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List of Top 1% and 10% paper

Date :
2024.06.17
Category :
Announcement

List of Top 1% and 10% paper

The following is a list of Top 1% and 10% paper by SciVal/Scopus. (as of 06/2024)
Top 1% paper

Suzuki K.: Overview of Deep Learning in Medical Imaging. Radiological Physics and Technology 10 (3): 257-273, 2017.

Top 1% paper

El-Baz A., Beache G. M., Gimel’farb G., Suzuki K., Okada K., Elnakib A., Soliman A., and Abdollahi B.: Computer aided diagnosis systems for lung cancer: Challenges and methodologies. International Journal of Biomedical Imaging 2013: Article ID 942353, 46 pages, 2013.

Top 1% paper

Hadjiiski L., Cha K., Chan H-P., Drukker K., Morra L., Nappi J. J. Sahiner B., Yoshida H., Chen Q., Deserno T. M., Greenspan H., Huisman H., Huo Z., Mazurchuk R., Petrick N., Regge D., Samala R., Summers R. M., Suzuki K., Tourassi G., Vergara D., and Armato III S. G.: AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging, Medical Physics 50: 1-24, 2022.

Top 10% paper

Shi Z., Hao H., Zhao M., Feng Y., He L., Wang Y., and Suzuki K.: A deep CNN based transfer learning method for false positive reduction. Multimedia Tools and Applications 78(1): 1017-1033, 2019.

Top 10% paper

Tajbakhsh N. and Suzuki K.: Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs Pattern Recognition 63: 476–486, 2017.

Top 10% paper

Martínez-García M., Zhang Y., Suzuki K., and Zhang Y.: Deep Recurrent Entropy Adaptive Model for System Reliability Monitoring. IEEE Transactions on Industrial Informatics 17(2): 839-848, 2020.

Top 10% paper

He L., Chao Y., and Suzuki K.: Configuration-Transition-Based Connected-Component Labeling. IEEE Transactions on Image Processing 23: 943-951, 2014.

Top 10% paper

Chen S. and Suzuki K.: Computerized Detection of Lung Nodules by Means of “Virtual Dual-Energy” Radiography. IEEE Transactions on Biomedical Engineering 60: 369-378, 2013.

Top 10% paper

Dai P., Luo H., Sheng H., Zhao Y., Li L., Wu J., Zhao Y., Suzuki K.: A New Approach to Segment Both Main and Peripheral Retinal Vessels Based on Gray-voting and Gaussian Mixture Model, PLoS ONE 10(6): e0127748, 2015.

Top 10% paper

Zarshenas A. and Suzuki K.: Binary Coordinate Ascent: An efficient optimization technique for feature subset selection for machine learning, Knowledge-Based Systems: 110: 191-201, 2016.

Top 10% paper

He L., Chao Y., and Suzuki K.: An Algorithm for Connected-Component Labeling, Hole Labeling and Euler Number Computing. Journal of Computer Science and Technology 28(3): 468-478, 2013.

Kenji Suzuki Laboratory

Institute of Innovative Research (IIR)
Tokyo Institute of Technology

Biomedical AI Research Unit