Open AccessOptical Tomographic Image Reconstruction Based on Gradient Tree Calculation Method
Author(s) -
Jinlan Guan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2074/1/012014
Subject(s) - tomographic reconstruction , computer science , iterative reconstruction , optical coherence tomography , computer vision , image (mathematics) , artificial intelligence , tomography , tree (set theory) , coherence (philosophical gambling strategy) , algorithm , mathematics , optics , physics , mathematical analysis , statistics
Optical coherence tomography is a new imaging method, which is widely used in many fields. This article introduces an iterative image reconstruction algorithm based on gradient trees. It also discusses image reconstruction methods containing void-like regions. It is proved that the image reconstruction based on the transportation model can overcome the shortcomings of the diffusion equation, and it can accurately reconstruct the optical tomographic image.