2781:
the special issue of IEEE Transaction on
Medical Imaging. One group of deep learning reconstruction algorithms apply post-processing neural networks to achieve image-to-image reconstruction, where input images are reconstructed by conventional reconstruction methods. Artifact reduction using the U-Net in limited angle tomography is such an example application. However, incorrect structures may occur in an image reconstructed by such a completely data-driven method, as displayed in the figure. Therefore, integration of known operators into the architecture design of neural networks appears beneficial, as described in the concept of precision learning. For example, direct image reconstruction from projection data can be learnt from the framework of filtered back-projection. Another example is to build neural networks by unrolling iterative reconstruction algorithms. Except for precision learning, using conventional reconstruction methods with deep learning reconstruction prior is also an alternative approach to improve the image quality of deep learning reconstruction.
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35:
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custom proprietary software. This is done not only to protect intellectual property, but may also be enforced by a government regulatory agency. Regardless, there are a number of general purpose tomographic reconstruction software packages that have been developed over the last couple decades, both commercial and open-source.
38:
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33:
32:
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36:
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Deep learning methods are widely applied to image reconstruction nowadays and have achieved impressive results in various image reconstruction tasks, including low-dose denoising, sparse-view reconstruction, limited angle tomography and metal artifact reduction. An excellent overview can be found in
2789:
Tomographic systems have significant variability in their applications and geometries (locations of sources and detectors). This variability creates the need for very specific, tailored implementations of the processing and reconstruction algorithms. Thus, most CT manufacturers provide their own
2763:
beam of radiation is difficult to obtain. Fan beams will generate series of line integrals, not parallel to each other, as projections. The fan-beam system requires a 360-degree range of angles, which imposes mechanical constraints, but it allows faster signal acquisition time, which may be
1766:(DFT) on each projection yields sampling in the frequency domain. Combining all the frequency-sampled projections generates a polar raster in the frequency domain. The polar raster is sparse, so interpolation is used to fill the unknown DFT points, and reconstruction can be done through the
1903:
The concentric square raster improves computational efficiency by allowing all the interpolation positions to be on rectangular DFT lattice. Furthermore, it reduces the interpolation error. Yet, the
Fourier-Transform algorithm has a disadvantage of producing inherently noisy output.
805:
1122:
2081:
1409:
3179:
Tobias Wuerfl; Mathis
Hoffmann; Vincent Christlein; Katharina Breininger; Yixing Huang; Mathias Unberath; Andreas Maier (2018). "Deep Learning Computed Tomography: Learning Projection-Domain Weights from Image Domain in Limited Angle Problems".
519:
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advantageous in certain settings such as in the field of medicine. Back projection follows a similar two-step procedure that yields reconstruction by computing weighted sum back-projections obtained from filtered projections.
2249:
comes from the fact that a one-dimensional projection needs to be filtered by a one-dimensional Radon kernel (back-projected) in order to obtain a two-dimensional signal. The filter used does not contain DC gain, so adding
1192:
2254:
may be desirable. Reconstruction using back-projection allows better resolution than interpolation method described above. However, it induces greater noise because the filter is prone to amplify high-frequency content.
2869:
based tomographic reconstruction of the sinogram of Fig.3, presented as animation over the iterative reconstruction process. The original object could be approximatively reconstructed, as the resulting image has some
2541:
2852:
Fig. 3: Sinogram of the phantom object (Fig.2) resulting from tomography. 50 projection slices were taken over 180 degree angle, equidistantly sampled (only by coincidence the x-axis marks displacement at -50/50
34:
2738:
3320:
Maier, Andreas; Hofmann, Hannes G.; Berger, Martin; Fischer, Peter; Schwemmer, Chris; Wu, Haibo; Müller, Kerstin; Hornegger, Joachim; Choi, Jang-Hwan; Riess, Christian; Keil, Andreas; Fahrig, Rebecca (2013).
97:
Figure 1: Parallel beam geometry utilized in tomography and tomographic reconstruction. Each projection, resulting from tomography under a specific angle, is made up of the set of line integrals through the
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138:(see Fig. 1). A set of many such projections under different angles organized in 2D is called a sinogram (see Fig. 3). In X-ray CT, the line integral represents the total attenuation of the beam of
650:
2550:
A fan-beam reconstruction of Shepp-Logan
Phantom with different sensor spacing. Smaller spacing between the sensors allow finer reconstruction. The figure was generated by using MATLAB.
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1520:
tells us that if we had an infinite number of one-dimensional projections of an object taken at an infinite number of angles, we could perfectly reconstruct the original object,
3120:
Maier, Andreas K; Syben, Christopher; Stimpel, Bernhard; Wuerfl, Tobias; Hoffmann, Mathis; Schebesch, Frank; Fu, Weilin; Mill, Leonid; Kling, Lasse; Christiansen, Silke (2019).
3488:
van Aarle, Wim; Palenstijn, Willem Jan; Cant, Jeroen; Janssens, Eline; Bleichrodt, Folkert; Dabravolski, Andrei; De
Beenhouwer, Jan; Joost Batenburg, K.; Sijbers, Jan (2016).
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Most of the commercial software packages that are available for purchase focus on processing data for benchtop cone-beam CT systems. A few of these software packages include
2181:
1512:
2816:
Some noteworthy examples of open-source reconstruction software include: Reconstruction
Toolkit (RTK), CONRAD, TomoPy, the ASTRA toolbox, PYRO-NN, ODL, TIGRE, and LEAP.
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The influence of
Poisson noise in deep learning reconstruction where Poisson noise causes the U-Net fail to reconstruct an existing high contrast lesion-like object.
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Practical reconstruction algorithms have been developed to implement the process of reconstruction of a three-dimensional object from its projections. These
420:
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1770:. Reconstruction performance may improve by designing methods to change the sparsity of the polar raster, facilitating the effectiveness of interpolation.
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3841:
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ASTRA (All Scales
Tomographic Reconstruction Antwerp) toolbox; very flexible, fast open-source software for computed tomographic reconstruction
2444:
4212:
106:
Resulting tomographic image from a plastic skull phantom. Projected X-rays are clearly visible on this slice taken with a CT-scan as image
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For instance, a concentric square raster in the frequency domain can be obtained by changing the angle between each projection as follow:
2557:
4053:
2824:
Shown in the gallery is the complete process for a simple object tomography and the following tomographic reconstruction based on ART.
