five

Optical tomography measurements and reconstructions of a multiple-scattering 3d-printed microphantom

收藏
NIAID Data Ecosystem2026-03-14 收录
下载链接:
https://zenodo.org/record/6652332
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset contains 2 sets of measurements of a 3d-printed microphantom, carried out with optical diffraction tomography system at Warsaw University of Technology. The measurements are conducted for 2 different wavelengths: 633nm and 835nm. Also, tomographic reconstructions of these datasets are shown. The reconstructions were computed with 3 algorithms: GPSC [1], MSBP-I [2] and MSBP-E [3]. Additionally, model of the 3D-printed microphantom is given. All files are *.mat files. In the reconstruction files there are 4 variables: REC - reconstruction matrix with information about 3D refractive index values in the microphantom dx - sample size in the reconstruction in x-y direction dz - sample size in the reconstruction in z direction (if not given, dz=dx) niter - number of iterations that were computed to generate the reconstruction The variables in the sinogram files are: dx - sample size in tomographic projections lambda - wavelength M - magnification in the optical system n_immersion - refractive index of the immersion medium NA - numerical aperture of the optical system rayXY - x-y coordinates of vectors representing illumination directions from which tomographic projections were acquired SINOamp - amplitude distribution of tomographic projections SINOph - phase distributions of tomographic projections The variables in the phantom model files are: dx - sample size n_immersion - refractive index of simulated immersion n_phantom - refractive index of the phantom model [1] W. Krauze, “Optical diffraction tomography with finite object support for the minimization of missing cone artifacts,”277 Biomed. optics express 11, 1919–1926 (2020) [2] S. Chowdhury, M. Chen, R. Eckert, D. Ren, F. Wu, N. Repina, and L. Waller, “High-resolution 3D refractive index292 microscopy of multiple-scattering samples from intensity images,” Optica 6, 1211 (2019). [3] U. S. Kamilov, I. N. Papadopoulos, M. H. Shoreh, A. Goy, C. Vonesch, M. Unser, and D. Psaltis, “Learning approach288 to optical tomography,” Optica 2, 517 (2015).
创建时间:
2022-10-21
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作