torch-reconstruct-tomogram

(sub-)Tomogram reconstruction and subtilt extraction for cryo-ET.

Overview

This package provides (sub-)tomogram reconstruction and subtilt extraction driven entirely from a torch-tilt-series TiltSeries. It supports

• extract_particle_tilt_series(): extract a subtilt-series at 3D location(s) in the sample
• reconstruct_subvolume(): rank-polymorphic reconstruction of 3D patch(es) at location(s) in the sample
• reconstruct_tomogram(): full volume reconstruction by tiling reconstructed patches in 3D
• load_tilt_series_images() / normalize_on_central_crop(): the lower-level image loading/normalization building blocks used internally by the functions above, also usable standalone

TiltSeries holds alignment geometry (in Angstroms) plus image_path/image_indices/pixel_spacing metadata. The functions above take a TiltSeries, load and (by default) normalize the matching raw images internally. output_pixel_spacing lets both local (reconstruct_subvolume) and global (reconstruct_tomogram) reconstruction target an arbitrary output voxel size. Reconstruction happens at the input pixel spacing and is Fourier-rescaled to the requested output size. Reconstruction is performed in Fourier space using central slice insertion. Positions are in zyx coordinates, in Angstroms, relative to the tomogram center.

Installation

pip install torch-reconstruct-tomogram

To load a tilt series from AreTomo or ETOMO output, also install the IO dependencies for torch-tilt-series:

pip install torch-tilt-series[io]

Examples

See the examples/ folder for scripts showing how to load a tilt series, reconstruct subvolumes and tomograms, and save the result.

License

This project is licensed under the BSD 3-Clause License - see the LICENSE file for details.