800:{\displaystyle p_{\theta }(r)=\int _{-\infty }^{\infty }\int _{-\infty }^{\infty }f(x,y)\delta (x\cos \theta +y\sin \theta -r)\,dx\,dy}
4605:
4484:
4224:
4133:
2866:
2744:
1767:
1117:{\displaystyle P_{\theta }(\omega )=\int _{-\infty }^{\infty }\int _{-\infty }^{\infty }f(x,y)\exp\,dx\,dy=F(\Omega _{1},\Omega _{2})}
4063:
3721:
2810:
239:
185:, as used in the first scanners. For this discussion we consider the data to be collected as a series of parallel rays, at position
74:
and its inverse used for tasks related to realistic object insertion required for testing and evaluating computed tomography use in
4048:
4043:
3926:
3039:
Wang, Ge; Ye, Jong Chu; Mueller, Klaus; Fessler, Jeffrey A (2018). "Image reconstruction is a new frontier of machine learning".
2885:
63:
2076:{\displaystyle f(x,y)={\frac {1}{2\pi }}\sum _{i=0}^{N-1}\Delta \theta _{i}g_{\theta _{i}}(x\cos \theta _{i}+y\sin \theta _{i})}
4128:
4111:
2794:
1417:
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4336:
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2087:
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2900:
142:
as it travels in a straight line through the object. As mentioned above, the resulting image is a 2D (or 3D) model of the
2989:
Herman, G. T., Fundamentals of computerized tomography: Image reconstruction from projection, 2nd edition, Springer, 2009
4726:
4660:
4592:
4582:
4560:
4331:
4299:
3930:
2546:
4390:
4358:
4341:
55:
602:
85:, but some of the terms and physical descriptions refer directly to the reconstruction of X-ray computed tomography.
70:(CT) where cross-sectional images of patients are obtained in non-invasive manner. Recent developments have seen the
4785:
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4199:
3939:
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4765:
4705:
4373:
4363:
1404:{\displaystyle f(x,y)={\frac {1}{2\pi }}\int \limits _{0}^{\pi }g_{\theta }(x\cos \theta +y\sin \theta )d\theta }
1289:
3002:
R. Mersereau, A. Oppenheim (1974). "Digital reconstruction of multidimensional signals from their projections".
4770:
4744:
4695:
4474:
4353:
4326:
4087:
3872:
3827:
2890:
2264:
1917:
1517:
3547:
Syben, Christopher; Michen, Markus; Stimpel, Bernhard; Seitz, Stephan; Ploner, Stefan; Maier, Andreas (2019).
4643:
4479:
4420:
4405:
4294:
4116:
4092:
143:
4700:
4514:
4383:
4314:
4121:
2806:
1200:
3276:
Yixing Huang; Alexander Preuhs; Guenter
Lauritsch; Michael Manhart; Xiaolin Huang; Andreas Maier (2019).
4378:
4309:
4175:
4058:
3977:
3884:
3681:
Kim, Hyojin; Champley, Kyle (2023). "Differentiable
Forward Projector for X-ray Computed Tomography".
2408:
1643:
4721:
4410:
4348:
4170:
3791:
NiftyRec; comprehensive open-source tomographic reconstruction software; Matlab and Python scriptable
3570:
3501:
3391:
3334:
907:
354:
is the attenuation coefficient as a function of position. Therefore, generally the total attenuation
3097:
Yixing Huang; Tobias Würfl; Katharina Breininger; Ling Liu; Günter Lauritsch; Andreas Maier (2018).
2163:
1481:
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4104:
182:
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4655:
4504:
4499:
4400:
4283:
4138:
3889:
3686:
3560:
3281:
3258:
3232:
3205:
3133:
3064:
2941:
2922:
2381:
1699:, statistical knowledge of the data acquisition process and geometry of the data imaging system.
114:
The projection of an object, resulting from the tomographic measurement process at a given angle
2215:
883:
848:
322:
149:
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4395:
4143:
3992:
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1475:
922:
230:
1271:
579:
397:
208:
117:
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3143:
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3019:
3011:
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813:
75:
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2871:
2837:
2186:
1696:
911:
107:
71:
51:
3441:"The ASTRA Toolbox: a platform for advanced algorithm development in electron tomography"
54:
where the challenge is to yield an estimate of a specific system from a finite number of
3574:
3505:
3395:
3338:
3278:
Data Consistent Artifact Reduction for Limited Angle Tomography with Deep Learning Prior
17:
4672:
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527:
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514:{\displaystyle p_{\theta }(r)=\ln \left({\frac {I}{I_{0}}}\right)=-\int \mu (x,y)\,ds}
4759:
4304:
4273:
4261:
4256:
4014:
3909:
3785:
3524:
3465:
135:
3638:
Biguri, Ander; Dosanjh, Manjit; Hancock, Steven; Soleimani, Manuchehr (2016-09-08).
3262:
3209:
3068:
2945:
2269:
The iterative algorithm is computationally intensive but it allows the inclusion of
1555:. However, there will only be a finite number of projections available in practice.
181:. The simplest and easiest way to visualise the method of scanning is the system of
43:
Tomographic reconstruction: Projection, Back projection and Filtered back projection
4687:
4540:
4535:
4442:
4266:
4251:
4185:
3456:
59:
3295:
3106:
2743:
An alternative family of recursive tomographic reconstruction algorithms are the
4610:
4165:
3997:
3987:
3967:
3957:
3899:
3894:
3863:
3709:
3084:
Multi-scale wavelet domain residual learning for limited-angle CT reconstruction
2930:
Proc. SPIE Optics and Photonics for Counterterrorism, Crime Fighting and Defence
2923:"Radon Transform based Metal Artefacts Generation in 3D Threat Image Projection"
1516:
In theory, the inverse Radon transformation would yield the original image. The
226:
3435:
van Aarle, Wim; Palenstijn, Willem Jan; De Beenhouwer, Jan; Altantzis, Thomas;
2921:
Najla Megherbi; Toby P. Breckon; Greg T. Flitton; Andre Mouton (October 2013).
1863:{\displaystyle \theta '={\frac {R_{0}}{\max\{|\cos \theta |,|\sin \theta |\}}}}
1187:{\displaystyle \Omega _{1}=\omega \cos \theta ,\Omega _{2}=\omega \sin \theta }
93:
4246:
4009:
4004:
3972:
3403:
3147:
3099:
Some Investigations on Robustness of Deep Learning in Limited Angle Tomography
82:
3665:
3246:
3193:
3052:
1640:, a rule of thumb for the number of projections needed for reconstruction is
4573:
4509:
3962:
3436:
1692:
3600:
3533:
3474:
3421:
3378:
Gürsoy, Doǧa; De Carlo, Francesco; Xiao, Xianghui; Jacobsen, Chris (2014).
