Y
YongKeun Park
Researcher at KAIST
Publications - 420
Citations - 14089
YongKeun Park is an academic researcher from KAIST. The author has contributed to research in topics: Scattering & Light scattering. The author has an hindex of 58, co-authored 378 publications receiving 11459 citations. Previous affiliations of YongKeun Park include Sungkyunkwan University & Massachusetts Institute of Technology.
Papers
More filters
Patent
Method and apparatus for generating 3-d molecular image based on label-free method using 3-d refractive index image and deep learning
TL;DR: In this article, a method and apparatus for generating a 3D molecular image based on a label-free method using a 3-D refractive index image and deep learning is presented.
Journal ArticleDOI
Pulse-to-pulse field characterization at X-ray free-electron lasers using a speckle-correlation scattering matrix
KyeoReh Lee,YongKeun Park,Jun Li +2 more
TL;DR: In this article , a speckle-correlation scattering matrix is proposed to reconstruct the complex field without sample constraints or multiple acquisitions by introducing a designed diffuser before the detector, which can readily serve as an on-field and real-time pulse diagnostic tool at XFELs.
Proceedings ArticleDOI
Optogenetic regulation of cellular functions through an intact skull using wavefront shaping
Jonghee Yoon,Minji Lee,KyeoReh Lee,Nury Kim,Jin Man Kim,Jongchan Park,Hyeon Seung Yu,Chulhee Choi,Won Do Heo,YongKeun Park +9 more
TL;DR: In vitro demonstration of spatiotemporal regulation of cellular activities by activating photoactivatable proteins through intact skull layer using wavefront shaping is presented.
Posted ContentDOI
High-fidelity optical diffraction tomography of live organisms using non-toxic tunable refractive index media
Dohyeon Lee,Moosung Lee,Haechan Kwak,Youngseo Kim,Jae Woo Shim,Jik Han Jung,Wei Sun Park,Ji-Ho Park,Sumin Lee,YongKeun Park +9 more
TL;DR: In this paper , a method for high-fidelity ODT by introducing non-toxic matching media is presented, which optimally reduces the RI contrast and enables visualization of the morphology and intra-organization of live biological samples without producing toxic effects.
Proceedings ArticleDOI
Rapid identification of individual bacterial pathogens using three-dimensional quantitative phase imaging and artificial neural network (Conference Presentation)
Geon-Soo Kim,Daewoong Ahn,Minhee Kang,Jin-Soo Park,Donghun Ryu,YoungJu Jo,Jinyeop Song,Jea Sung Ryu,Gunho Choi,Hyun Jung Chung,Kyuseok Kim,Doo Ryeon Chung,In Young Yoo,Hee Jae Huh,Hyun-Seok Min,Nam Yong Lee,YongKeun Park +16 more
TL;DR: In this paper , a hybrid framework of quantitative phase imaging and artificial neural network was proposed to facilitate rapid identification of infectious pathogens at an individual-cell level, where three-dimensional images of refractive index were acquired for individual bacteria, and an optimized artificial neural networks determined the species based on the three-dimensions morphologies, securing 82.5% blind test accuracy at individual cell level.