Hideo Yokota - Concepedia

Author

Hideo Yokota

RIKEN Center for Advanced Photonics ORCID

Also Known As

H Yokota, H. Yokota, HIDEO YOKOTA, HIdeo Yokota, Hideo YOKOTA, Hideo Yokota, Norio Yamashita, Shinichi Goto, Terumitsu Hasebe, Yokota Hideo

374

Publications

5.2K

Citations

H-Index

209

Concepts

All Affiliations

RIKEN Center for Advanced Photonics RIKEN The University of Tokyo Hokkaido University University of Manchester

About

Hideo Yokota is an author at RIKEN Center for Advanced Photonics specializing in engineering, biomedical imaging, and medical imaging.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	21	40	3.1K
2	Medicine	14	18	2.1K
3	Health Sciences	12	12	325
4	Natural Sciences	3	3	111
5	Public Health	2	2	36

Hideo Yokota

Publications

4.5K

Citations

H-Index

Page 1

	Year	Citations
Whole-Brain Imaging with Single-Cell Resolution Using Chemical Cocktails and Computational Analysis Etsuo A. Susaki, Kazuki Tainaka, Dimitri Perrin, Cell Tissue ImagingEngineeringMicroscopyAdvanced ImagingComputational Analysis	2014	1.3K
Hyper Suprime-Cam: System design and verification of image quality Satoshi Miyazaki, Yutaka Komiyama, Satoshi Kawanomoto, Publications of the Astronomical Society of Japan EngineeringOptical TestingImage AnalysisActive OpticsAstronomical Image Analysis	2017	527
Local Nucleosome Dynamics Facilitate Chromatin Accessibility in Living Mammalian Cells Saera Hihara, Chan‐Gi Pack, Kazunari Kaizu, Cell Reports	2012	209
Glaucoma Diagnosis with Machine Learning Based on Optical Coherence Tomography and Color Fundus Images Guangzhou An, Kazuko Omodaka, Kazuki Hashimoto, Journal of Healthcare Engineering Convolutional Neural NetworkEngineeringMachine LearningOct DataOptic Nerve	2019	193
Automatic detection of early gastric cancer in endoscopic images using a transferring convolutional neural network Y. Sakai, Satoko Takemoto, Keisuke Hori, Convolutional Neural NetworkEngineeringMachine LearningGastroenterologyEndoscopic Images	2018	122
Optical Coherence Tomography-Based Deep-Learning Models for Classifying Normal and Age-Related Macular Degeneration and Exudative and Non-Exudative Age-Related Macular Degeneration Changes Naohiro Motozawa, Guangzhou An, Seiji Takagi, Ophthalmology and Therapy	2019	116
Nuclear pore formation but not nuclear growth is governed by cyclin-dependent kinases (Cdks) during interphase Kazuhiro Maeshima, Haruki Iino, Saera Hihara, Nature Structural & Molecular Biology Signal TransductionCyclin-dependent KinasesNuclear Pore FormationCell SignalingNuclear Growth	2010	106
Final design of the Energy-Resolved Neutron Imaging System “RADEN” at J-PARC T. Shinohara, Tetsuya Kai, Kenichi Oikawa, Journal of Physics Conference Series New Pulsed-neutron InstrumentNuclear PhysicsEngineeringPulsed NatureInstrumentation	2016	76
Immobility responses are induced by photoactivation of single glomerular species responsive to fox odour TMT Harumi Saito, Hirofumi Nishizumi, Satoshi Suzuki, Nature Communications	2017	72
Comparison of Machine-Learning Classification Models for Glaucoma Management Guangzhou An, Kazuko Omodaka, Satoru Tsuda, Journal of Healthcare Engineering	2018	70

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