3364:
3254:
3201:
3165:
3060:
3015:
1762:
are generated at equally spaced angles, each sampled at the same rate. The
81:
This article applies in general to reconstruction methods for all kinds of
4596:
3514:
3024:
2536:{\displaystyle f_{0}(x,y)=\sum _{i=1}^{N}\lambda _{i}p_{\theta _{i}}(r)}
1912:
In practice of tomographic image reconstruction, often a stabilized and
4625:
4028:
3790:
2937:
2251:
67:
3802:"ITS plc - Electrical Process Tomography For Industrial Visualization"
3380:"TomoPy: A framework for the analysis of synchrotron tomographic data"
3346:
4620:
3619:
3582:
3716:(1988), Principles of Computerized Tomographic Imaging, IEEE Press,
102:
3691:
3565:
3286:
3237:
3138:
2733:{\displaystyle f_{k}(x,y)=f_{k-1}(x,y)+\sum _{i=1}^{N}\lambda _{i}}
4647:
3858:
3819:
3614:
3323:"CONRAD - A software framework for cone-beam imaging in radiology"
2771:
2545:
2438:
are a set of parameters to optimize the conversion of iterations.
139:
101:
92:
58:. The mathematical basis for tomographic imaging was laid down by
3767:
3223:
J. Adler; O. Öktem (2018). "Learned Primal-Dual Reconstruction".
3633:
3823:
3678:
2802:
1923:
With a sampled discrete system, the inverse Radon transform is
3489:
3440:
309:{\displaystyle I=I_{0}\exp \left({-\int \mu (x,y)\,ds}\right)}
27:
Estimate object properties from a finite number of projections
3796:
Open-source tomographic reconstruction and visualization tool
3743:
3549:"PYRO-NN: Python Reconstruction Operators in Neural Networks"
1916:
version of the inverse Radon transform is used, known as the
3490:"Fast and flexible X-ray tomography using the ASTRA toolbox"
3122:"Learning with known operators reduces maximum error bounds"
1292:, the inverse Radon transform formula can be easily derived.
3729:"Analytic and iterative reconstruction algorithms in SPECT"
3640:"TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction"
3308:
2886:
Operation of computed tomography#Tomographic reconstruction
3801:
3762:
Insight ToolKit; open-source tomographic support software
2798:
110:, due to limited amount of projection slices over angles.
1467:{\displaystyle g_{\theta }(x\cos \theta +y\sin \theta )}
2150:{\displaystyle g_{\theta }(t)=p_{\theta }(t)\cdot k(t)}
1707:
Reconstruction can be made using interpolation. Assume
3795:
524:
Using the coordinate system of Figure 1, the value of
3280:. Machine Learning for Medical Image Reconstruction.
2560:
2447:
2411:
2384:
2364:
2337:
2317:
2279:
2218:
2189:
2166:
2090:
1932:
1879:
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1733:
1713:
1695:
are designed largely based on the mathematics of the
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3439:; Batenburg, K. Joost; Sijbers, Jan (October 2015).
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2183:is the angular spacing between the projections and
3731:Journal of Nuclear Medicine 43(10):1343-1358, 2002
2759:Use of a noncollimated fan beam is common since a
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1233:represents a slice of the 2D Fourier transform of
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126:
3744:"Principles of Computerized Tomographic Imaging"
1807:
645:{\displaystyle x\cos \theta +y\sin \theta =r\ }
3835:
8:
3644:Biomedical Physics & Engineering Express
3634:Released by the University of Bath and CERN.
2749:iterative sparse asymptotic minimum variance
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1810:
62:. A notable example of applications is the
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4447:
4437:
4033:
3877:
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2977:Multidimensional digital signal processing
2212:is a Radon kernel with frequency response
655:So the equation above can be rewritten as
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119:
4678:Orthogonal polarization spectral imaging
29:
2913:
2826:
1703:Fourier-domain reconstruction algorithm
225:. This is repeated for various angles.
2932:. Vol. 8901. SPIE. pp. 1–7.
1900:is highest frequency to be evaluated.
3768:"TomoPy — TomoPy 1.1.3 documentation"
146:. That is, we wish to find the image
7:
3225:IEEE Transactions on Medical Imaging
3182:IEEE Transactions on Medical Imaging
3041:IEEE Transactions on Medical Imaging
2997:
2995:
2970:
2968:
2966:
2964:
2962:
1226:{\displaystyle P_{\theta }(\omega )}
925:of the projection can be written as
2785:Tomographic reconstruction software
2745:algebraic reconstruction techniques
2358:be the distortion operator for the
4776:Multidimensional signal processing
4485:Sestamibi parathyroid scintigraphy
3082:Gu, Jawook; Ye, Jong Chul (2017).
2259:Iterative reconstruction algorithm
2167:
1996:
1768:inverse discrete Fourier transform
1160:
1132:
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1089:
988:
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718:
713:
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695:
25:
2331:be the number of projections and
414:, is given by the line integral:
4740:
4739:
3384:Journal of Synchrotron Radiation
2858:
2845:
2829:
2807:Livermore Tomography Tools (LTT)
2431:{\displaystyle \{\lambda _{i}\}}
2378:th projection taken at an angle
1677:{\displaystyle N>\pi d/R_{s}}
910:. This function is known as the
4242:Cholangiopancreatography (MRCP)
3742:Slaney, A. C. Kak and Malcolm.
205:, across a projection at angle
4490:Radioactive iodine uptake test
3457:10.1016/j.ultramic.2015.05.002
2975:Dudgeon and Mersereau (1984).
