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Kenji Suzuki, Ph.D.

Kenji Suzuki
Associate Professor of Electrical and Computer Engineering

Office: 

M-104, Medical Imaging Research Center (Suite 100, Technology Business Center); SH-338, Siegel Hall

Phone: 

312-567-5232

Fax: 

312-567-8976

Email: 

Education 

B.S. in Electrical and Electronic Engineering (Magna Cum Laude), Meijo University, Japan, 1991
M.S. in Electrical and Electronic Engineering (Summa Cum Laude), Meijo University, Japan, 1993
Ph.D. in Information Engineering (by Published Work), Nagoya University, Japan, 2001

Research 

Kenji Suzuki joined Department of Electrical and Computer Engineering and Medical Imaging Research Center, Illinois Institute of Technology, as Associate Professor in 2014. Before that, he worked in Research and Development Center, Hitachi Medical Corporation, Japan, from 1993 to 1997. From 1997 to 2001, he worked in Faculty of Information Science and Technology, Aichi Prefectural University, Japan, as a faculty member. In 2001, he joined Department of Radiology, the University of Chicago, as Research Associate. He was promoted to Assistant Professor of Radiology, Graduate Program in Medical Physics, and Cancer Research Center in 2006.

His research interests include computational intelligence and machine learning in medical imaging, computer-aided detection and diagnosis, and medical image processing and analysis. He published more than 230 papers (including 95 peer-reviewed journal papers) and 75 refereed abstracts. His papers were cited more than 4,000 times by other researchers, and he has an h-index of 31. He is inventor on 30 patents (including 11 granted patents), which were licensed to several companies and commercialized. He published 9 books and 19 book chapters, and edited 6 journal special issues. He was awarded/co-awarded more than 44 grants including NIH R01 totaling 10.2 million dollars.

He served as a grant reviewer for funding agencies, including National Science Foundation (NSF), National Institutes of Health (NIH), and US Army Medical Research and Materiel Command (USAMRMC). He served as the Editor-in-Chief/Associate Editor of 33 leading international journals, including Medical Physics, Academic Radiology, and International Journal of Biomedical Imaging. He served as a referee for 70 international journals, an organizer of 17 international conferences, and a program committee member of 120 international conferences.

He supervised more than 45 graduate/undergraduate students and 6 postdocs/computer scientists, and accepted 12 visiting professors in his laboratory from foreign countries, supported by grants/scholarships from their governments/institutions. He received 33 awards for his research and teaching, including Paul Hodges Award, 3 Certificate of Merit Awards from RSNA, IEEE Outstanding Member Award from IEEE, Cancer Research Foundation Young Investigator Award, Kurt Rossmann Award for Excellence in Teaching from University of Chicago, and IEICE Best Paper Award. He has been a Senior Member of IEEE since 2004.

Awards 

The 2014 Best Paper Award, the Institute of Electronics, Information and Communication Engineers (IEICE), 2014

The Kurt Rossmann Award for Excellence in Teaching, Graduate Program in Medical Physics, University of Chicago, 2011

IEEE 2010 Outstanding Member Award, IEEE Chicago Section, 2010

Certificate of Merit Award, Radiological Society of North America (RSNA), 2009

Honorable Mention Poster Award, SPIE International Symposium on Medical Imaging, 2006

Certificate of Merit Award, Radiological Society of North America (RSNA), 2006

Young Investigator Award, Cancer Research Foundation, 2005

RSNA Research Trainee Prize, Radiological Society of North America (RSNA), 2004

Certificate of Merit Award, Radiological Society of North America (RSNA), 2003

Paul C. Hodges Award, Paul C. Hodges Alumni Society, Department of Radiology, University of Chicago, 2002

Listed in Marquis Who’s Who in the World, 2000-2004; 500 Great Asians of the Early 21st Century, 2000; Marquis Who’s Who in Finance and Industry, 2001-2002; Marquis Who’s Who in Finance and Business, 2002-2003; Marquis Who’s Who in Science and Engineering, 2006-2009; Who’s Who of Emerging Leaders, 2007; Marquis Who’s Who in Mathematics and Information Technology, 2011; Marquis Who’s Who in America, 2007, 2013-2015

Books 

Suzuki K.: Editor. Computational Intelligence in Biomedical Imaging, Springer (New York, NY), 411 pp., 2014.

Wu G., Zhang D., Shen D., Yan P., Suzuki K., Wang F.: Editors. Machine Learning in Medical Imaging (MLMI), Lecture Notes in Computer Science (Springer-Verlag, Berlin), vol. 8184 (Springer-Verlag, Berlin), 262 pp., 2013.

