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[해외논문] Missing Cone Artifact Removal in ODT Using Unsupervised Deep Learning in the Projection Domain

IEEE transactions on computational imaging, v.7, 2021년, pp.747 - 758  

Chung, Hyungjin (Korea Advanced Institute of Science and Technology (KAIST), Department of Bio and Brain Engineering, Daejeon, Republic of Korea) ,  Huh, Jaeyoung (Korea Advanced Institute of Science and Technology (KAIST), Department of Bio and Brain Engineering, Daejeon, Republic of Korea) ,  Kim, Geon (Korea Advanced Institute of Science and Technology (KAIST), Department of Physics, Daejeon, Republic of Korea) ,  Park, Yong Keun (Korea Advanced Institute of Science and Technology (KAIST), Department of Physics, Daejeon, Republic of Korea) ,  Ye, Jong Chul (Korea Advanced Institute of Science and Technology (KAIST), Department of Bio and Brain Engineering, Daejeon, Republic of Korea)

Abstract AI-Helper 아이콘AI-Helper

Optical diffraction tomography (ODT) produces a three-dimensional distribution of the refractive index (RI) by measuring scattering fields at various angles. Although the distribution of the RI is highly informative, due to the missing cone problem stemming from the limited-angle acquisition of holo...

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