2896:Industrial computed tomography
2811:Cone Beam Software Tools (CST)
2727:
2724:
2712:
2680:
2674:
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2617:
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2583:
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2524:
2470:
2458:
2295:
2283:
2228:
2220:
2199:
2193:
2176:{\displaystyle \Delta \theta }
2144:
2138:
2129:
2123:
2107:
2101:
2070:
2026:
1948:
1936:
1850:
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1828:
1814:
1749:
1737:
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1568:
1542:
1530:
1507:{\displaystyle p_{\theta }(r)}
1501:
1495:
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1431:
1392:
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1316:
1304:
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1243:
1220:
1214:
1111:
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50:is a type of multidimensional
1:
4470:Radionuclide ventriculography
3944:Lower gastrointestinal series
3936:Upper gastrointestinal series
2901:Industrial Tomography Systems
2273:information about the system
394:, on the projection at angle
4661:Optical coherence tomography
4583:Myocardial perfusion imaging
4171:Dental panoramic radiography
3657:10.1088/2057-1976/2/5/055010
3309:Reconstruction Toolkit (RTK)
3296:10.1007/978-3-030-33843-5_10
3107:10.1007/978-3-030-00928-1_17
3086:. Fully3D. pp. 443–447.
2768:Deep learning reconstruction
3126:Nature Machine Intelligence
2840:, two kitty-corner squares.
2398:{\displaystyle \theta _{i}}
576:will be projected at angle
4807:
4465:Ventilation/perfusion scan
3940:Small-bowel follow-through
2262:
1764:discrete Fourier transform
1613:and desired resolution is
48:Tomographic reconstruction
4735:
4706:Dynamic angiothermography
4450:
4374:Abdominal ultrasonography
3880:
3525:10067/1392160151162165141
3466:10067/1278340151162165141
3404:10.1107/S1600577514013939
3148:10.1038/s42256-019-0077-5
2235:{\displaystyle |\omega |}
1908:Back projection algorithm
1687:Reconstruction algorithms
1474:is the derivative of the
1290:inverse Fourier transform
899:{\displaystyle \delta ()}
873:{\displaystyle \mu (x,y)}
347:{\displaystyle \mu (x,y)}
174:{\displaystyle \mu (x,y)}
134:, is made up of a set of
4696:Non-contact thermography
4475:Radionuclide angiography
4327:Doppler echocardiography
3247:10.1109/TMI.2018.2799231
3194:10.1109/TMI.2018.2833499
3053:10.1109/TMI.2018.2833635
2891:Cone beam reconstruction
2265:Iterative reconstruction
1918:filtered back projection
1518:projection-slice theorem
18:Reconstruction algorithm
4480:Radioisotope renography
3004:Proceedings of the IEEE
2755:Fan-beam reconstruction
1593:has effective diameter
1281:{\displaystyle \theta }
589:{\displaystyle \theta }
407:{\displaystyle \theta }
218:{\displaystyle \theta }
144:attenuation coefficient
127:{\displaystyle \theta }
4515:Gastric emptying study
3772:Tomopy.readthedocs.org
3016:10.1109/proc.1974.9625
2777:
2734:
2643:
2551:
2537:
2496:
2432:
2399:
2372:
2352:
2325:
2302:
2301:{\displaystyle f(x,y)}
2236:
2206:
2177:
2151:
2077:
1995:
1894:
1864:
1756:
1755:{\displaystyle f(x,y)}
1721:
1678:
1634:
1607:
1587:
1586:{\displaystyle f(x,y)}
1549:
1548:{\displaystyle f(x,y)}
1508:
1468:
1405:
1351:
1282:
1262:
1261:{\displaystyle f(x,y)}
1227:
1188:
1118:
900:
874:
839:
838:{\displaystyle f(x,y)}
801:
646:
590:
570:
538:
515:
408:
388:
368:
348:
310:
219:
199:
175:
128:
111:
99:
44:
4176:X-ray motion analysis
4059:X-ray microtomography
3978:Hysterosalpingography
3885:Pneumoencephalography
2775:
2735:
2623:
2549:
2538:
2476:
2433:
2400:
2373:
2353:
2351:{\displaystyle D_{i}}
2326:
2303:
2237:
2207:
2178:
2152:
2078:
1969:
1895:
1893:{\displaystyle R_{0}}
1865:
1757:
1722:
1679:
1635:
1633:{\displaystyle R_{s}}
1608:
1588:
1550:
1509:
1469:
1406:
1337:
1283:
1263:
1228:
1189:
1119:
901:
875:
840:
802:
647:
591:
571:
569:{\displaystyle (x,y)}
544:onto which the point
539:
516:
409:
389:
374:of a ray at position
369:
349:
311:
220:
200:
176:
129:
105:
96:
42:
4701:Contact thermography
4411:Emergency ultrasound
4349:Transcranial Doppler
4100:Abdominal and pelvis
3515:10.1364/OE.24.025129
2558:
2445:
2409:
2382:
2362:
2335:
2315:
2277:
2216:
2205:{\displaystyle k(t)}
2187:
2164:
2088:
1930:
1877:
1780:
1731:
1711:
1644:
1617:
1597:
1562:
1524:
1482:
1418:
1298:
1272:
1237:
1201:
1128:
932:
918:) of the 2D object.
908:Dirac delta function
884:
849:
814:
662:
603:
580:
548:
528:
421:
398:
378:
358:
323:
240:
209:
189:
150:
118:
4668:Confocal microscopy
4546:Indium-111 WBC scan
4369:Echoencephalography
4105:Virtual colonoscopy
3575:2019MedPh..46.5110S
3506:2016OExpr..2425129V
3396:2014SPIE.9212E..0NG
3339:2013MedPh..40k1914M
992:
974:
722:
704:
183:parallel projection
89:Introducing formula
68:computed tomography
4656:Optical tomography
4505:Dacryoscintigraphy
4500:Immunoscintigraphy
4139:Whole body imaging
3890:Dental radiography
2938:10.1117/12.2028506
2778:
2730:
2552:
2533:
2428:
2395:
2368:
2348:
2321:
2298:
2232:
2202:
2173:
2147:
2073:
1890:
1860:
1752:
1717:
1674:
1630:
1603:
1583:
1545:
1504:
1464:
1401:
1278:
1258:
1223:
1184:
1114:
975:
957:
896:
870:
835:
797:
705:
687:
642:
586:
566:
534:
511:
404:
384:
364:
344:
306:
215:
195:
171:
124:
112:
100:
45:
4786:Signal processing
4753:
4752:
4715:Target conditions
4638:
4637:
4634:
4633:
4554:
4553:
4495:Bone scintigraphy
4460:Scintimammography
4455:Cholescintigraphy
4300:contrast-enhanced
4194:
4193:
4154:
4153:
4144:Full-body CT scan
4044:General operation
4023:
4022:
3993:Angiocardiography
3559:(11): 5110–5115.
