Machine Learning-Based View Synthesis in Fourier Lightfield Microscopy
| Autor: | Julen Rostan, Nicolò Incardona, Pedro Latorre Carmona, Manuel Martinez-Corral, Emilio Sánchez-Ortiga |
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| Rok vydání: | 2022 |
| Předmět: |
Informática
Microscopy Fourier lightfield microscopy view synthesis neural radiance fields 3D microscopy ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Biochemistry Computer science Atomic and Molecular Physics and Optics Analytical Chemistry Machine Learning Microscòpia Instrumento óptico Imaging Three-Dimensional Tecnología avanzada Algoritmo Neural radiance fields Electrical and Electronic Engineering View synthesis Fourier Anàlisi de Instrumentation |
| Zdroj: | Rostan, Julen Incardona, Nicolò Sánchez Ortiga, Emilio Martínez Corral, Manuel Latorre-Carmona, Pedro 2022 Machine Learning-Based View Synthesis in Fourier Lightfield Microscopy Sensors 22 3487 RODERIC. Repositorio Institucional de la Universitat de Valéncia instname Sensors; Volume 22; Issue 9; Pages: 3487 |
| Popis: | Current interest in Fourier lightfield microscopy is increasing, due to its ability to acquire 3D images of thick dynamic samples. This technique is based on simultaneously capturing, in a single shot, and with a monocular setup, a number of orthographic perspective views of 3D microscopic samples. An essential feature of Fourier lightfield microscopy is that the number of acquired views is low, due to the trade-off relationship existing between the number of views and their corresponding lateral resolution. Therefore, it is important to have a tool for the generation of a high number of synthesized view images, without compromising their lateral resolution. In this context we investigate here the use of a neural radiance field view synthesis method, originally developed for its use with macroscopic scenes acquired with a moving (or an array of static) digital camera(s), for its application to the images acquired with a Fourier lightfield microscope. The results obtained and presented in this paper are analyzed in terms of lateral resolution and of continuous and realistic parallax. We show that, in terms of these requirements, the proposed technique works efficiently in the case of the epi-illumination microscopy mode. This research was funded by Grant RTI2018-099041-B-I00, which is co-founded by the Ministerio de Ciencia, Innovacion y Universidades (Spain), by the European Regional Development Fund, and by Generalitat Valenciana (Spain) under Grant PROMETEO/2019/048. |
| Databáze: | OpenAIRE |
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