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| Original author(s) | Doga Gursoy |
|---|---|
| Developer(s) | Community project |
| Stable release | 1.14.4 [1] / 10 November 2023 |
| Repository | |
| Written in | Python, C |
| Operating system | Linux, OS X |
| Type | Image processing |
| License | BSD-3 |
| Website | tomopy |
TomoPy is an open-sourced Python toolbox to perform tomographic data processing and image reconstruction. [2]
Tomographic reconstruction creates three-dimensional views of an object by combining two-dimensional images taken from multiple directions, for example in how a computer-aided tomography scanner allows 3D views of the heart or brain. Data collection can be rapid, but the required computations are massive. Further, many common experimental perturbations can degrade the quality of tomographs, unless corrections are applied. Unless automated tools make these corrections, beamline staff can be overwhelmed by data that can be collected far faster than corrections and reconstruction can be performed. [3]
To address the needs for image correction and tomographic reconstruction in an instrument independent manner, the TomoPy code was developed, which is a parallelizable high performance tomography library.[ citation needed ]
Positron emission tomography (PET) is a functional imaging technique that uses radioactive substances known as radiotracers to visualize and measure changes in metabolic processes, and in other physiological activities including blood flow, regional chemical composition, and absorption. Different tracers are used for various imaging purposes, depending on the target process within the body.
A computed tomography scan is a medical imaging technique used to obtain detailed internal images of the body. The personnel that perform CT scans are called radiographers or radiology technologists.
Single-photon emission computed tomography is a nuclear medicine tomographic imaging technique using gamma rays. It is very similar to conventional nuclear medicine planar imaging using a gamma camera, but is able to provide true 3D information. This information is typically presented as cross-sectional slices through the patient, but can be freely reformatted or manipulated as required.
Tomography is imaging by sections or sectioning that uses any kind of penetrating wave. The method is used in radiology, archaeology, biology, atmospheric science, geophysics, oceanography, plasma physics, materials science, cosmochemistry, astrophysics, quantum information, and other areas of science. The word tomography is derived from Ancient Greek τόμος tomos, "slice, section" and γράφω graphō, "to write" or, in this context as well, "to describe." A device used in tomography is called a tomograph, while the image produced is a tomogram.
An X-ray microscope uses electromagnetic radiation in the X-ray band to produce magnified images of objects. Since X-rays penetrate most objects, there is no need to specially prepare them for X-ray microscopy observations.
Tomographic reconstruction is a type of multidimensional inverse problem where the challenge is to yield an estimate of a specific system from a finite number of projections. The mathematical basis for tomographic imaging was laid down by Johann Radon. A notable example of applications is the reconstruction of computed tomography (CT) where cross-sectional images of patients are obtained in non-invasive manner. Recent developments have seen the Radon transform and its inverse used for tasks related to realistic object insertion required for testing and evaluating computed tomography use in airport security.
Iterative reconstruction refers to iterative algorithms used to reconstruct 2D and 3D images in certain imaging techniques. For example, in computed tomography an image must be reconstructed from projections of an object. Here, iterative reconstruction techniques are usually a better, but computationally more expensive alternative to the common filtered back projection (FBP) method, which directly calculates the image in a single reconstruction step. In recent research works, scientists have shown that extremely fast computations and massive parallelism is possible for iterative reconstruction, which makes iterative reconstruction practical for commercialization.
Nanotomography, much like its related modalities tomography and microtomography, uses x-rays to create cross-sections from a 3D-object that later can be used to recreate a virtual model without destroying the original model, applying Nondestructive testing. The term nano is used to indicate that the pixel sizes of the cross-sections are in the nanometer range
Discrete tomography focuses on the problem of reconstruction of binary images from a small number of their projections.
Electron tomography (ET) is a tomography technique for obtaining detailed 3D structures of sub-cellular, macro-molecular, or materials specimens. Electron tomography is an extension of traditional transmission electron microscopy and uses a transmission electron microscope to collect the data. In the process, a beam of electrons is passed through the sample at incremental degrees of rotation around the center of the target sample. This information is collected and used to assemble a three-dimensional image of the target. For biological applications, the typical resolution of ET systems are in the 5–20 nm range, suitable for examining supra-molecular multi-protein structures, although not the secondary and tertiary structure of an individual protein or polypeptide. Recently, atomic resolution in 3D electron tomography reconstructions has been demonstrated.
Avizo is a general-purpose commercial software application for scientific and industrial data visualization and analysis.