3347:10.1118/1.4824926
3010:(10): 1319–1338.
2371:{\displaystyle i}
2324:{\displaystyle N}
1967:
1858:
1720:{\displaystyle N}
1606:{\displaystyle d}
1476:Hilbert transform
1335:
923:Fourier Transform
641:
537:{\displaystyle r}
471:
387:{\displaystyle r}
367:{\displaystyle p}
198:{\displaystyle r}
40:
16:(Redirected from
4798:
4766:Inverse problems
4743:
4742:
4566:
4448:
4438:
4322:Echocardiography
4181:Hounsfield scale
4034:
3953:Cholecystography
3878:
3869:
3844:
3837:
3830:
3821:
3816:
3814:
3812:
3782:
3780:
3778:
3758:
3756:
3754:
3697:
3696:
3694:
3676:
3670:
3669:
3659:
3631:
3625:
3624:
3611:
3605:
3604:
3594:
3583:10.1002/mp.13753
3568:
3544:
3538:
3537:
3527:
3517:
3485:
3479:
3478:
3468:
3432:
3426:
3425:
3415:
3390:(5): 1188–1193.
3375:
3369:
3368:
3358:
3317:
3311:
3306:
3300:
3299:
3289:
3273:
3267:
3266:
3240:
3231:(6): 1322–1332.
3220:
3214:
3213:
3188:(6): 1454–1463.
3176:
3170:
3169:
3159:
3141:
3117:
3111:
3110:
3094:
3088:
3087:
3079:
3073:
3072:
3047:(6): 1289–1296.
3036:
3030:
3029:
3027:
2999:
2990:
2987:
2981:
2980:
2979:. Prentice-Hall.
2972:
2957:
2956:
2954:
2952:
2927:
2918:
2872:visual artifacts
2862:
2849:
2833:
2739:
2737:
2736:
2731:
2711:
2710:
2695:
2694:
2673:
2672:
2671:
2670:
2653:
2652:
2642:
2637:
2604:
2603:
2570:
2569:
2542:
2540:
2539:
2534:
2523:
2522:
2521:
2520:
2506:
2505:
2495:
2490:
2457:
2456:
2437:
2435:
2434:
2429:
2424:
2423:
2404:
2402:
2401:
2396:
2394:
2393:
2377:
2375:
2374:
2369:
2357:
2355:
2354:
2349:
2347:
2346:
2330:
2328:
2327:
2322:
2307:
2305:
2304:
2299:
2241:
2239:
2238:
2233:
2231:
2223:
2211:
2209:
2208:
2203:
2182:
2180:
2179:
2174:
2156:
2154:
2153:
2148:
2122:
2121:
2100:
2099:
2082:
2080:
2079:
2074:
2069:
2068:
2047:
2046:
2025:
2024:
2023:
2022:
2008:
2007:
1994:
1983:
1968:
1966:
1955:
1899:
1897:
1896:
1891:
1889:
1888:
1869:
1867:
1866:
1861:
1859:
1857:
1853:
1839:
1831:
1817:
1805:
1804:
1795:
1790:
1761:
1759:
1758:
1753:
1726:
1724:
1723:
1718:
1683:
1681:
1680:
1675:
1673:
1672:
1663:
1639:
1637:
1636:
1631:
1629:
1628:
1612:
1610:
1609:
1604:
1592:
1590:
1589:
1584:
1554:
1552:
1551:
1546:
1513:
1511:
1510:
1505:
1494:
1493:
1473:
1471:
1470:
1465:
1430:
1429:
1410:
1408:
1407:
1402:
1361:
1360:
1350:
1345:
1336:
1334:
1323:
1287:
1285:
1284:
1279:
1267:
1265:
1264:
1259:
1232:
1230:
1229:
1224:
1213:
1212:
1193:
1191:
1190:
1185:
1168:
1167:
1140:
1139:
1123:
1121:
1120:
1115:
1110:
1109:
1097:
1096:
991:
986:
973:
968:
944:
943:
905:
903:
902:
897:
879:
877:
876:
871:
844:
842:
841:
836:
806:
804:
803:
798:
721:
716:
703:
698:
674:
673:
651:
649:
648:
643:
639:
595:
593:
592:
587:
575:
573:
572:
567:
543:
541:
540:
535:
520:
518:
517:
512:
476:
472:
470:
469:
457:
433:
432:
413:
411:
410:
405:
393:
391:
390:
385:
373:
371:
370:
365:
353:
351:
350:
345:
315:
313:
312:
307:
305:
301:
258:
257:
224:
222:
221:
216:
204:
202:
201:
196:
180:
178:
177:
172:
133:
131:
130:
125:
76:airport security
41:
21:
4806:
4805:
4801:
4800:
4799:
4797:
4796:
4795:
4771:Medical imaging
4756:
4755:
4754:
4749:
4731:
4710:
4682:
4630:
4616:PET mammography
4587:
4550:
4536:Gallium-67 scan
4531:Octreotide scan
4519:
4427:
4278:
4190:
4150:
4073:
4054:High-resolution
4019:
3983:Skeletal survey
3949:Cholangiography
3862:
3853:
3851:Medical imaging
3848:
3810:
3808:
3800:
3776:
3774:
3766:
3752:
3750:
3741:
3738:
3706:
3704:Further reading
3701:
3700:
3680:
3677:
3673:
3637:
3636:
3632:
3628:
3613:
3612:
3608:
3553:Medical Physics
3546:
3545:
3541:
3487:
3486:
3482:
3445:Ultramicroscopy
3434:
3433:
3429:
3377:
3376:
3372:
3327:Medical Physics
3319:
3318:
3314:
3307:
3303:
3275:
3274:
3270:
3222:
3221:
3217:
3178:
3177:
3173:
3119:
3118:
3114:
3096:
3095:
3091:
3081:
3080:
3076:
3038:
3037:
3033:
3001:
3000:
2993:
2988:
2984:
2974:
2973:
2960:
2950:
2948:
2925:
2920:
2919:
2915:
2910:
2882:
2875:
2863:
2854:
2850:
2841:
2834:
2822:
2795:Volume Graphics
2787:
2770:
2757:
2696:
2686:
2662:
2657:
2644:
2589:
2561:
2556:
2555:
2512:
2507:
2497:
2448:
2443:
2442:
2415:
2407:
2406:
2385:
2380:
2379:
2360:
2359:
2338:
