki
, Isao Horiba, Kazuo Ikegaya, Michio Nanki:
Recognition of Coronary Arterial Stenosis Using Neural Network on DSA System. Syst. Comput. Jpn. 26(8): 66-74 (1995)
Coauthor Index
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