Cone beam computed tomography is a medical imaging technique consisting of X-ray computed tomography where the X-rays are divergent, forming a cone.
IMOD is an open-source, cross-platform suite of modeling, display and image processing programs used for 3D reconstruction and modeling of microscopy images with a special emphasis on electron microscopy data. IMOD has been used across a range of scales from macromolecule structures to organelles to whole cells and can also be used for optical sections. IMOD includes tools for image reconstruction, image segmentation, 3D mesh modeling and analysis of 2D and 3D data.
Phase-contrast X-ray imaging or phase-sensitive X-ray imaging is a general term for different technical methods that use information concerning changes in the phase of an X-ray beam that passes through an object in order to create its images. Standard X-ray imaging techniques like radiography or computed tomography (CT) rely on a decrease of the X-ray beam's intensity (attenuation) when traversing the sample, which can be measured directly with the assistance of an X-ray detector. However, in phase contrast X-ray imaging, the beam's phase shift caused by the sample is not measured directly, but is transformed into variations in intensity, which then can be recorded by the detector.
Three-dimensional X-ray diffraction (3DXRD) is a microscopy technique using hard X-rays to investigate the internal structure of polycrystalline materials in three dimensions. For a given sample, 3DXRD returns the shape, juxtaposition, and orientation of the crystallites ("grains") it is made of. 3DXRD allows investigating micrometer- to millimetre-sized samples with resolution ranging from hundreds of nanometers to micrometers. Other techniques employing X-rays to investigate the internal structure of polycrystalline materials include X-ray diffraction contrast tomography (DCT) and high energy X-ray diffraction (HEDM).
X-ray computed tomography operates by using an X-ray generator that rotates around the object; X-ray detectors are positioned on the opposite side of the circle from the X-ray source.
Three-dimensional electrical capacitance tomography also known as electrical capacitance volume tomography (ECVT) is a non-invasive 3D imaging technology applied primarily to multiphase flows. Was introduced in the early 2000s as an extension of the conventional two-dimensional ECT. In conventional electrical capacitance tomography, sensor plates are distributed around a surface of interest. Measured capacitance between plate combinations is used to reconstruct 2D images (tomograms) of material distribution. Because the ECT sensor plates are required to have lengths on the order of the domain cross-section, 2D ECT does not provide the required resolution in the axial dimension. In ECT, the fringing field from the edges of the plates is viewed as a source of distortion to the final reconstructed image and is thus mitigated by guard electrodes. 3D ECT exploits this fringing field and expands it through 3D sensor designs that deliberately establish an electric field variation in all three dimensions. In 3D tomography, the data are acquired in 3D geometry, and the reconstruction algorithm produces the three-dimensional image directly, in contrast to 2D tomography, where 3D information might be obtained by stacking 2D slices reconstructed individually.
Deep learning in photoacoustic imaging combines the hybrid imaging modality of photoacoustic imaging (PA) with the rapidly evolving field of deep learning. Photoacoustic imaging is based on the photoacoustic effect, in which optical absorption causes a rise in temperature, which causes a subsequent rise in pressure via thermo-elastic expansion. This pressure rise propagates through the tissue and is sensed via ultrasonic transducers. Due to the proportionality between the optical absorption, the rise in temperature, and the rise in pressure, the ultrasound pressure wave signal can be used to quantify the original optical energy deposition within the tissue.
In physics and chemistry, photoemission orbital tomography is a combined experimental / theoretical approach which reveals information about the spatial distribution of individual molecular orbitals. Experimentally, it uses angle-resolved photoemission spectroscopy (ARPES) to obtain constant binding energy photoemission angular distribution maps, so-called tomograms, to reveal information about the electron probability distribution in molecular orbitals. Theoretically, one rationalizes these tomograms as hemispherical cuts through the molecular orbital in momentum space. This interpretation relies on the assumption of a plane wave final state, i.e., the idea that the outgoing electron can be treated as a free electron, which can be further exploited to reconstruct real-space images of molecular orbitals on a sub-Ångström length scale in two or three dimensions. Presently, POT has been applied to various organic molecules forming well-oriented monolayers on single crystal surfaces or to two-dimensional materials.
X-ray diffraction computed tomography is an experimental technique that combines X-ray diffraction with the computed tomography data acquisition approach. X-ray diffraction (XRD) computed tomography (CT) was first introduced in 1987 by Harding et al. using a laboratory diffractometer and a monochromatic X-ray pencil beam. The first implementation of the technique at synchrotron facilities was performed in 1998 by Kleuker et al.