2333:
2332:
2313:
2312:
2275:
2274:
2267:
2261:
2247:back-projection
2214:
2213:
2185:
2184:
2162:
2161:
2113:
2091:
2086:
2085:
2060:
2038:
2014:
2009:
1999:
1959:
1928:
1927:
1910:
1880:
1875:
1874:
1806:
1796:
1783:
1778:
1777:
1729:
1728:
1727:projections of
1709:
1708:
1705:
1697:X-ray transform
1689:
1664:
1642:
1641:
1620:
1615:
1614:
1595:
1594:
1560:
1559:
1522:
1521:
1485:
1480:
1479:
1421:
1416:
1415:
1352:
1327:
1296:
1295:
1270:
1269:
1235:
1234:
1204:
1199:
1198:
1159:
1131:
1126:
1125:
1101:
1088:
935:
930:
929:
912:Radon transform
882:
881:
847:
846:
812:
811:
665:
660:
659:
601:
600:
578:
577:
546:
545:
526:
525:
461:
452:
424:
419:
418:
396:
395:
376:
375:
356:
355:
321:
320:
265:
249:
238:
237:
207:
206:
187:
186:
148:
147:
116:
115:
91:
72:Radon transform
52:inverse problem
30:
28:
23:
22:
15:
12:
11:
5:
4804:
4802:
4794:
4793:
4788:
4783:
4778:
4773:
4768:
4758:
4757:
4751:
4750:
4748:
4747:
4736:
4733:
4732:
4730:
4729:
4724:
4718:
4716:
4712:
4711:
4709:
4708:
4703:
4698:
4692:
4690:
4684:
4683:
4681:
4680:
4675:
4673:Endomicroscopy
4670:
4665:
4664:
4663:
4652:
4650:
4640:
4639:
4636:
4635:
4632:
4631:
4629:
4628:
4623:
4618:
4613:
4608:
4602:
4600:
4589:
4588:
4586:
4585:
4579:
4577:
4563:
4556:
4555:
4552:
4551:
4549:
4548:
4543:
4538:
4533:
4527:
4525:
4521:
4520:
4518:
4517:
4512:
4507:
4502:
4497:
4492:
4487:
4482:
4477:
4472:
4467:
4462:
4457:
4451:
4445:
4435:
4429:
4428:
4426:
4425:
4424:
4423:
4418:
4408:
4403:
4398:
4393:
4388:
4387:
4386:
4381:
4371:
4366:
4361:
4356:
4351:
4346:
4345:
4344:
4339:
4334:
4329:
4319:
4318:
4317:
4312:
4307:
4302:
4297:
4288:
4286:
4280:
4279:
4277:
4276:
4271:
4270:
4269:
4264:
4259:
4249:
4244:
4239:
4234:
4233:
4232:
4222:
4217:
4216:
4215:
4204:
4202:
4196:
4195:
4192:
4191:
4189:
4188:
4183:
4178:
4173:
4168:
4162:
4160:
4156:
4155:
4152:
4151:
4149:
4148:
4147:
4146:
4136:
4131:
4126:
4125:
4124:
4119:
4109:
4108:
4107:
4097:
4096:
4095:
4090:
4081:
4079:
4075:
4074:
4072:
4071:
4066:
4061:
4056:
4051:
4046:
4040:
4038:
4031:
4025:
4024:
4021:
4020:
4018:
4017:
4012:
4007:
4002:
4001:
4000:
3995:
3985:
3980:
3975:
3970:
3965:
3960:
3955:
3946:
3933:
3924:
3919:
3914:
3913:
3912:
3902:
3897:
3892:
3887:
3881:
3875:
3866:
3855:
3854:
3849:
3847:
3846:
3839:
3832:
3824:
3818:
3817:
3798:
3793:
3788:
3783:
3764:
3759:
3737:
3736:External links
3734:
3733:
3732:
3727:Bruyant, P.P.
3725:
3714:Malcolm Slaney
3705:
3702:
3699:
3698:
3671:
3626:
3615:"Odlgroup/Odl"
3606:
3539:
3494:Optics Express
3480:
3427:
3370:
3333:(11): 111914.
3312:
3301:
3268:
3215:
3171:
3132:(8): 373–380.
3112:
3089:
3074:
3031:
2991:
2982:
2958:
2912:
2911:
2909:
2906:
2905:
2904:
2898:
2893:
2888:
2881:
2878:
2877:
2876:
2864:
2857:
2855:
2851:
2844:
2842:
2838:Phantom object
2835:
2828:
2821:
2818:
2786:
2783:
2769:
2766:
2756:
2753:
2741:
2740:
2729:
2726:
2723:
2720:
2717:
2714:
2709:
2706:
2703:
2699:
2693:
2689:
2685:
2682:
2679:
2676:
2669:
2665:
2660:
2656:
2651:
2647:
2641:
2636:
2633:
2630:
2626:
2622:
2619:
2616:
2613:
2610:
2607:
2602:
2599:
2596:
2592:
2588:
2585:
2582:
2579:
2576:
2573:
2568:
2564:
2544:
2543:
2532:
2529:
2526:
2519:
2515:
2510:
2504:
2500:
2494:
2489:
2486:
2483:
2479:
2475:
2472:
2469:
2466:
2463:
2460:
2455:
2451:
2427:
2422:
2418:
2414:
2392:
2388:
2367:
2345:
2341:
2320:
2297:
2294:
2291:
2288:
2285:
2282:
2263:Main article:
2260:
2257:
2230:
2226:
2222:
2201:
2198:
2195:
2192:
2172:
2169:
2158:
2157:
2146:
2143:
2140:
2137:
2134:
2131:
2128:
2125:
2120:
2116:
2112:
2109:
2106:
2103:
2098:
2094:
2083:
2072:
2067:
2063:
2059:
2056:
2053:
2050:
2045:
2041:
2037:
2034:
2031:
2028:
2021:
2017:
2012:
2006:
2002:
1998:
1993:
1990:
1987:
1982:
1979:
1976:
1972:
1965:
1962:
1958:
1953:
1950:
1947:
1944:
1941:
1938:
1935:
1909:
1906:
1887:
1883:
1871:
1870:
1856:
1852:
1848:
1845:
1842:
1838:
1834:
1830:
1826:
1823:
1820:
1816:
1812:
1809:
1803:
1799:
1793:
1789:
1786:
1751:
1748:
1745:
1742:
1739:
1736:
1716:
1704:
1701:
1688:
1685:
1671:
1667:
1662:
1658:
1655:
1652:
1649:
1627:
1623:
1602:
1582:
1579:
