Achieving high quality 3D RI reconstructions from sparse data in high-throuput Holographic Tomography through CNN-based 2D projection synthesis - dataset

This dataset constains training data of two types:

1. Synthetic and technical volumes:
   This part of the dataset contains synthetically generated objects containing spherical or cube-like objects, augmented to include flipping, noise, shifting, stretching and shearing. It also contains technical objects (cell phantoms) [1, 2] and their augmentations.
2. Experimental data: 
   It also contains a large number of volumes with experimental 3D RI reconstructions: microspheres, HaCaT, lymphocyte cells and many others [3, 4].

This dataset was curated in a way to have balance between synthetic, technical and experimental data. It was also ensured that it was balanced in terms of the objects themselves. Therefore it contains the same number of datapoints originating from each object.

It also contains the models for synthesizing phase and amplitude of the projections. Suggested use: Models take two adjacent projections (originating from adjacent illumination angles in the setup) and generate one intermediate projection between them. It is suggested to iterate over the entire projection space (assuming cone-beam illumination) one by one and generating a new projection in between each pair, essentially doubling the projection space size.

[1] M. Ziemczonok, A. Kuś, P. Wasylczyk, and M. Kujawińska, “3d-printed biological cell phantom for testing 3d quantitative phase imaging systems,” Sci. Reports 9, 1–9 (2019).
[2] M. Ziemczonok, A. Kuś, and M. Kujawińska, “Optical diffraction tomography meets metrology — measurement accuracy on cellular and subcellular level,” Measurement 195, 111106 (2022).
[3] M. Baczewska, W. Krauze, A. Kuś, P. Stępień, K. Tokarska, K. Zukowski, E. Malinowska, Z. Brzózka, and M. Kujawińska, “On-chip holographic tomography for quantifying refractive index changes of cells’ dynamics,” in Quantitative Phase Imaging VIII, vol. 11970 Y. Liu, G. Popescu, and Y. Park, eds., International Society for Optics and Photonics (SPIE, 2022), p. 1197008.
[4] P. Stępień, M. Ziemczonok, M. Kujawińska, M. Baczewska, L. Valenti, A. Cherubini, E. Casirati, and W. Krauze, “Numerical refractive index correction for the stitching procedure in tomographic quantitative phase imaging,” Biomed. Opt. Express 13, 5709–5720 (2022).