Kenji Suzuki
Kenji Suzuki, Ph.D. (by Published Work; Nagoya University) worked at Hitachi Medical Corporation, Japan, Aichi Prefectural University, Japan, as a faculty member, and in Department of Radiology, University of Chicago, as Assistant Professor. In 2014, he joined Department of Electric and Computer Engineering and Medical Imaging Research Center, Illinois Institute of Technology, as Associate Professor. In 2017, he was jointly appointed in World Research Hub Initiative at Tokyo Institute of Technology as Professor. He published more than 320 papers (including 110 peer-reviewed journal papers). His papers were cited more than 8,000 times by other researchers. He has an h-index of 40. He is inventor on 30 patents (including 13 granted patents), which were licensed to several companies and commercialized. He published 10 books and 22 book chapters, and edited 13 journal special issues. He was awarded/co-awarded more than 25 grants as PI including NIH R01 and ACS. He served as the Editor of a number of leading international journals, including Pattern Recognition and Medical Physics. He served as a referee for 80 international journals, an organizer of 30 international conferences, and a program committee member of 150 international conferences. He received 25 awards, including 3 RSNA Certificate of Merit Awards, IEEE Outstanding Member Award, Cancer Research Foundation Young Investigator Award, University of Chicago Kurt Rossmann Award for Excellence in Teaching, IEICE 2014 Best Journal Paper Award, and Springer-Nature EANM Most Cited Journal Paper Award 2016.
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Papers by Kenji Suzuki
Methods: We developed a 3D automated scheme for measuring polyp volume at CTC. Our scheme consisted of segmentation of colon wall to confine polyp segmentation to the colon wall, extraction of a highly polyp-like seed region based on the Hessian matrix, a 3D volume growing technique under the minimum surface expansion criterion for segmentation of polyps, and sub-voxel refinement and surface smoothing for obtaining a smooth polyp surface. Our database consisted of 30 polyp views (15 polyps) in CTC scans from 13 patients. Each patient was scanned in the supine and prone positions. Polyp sizes measured in optical colonoscopy (OC) ranged from 6-18 mm with a mean of 10 mm. A radiologist outlined polyps in each slice and calculated volumes by summation of volumes in each slice. The measurement study was repeated 3 times at least 1 week apart for minimizing a memory effect bias. We used the mean volume of the three studies as “gold standard”.
Results: Our measurement scheme yielded a mean polyp volume of 0.38 cc (range, 0.15-1.24 cc), whereas a mean “gold standard” manual volume was 0.40 cc (range, 0.15-1.08 cc). The “gold-standard” manual and computer volumetric reached excellent agreement (intra-class correlation coefficient =0.80), with no statistically significant difference [P (F≤f) =0.42].
Conclusions: We developed an automated scheme for measuring polyp volume at CTC based on Hessian matrix-based shape extraction and volume growing. Polyp volumes obtained by our automated scheme agreed excellently with “gold standard” manual volumes. Our fully automated scheme can efficiently provide accurate polyp volumes for radiologists; thus, it would help radiologists improve the accuracy and efficiency of polyp volume measurements in CTC.
Books by Kenji Suzuki
Methods: We developed a 3D automated scheme for measuring polyp volume at CTC. Our scheme consisted of segmentation of colon wall to confine polyp segmentation to the colon wall, extraction of a highly polyp-like seed region based on the Hessian matrix, a 3D volume growing technique under the minimum surface expansion criterion for segmentation of polyps, and sub-voxel refinement and surface smoothing for obtaining a smooth polyp surface. Our database consisted of 30 polyp views (15 polyps) in CTC scans from 13 patients. Each patient was scanned in the supine and prone positions. Polyp sizes measured in optical colonoscopy (OC) ranged from 6-18 mm with a mean of 10 mm. A radiologist outlined polyps in each slice and calculated volumes by summation of volumes in each slice. The measurement study was repeated 3 times at least 1 week apart for minimizing a memory effect bias. We used the mean volume of the three studies as “gold standard”.
Results: Our measurement scheme yielded a mean polyp volume of 0.38 cc (range, 0.15-1.24 cc), whereas a mean “gold standard” manual volume was 0.40 cc (range, 0.15-1.08 cc). The “gold-standard” manual and computer volumetric reached excellent agreement (intra-class correlation coefficient =0.80), with no statistically significant difference [P (F≤f) =0.42].
Conclusions: We developed an automated scheme for measuring polyp volume at CTC based on Hessian matrix-based shape extraction and volume growing. Polyp volumes obtained by our automated scheme agreed excellently with “gold standard” manual volumes. Our fully automated scheme can efficiently provide accurate polyp volumes for radiologists; thus, it would help radiologists improve the accuracy and efficiency of polyp volume measurements in CTC.