1576:
1573:
1570:
1567:
1544:
1541:
1538:
1535:
1532:
1529:
1503:
1500:
1497:
1492:
1488:
1463:
1460:
1457:
1454:
1451:
1448:
1445:
1442:
1439:
1436:
1433:
1428:
1424:
1412:
1411:
1400:
1397:
1394:
1391:
1388:
1385:
1382:
1379:
1376:
1373:
1370:
1367:
1364:
1359:
1355:
1349:
1344:
1340:
1333:
1330:
1326:
1321:
1318:
1315:
1312:
1309:
1306:
1303:
1293:
1277:
1257:
1254:
1251:
1248:
1245:
1242:
1222:
1219:
1216:
1211:
1207:
1195:
1194:
1183:
1180:
1177:
1174:
1171:
1166:
1162:
1158:
1155:
1152:
1149:
1146:
1143:
1138:
1134:
1113:
1108:
1104:
1100:
1095:
1091:
1087:
1084:
1081:
1078:
1075:
1071:
1068:
1064:
1061:
1058:
1055:
1052:
1049:
1046:
1043:
1040:
1037:
1034:
1031:
1028:
1025:
1022:
1019:
1016:
1013:
1010:
1007:
1004:
1001:
998:
995:
990:
985:
982:
978:
972:
967:
964:
960:
956:
953:
950:
947:
942:
938:
895:
892:
889:
869:
866:
863:
860:
857:
854:
834:
831:
828:
825:
822:
819:
808:
807:
796:
793:
789:
786:
782:
779:
776:
773:
770:
767:
764:
761:
758:
755:
752:
749:
746:
743:
740:
737:
734:
731:
728:
725:
720:
715:
712:
708:
702:
697:
694:
690:
686:
683:
680:
677:
672:
668:
653:
652:
638:
635:
632:
629:
626:
623:
620:
617:
614:
611:
608:
585:
565:
562:
559:
556:
553:
533:
522:
521:
510:
507:
503:
500:
497:
494:
491:
488:
485:
482:
479:
475:
468:
464:
460:
455:
451:
448:
445:
442:
439:
436:
431:
427:
403:
383:
363:
343:
340:
337:
334:
331:
328:
317:
316:
304:
300:
297:
293:
290:
287:
284:
281:
278:
275:
272:
268:
264:
261:
256:
252:
248:
245:
214:
194:
170:
167:
164:
161:
158:
155:
136:line integrals
123:
90:
87:
64:reconstruction
26:
24:
14:
13:
10:
9:
6:
4:
3:
2:
4803:
4792:
4789:
4787:
4784:
4782:
4779:
4777:
4774:
4772:
4769:
4767:
4764:
4763:
4761:
4746:
4738:
4737:
4734:
4728:
4725:
4723:
4720:
4719:
4717:
4713:
4707:
4704:
4702:
4699:
4697:
4694:
4693:
4691:
4689:
4685:
4679:
4676:
4674:
4671:
4669:
4666:
4662:
4659:
4658:
4657:
4654:
4653:
4651:
4649:
4645:
4641:
4627:
4624:
4622:
4619:
4617:
4614:
4612:
4609:
4607:
4604:
4603:
4601:
4598:
4594:
4590:
4584:
4581:
4580:
4578:
4575:
4571:
4567:
4564:
4562:
4557:
4547:
4544:
4542:
4541:Ga-68-DOTATOC
4539:
4537:
4534:
4532:
4529:
4528:
4526:
4522:
4516:
4513:
4511:
4508:
4506:
4503:
4501:
4498:
4496:
4493:
4491:
4488:
4486:
4483:
4481:
4478:
4476:
4473:
4471:
4468:
4466:
4463:
4461:
4458:
4456:
4453:
4452:
4449:
4446:
4444:
4439:
4436:
4434:
4430:
4422:
4419:
4417:
4414:
4413:
4412:
4409:
4407:
4404:
4402:
4399:
4397:
4394:
4392:
4389:
4385:
4382:
4380:
4377:
4376:
4375:
4372:
4370:
4367:
4365:
4362:
4360:
4357:
4355:
4354:Intravascular
4352:
4350:
4347:
4343:
4340:
4338:
4335:
4333:
4330:
4328:
4325:
4324:
4323:
4320:
4316:
4313:
4311:
4308:
4306:
4303:
4301:
4298:
4296:
4293:
4292:
4290:
4289:
4287:
4285:
4281:
4275:
4274:Synthetic MRI
4272:
4268:
4265:
4263:
4260:
4258:
4255:
4254:
4253:
4250:
4248:
4245:
4243:
4240:
4238:
4235:
4231:
4228:
4227:
4226:
4223:
4221:
4218:
4214:
4211:
4210:
4209:
4206:
4205:
4203:
4201:
4197:
4187:
4184:
4182:
4179:
4177:
4174:
4172:
4169:
4167:
4164:
4163:
4161:
4157:
4145:
4142:
4141:
4140:
4137:
4135:
4132:
4130:
4127:
4123:
4120:
4118:
4115:
4114:
4113:
4110:
4106:
4103:
4102:
4101:
4098:
4094:
4091:
4089:
4086:
4085:
4083:
4082:
4080:
4076:
4070:
4067:
4065:
4064:Electron beam
4062:
4060:
4057:
4055:
4052:
4050:
4047:
4045:
4042:
4041:
4039:
4035:
4032:
4030:
4026:
4016:
4015:Orbital x-ray
4013:
4011:
4008:
4006:
4003:
3999:
3996:
3994:
3991:
3990:
3989:
3986:
3984:
3981:
3979:
3976:
3974:
3971:
3969:
3966:
3964:
3961:
3959:
3956:
3954:
3950:
3947:
3945:
3941:
3937:
3934:
3932:
3928:
3925:
3923:
3920:
3918:
3915:
3911:
3910:Bronchography
3908:
3907:
3906:
3903:
3901:
3898:
3896:
3893:
3891:
3888:
3886:
3883:
3882:
3879:
3876:
3874:
3870:
3867:
3865:
3860:
3856:
3852:
3845:
3840:
3838:
3833:
3831:
3826:
3825:
3822:
3807:
3803:
3799:
3797:
3794:
3792:
3789:
3787:
3784:
3773:
3769:
3765:
3763:
3760:
3749:
3745:
3740:
3739:
3735:
3730:
3726:
3723:
3722:0-87942-198-3
3719:
3715:
3711:
3708:
3707:
3703:
3693:
3688:
3684:
3679:
3675:
3672:
3667:
3663:
3658:
3653:
3650:(5): 055010.