Suzuki K.: Editor. Artificial Neural Networks - Architectures and Applications, In-Tech (Vukovar, Croatia), 256 pp., 2013.

Wang F., Shen D., Yan P., Suzuki K.: Editors. Machine Learning in Medical Imaging (MLMI), Lecture Notes in Computer Science (Springer-Verlag, Berlin), vol. 7588 (Springer-Verlag, Berlin), 276 pp., 2012.

Suzuki K.: Editor. Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis, IGI Global (Hershey, PA), 524 pp., 2012.

Suzuki K., Wang F., Shen D, Yan P.: Editors. Machine Learning in Medical Imaging (MLMI), Lecture Notes in Computer Science, 7009, Springer-Verlag (Berlin), 355 pp., 2011.

Suzuki K.: Editor. Artificial Neural Networks - Industrial and Control Engineering Applications, 478 pp., In-Tech (Vukovar, Croatia), 2011.

Suzuki K.: Editor. Artificial Neural Networks - Methodological Advances and Biomedical Applications, In-Tech (Vukovar, Croatia), 362 pp., 2011.

Wang F., Yan P., Suzuki K., Shen D: Editors. Machine Learning in Medical Imaging, Lecture Notes in Computer Science, 6357, Springer-Verlag (Berlin), 192 pp., 2010.

Professional Society Memberships 

Senior Member, Institute of Electrical and Electronics Engineers (IEEE)

Member, Advancing Science, Serving Society (AAAS)

Member, American Association of Physicists in Medicine (AAPM)

Member, International Society for Optical Engineering (SPIE)

Member, Medical Image Computing and Computer Assisted Intervention Society (MICCAI)

Member, Institute of Electronics, Information and Communication Engineers (IEICE)

Member, Information Processing Society of Japan (IPSJ)

Publications 

1.      Xu J. and Suzuki K.:  Max-AUC Feature Selection in Computer-aided Detection of Polyps in CT Colonography.  IEEE Journal of Biomedical and Health Informatics 18: 585-593, 2014.

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

3.      Chen S. and Suzuki K.:  Separation of Bones from Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined with Total Variation Minimization Smoothing.  IEEE Transactions on Medical Imaging 33: 246-257, 2014.

4.      Huynh T. H., Karademir I., Oto A., and Suzuki K.:  Computerized Liver Volumetry on MRI by Using 3D Geodesic Active Contour Segmentation.  American Journal of Roentgenology 202: 152-159, 2014.

5.      Suzuki K.:  Machine Learning in Computer-aided Diagnosis of the Thorax and Colon in CT: A Survey.  IEICE Transactions on Information & Systems.E96-D: 772-783, 2013.

6.      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.

7.      Suzuki K.:  A Review of Computer-aided Diagnosis in Thoracic and Colonic Imaging.  Quantitative Imaging in Medicine and Surgery 2: 163-176, 2012.

8.      Suzuki K.:  Pixel-based Machine-Learning in Medical Imaging. International Journal of Biomedical Imaging 2012: Article ID 792079, 18 pages, 2012.

9.      Suzuki K., Epstein M. L., Kohlbrenner R., Garg S., Hori M., Oto A., and Baron R. L.:  Quantitative Radiology: Computerized CT Liver Volumetry in Comparison with Interactive Volumetry and Manual Volumetry.  American Journal of Roentgenology 197: W706-W712, 2011.

10.   Xu J. and Suzuki K.:  Massive-training support vector regression and Gaussian process for false-positive reduction in computer-aided detection of polyps in CT colonography.  Medical Physics 38: 1888-1902, 2011.

11.   He L., Chao Y., and Suzuki K.:  Two efficient label-equivalence-based connected-component labeling algorithms for three-dimensional binary images.  IEEE Transactions on Image Processing 20: 2122-2134, 2011.

12.   Suzuki K., Zhang J., and Xu J.:  Massive-training artificial neural network coupled with Laplacian-eigenfunction-based dimensionality reduction for computer-aided detection of polyps in CT colonography.  IEEE Transactions on Medical Imaging 29: 1907-1917, 2010.

13.   Suzuki K., Kohlbrenner R., Epstein M. L., Obajuluwa A. M., Xu J., and Hori M.:  Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms.  Medical Physics 37: 2159-2166, 2010.

14.   Suzuki K., Rockey D. C., and Dachman A. H.:  CT colonography: Advanced computer-aided detection scheme utilizing MTANNs for detection of "missed" polyps in a multicenter clinical trial.  Medical Physics 37: 12-21, 2010.

15.   He L., Chao Y., and Suzuki K.:  An efficient first-scan method for pixel-based label-equivalence labeling algorithms.  Pattern Recognition Letters 31: 28-35, 2010.

16.   Suzuki K.: Supervised ‘lesion-enhancement’ filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD). Physics in Medicine and Biology 54: S31-S45, 2009.

17.   Suzuki K., Yoshida H., Nappi J., Armato III S. G., and Dachman A. H.: Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography. Medical Physics 35: 694-703, 2008.

18.   Suzuki K., Yoshida H., Nappi J., and Dachman A. H.:  Massive-training artificial neural network (MTANN) for reduction of false positives in computer-aided detection of polyps: suppression of rectal tubes.  Medical Physics 33: 3814-3824, 2006.

19.   Suzuki K., Abe H., MacMahon H., and Doi K.:  Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN).  IEEE Transactions on Medical Imaging 25: 406-416, 2006.

20.   Suzuki K., and Doi K.:  How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT?  Academic Radiology 12: 1333-1341, 2005.

21.   Suzuki K., Li F., Sone S., and Doi K.: 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 Transactions on Medical Imaging 24: 1138-1150, 2005.

22.   Suzuki K., Shiraishi J., Abe H., MacMahon H., and Doi K.: False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network. Academic Radiology 12: 191-201, 2005.

23.   Suzuki K.:  Determining the receptive field of a neural filter.  Journal of Neural Engineering 1: 228-237, 2004.

24.   Suzuki K., Horiba I., Sugie N., and Nanki M.:  Extraction of left ventricular contours from left ventriculograms by means of a neural edge detector.  IEEE Transactions on Medical Imaging 23: 330-339, 2004.

25.   Suzuki K., Horiba I., and Sugie N.:  Neural edge enhancer for supervised edge enhancement from noisy images.  IEEE Transactions on Pattern Analysis and Machine Intelligence 25: 1582-1596, 2003.

26.   Suzuki K., Armato III S. G., Li F., Sone S., and Doi K.:  Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT.  Medical Physics 30: 1602-1617, 2003. 

27.   Suzuki K., Horiba I., and Sugie N.:  Linear-time connected-component labeling based on sequential local operations.  Computer Vision and Image Understanding 89: 1-23, 2003. 

28.   Suzuki K., Horiba I., Sugie N., and Nanki M.:  Neural filter with selection of input features and its application to image quality improvement of medical image sequences.  IEICE Transactions on Information and Systems E85-D: 1710-1718, 2002.

29.   Suzuki K., Horiba I., and Sugie N.:  Efficient approximation of neural filters for removing quantum noise from images.  IEEE Transactions on Signal Processing 50: 1787-1799, 2002.

30.   Suzuki K., Horiba I., and Sugie N.:  A simple neural network pruning algorithm with application to filter synthesis.  Neural Processing Letters 13: 43-53, 2001.

Patents 

1.   Suzuki K. and Doi K.:  Image modification and detection using massive training artificial neural networks (MTANN).  United States Patent, No. 7545965 issued June 2009 (filed November 2003).

2.   Suzuki K. and Doi K.:  Method of training massive training artificial neural network (MTANN) for the detection of abnormalities in medical images.  United States Patent, No. 6,754,380, issued June 2004 (filed February 2003).

3.   Suzuki K. and Doi K.:  Massive training artificial neural network (MTANN) for detecting abnormalities in medical images.  United States Patent, No. 6,819,790, issued November 2004 (filed April 2002).

4.   Suzuki K., Ikeda S., and Horiba I.:  Image processor.  Japanese Patent, No. 39492129, issued April 2007 (filed March 1997).

5.   Suzuki K.:  Image processor.  Japanese Patent, No. 3,953,569, issued May 2007 (filed March 1997).

6.   Horiba I., Suzuki K., and Hayashi T.:  Image processing apparatus for performing image converting process by neural network.  United States Patent, No. 6,084,981, issued July 2000 (filed March 1996).

7.   Horiba I., Suzuki K., and Hayashi T.:  Image processor.  Japanese Patent, No. 3,642,591, issued February 2005 (filed November 1994).

8.   Horiba I. and Suzuki K.:  Medical image diagnosing apparatus.  Japanese Patent, No. 3,641,495, issued January 2005 (filed July 1994).

9.   Yoshino H., Oda K., Kawasaki S., Takeya M., Sugawara M., Yamada K., and Suzuki K.:  Image diagnostic system.  Japanese Patent, No. 3,465,960, issued August 2003 (filed June 1994).

10.   Horiba I., Suzuki K., Ueda K., and Yamada M.:  Method for detecting traffic status.  Japanese Patent, No. 2,533,719, issued June 1996 (filed October 1992).

11.   Horiba I., and Suzuki K.:  Image processor.  Japanese Patent, No. 3,147,469, issued January 2001 (filed March 1992).