3649:
3645:
3641:
3635:
3630:
3627:
3622:
3621:
3616:
3610:
3607:
3602:
3598:
3593:
3588:
3584:
3580:
3576:
3572:
3567:
3562:
3558:
3554:
3550:
3543:
3540:
3535:
3531:
3526:
3521:
3516:
3511:
3507:
3503:
3500:(22): 35–47.
3499:
3495:
3491:
3484:
3481:
3476:
3472:
3467:
3462:
3458:
3454:
3450:
3446:
3442:
3438:
3431:
3428:
3423:
3419:
3414:
3409:
3405:
3401:
3397:
3393:
3389:
3385:
3381:
3374:
3371:
3366:
3362:
3357:
3352:
3348:
3344:
3340:
3336:
3332:
3328:
3324:
3316:
3313:
3310:
3305:
3302:
3297:
3293:
3288:
3283:
3279:
3272:
3269:
3264:
3260:
3256:
3252:
3248:
3244:
3239:
3234:
3230:
3226:
3219:
3216:
3211:
3207:
3203:
3199:
3195:
3191:
3187:
3183:
3175:
3172:
3167:
3163:
3158:
3153:
3149:
3145:
3140:
3135:
3131:
3127:
3123:
3116:
3113:
3108:
3104:
3100:
3093:
3090:
3085:
3078:
3075:
3070:
3066:
3062:
3058:
3054:
3050:
3046:
3042:
3035:
3032:
3026:
3021:
3017:
3013:
3009:
3005:
2998:
2996:
2992:
2986:
2983:
2978:
2971:
2969:
2967:
2965:
2963:
2959:
2947:
2943:
2939:
2935:
2931:
2924:
2917:
2914:
2907:
2902:
2899:
2897:
2894:
2892:
2889:
2887:
2884:
2883:
2879:
2873:
2868:
2861:
2856:
2848:
2843:
2839:
2832:
2827:
2825:
2819:
2817:
2814:
2812:
2808:
2804:
2800:
2796:
2791:
2784:
2782:
2774:
2767:
2765:
2762:
2754:
2752:
2750:
2746:
2721:
2718:
2715:
2707:
2704:
2701:
2697:
2691:
2687:
2683:
2677:
2667:
2663:
2658:
2649:
2645:
2639:
2634:
2631:
2628:
2624:
2620:
2614:
2611:
2608:
2600:
2597:
2594:
2590:
2586:
2580:
2577:
2574:
2566:
2562:
2554:
2553:
2548:
2527:
2517:
2513:
2508:
2502:
2498:
2492:
2487:
2484:
2481:
2477:
2473:
2467:
2464:
2461:
2453:
2449:
2441:
2440:
2439:
2420:
2416:
2390:
2386:
2365:
2343:
2339:
2318:
2309:
2292:
2289:
2286:
2280:
2272:
2266:
2258:
2256:
2253:
2248:
2243:
2224:
2196:
2190:
2170:
2141:
2135:
2132:
2126:
2118:
2114:
2110:
2104:
2096:
2092:
2084:
2065:
2061:
2057:
2054:
2051:
2048:
2043:
2039:
2035:
2032:
2029:
2019:
2015:
2010:
2004:
2000:
1991:
1988:
1985:
1980:
1977:
1974:
1970:
1963:
1960:
1956:
1951:
1945:
1942:
1939:
1933:
1926:
1925:
1924:
1921:
1919:
1915:
1907:
1905:
1901:
1885:
1881:
1846:
1843:
1840:
1832:
1824:
1821:
1818:
1801:
1797:
1791:
1787:
1784:
1776:
1775:
1774:
1771:
1769:
1765:
1746:
1743:
1740:
1734:
1714:
1702:
1700:
1698:
1694:
1686:
1684:
1669:
1665:
1660:
1656:
1653:
1650:
1647:
1625:
1621:
1600:
1577:
1574:
1571:
1565:
1556:
1539:
1536:
1533:
1527:
1519:
1514:
1498:
1490:
1486:
1477:
1458:
1455:
1452:
1449:
1446:
1443:
1440:
1437:
1434:
1426:
1422:
1398:
1395:
1389:
1386:
1383:
1380:
1377:
1374:
1371:
1368:
1365:
1357:
1353:
1347:
1342:
1338:
1331:
1328:
1324:
1319:
1313:
1310:
1307:
1301:
1294:
1291:
1275:
1252:
1249:
1246:
1240:
1217:
1209:
1205:
1197:
1196:
1181:
1178:
1175:
1172:
1169:
1164:
1156:
1153:
1150:
1147:
1144:
1141:
1136:
1106:
1098:
1093:
1082:
1079:
1076:
1073:
1069:
1066:
1056:
1053:
1050:
1047:
1044:
1041:
1038:
1035:
1032:
1026:
1023:
1020:
1014:
1011:
1005:
1002:
999:
993:
980:
976:
962:
958:
954:
948:
940:
936:
928:
927:
926:
924:
919:
917:
913:
909:
887:
864:
861:
858:
852:
829:
826:
823:
817:
794:
791:
787:
784:
777:
774:
771:
768:
765:
762:
759:
756:
753:
750:
747:
741:
735:
732:
729:
723:
710:
706:
692:
688:
684:
678:
670:
666:
658:
657:
656:
636:
633:
630:
627:
624:
621:
618:
615:
612:
609:
606:
599:
598:
597:
596:is given by:
583:
560:
557:
554:
531:
508:
505:
498:
495:
492:
486:
483:
480:
477:
473:
466:
462:
458:
453:
449:
446:
443:
437:
429:
425:
417:
416:
415:
401:
381:
361:
338:
335:
332:
326:
302:
298:
295:
288:
285:
282:
276:
273:
270:
266:
262:
259:
254:
250:
246:
243:
236:
235:
234:
232:
231:exponentially
228:
212:
192:
184:
165:
162:
159:
153:
145:
141:
137:
121:
109:
104:
95:
88:
86:
84:
79:
77:
73:
69:
65:
61:
57:
53:
49:
19:
4722:Acute stroke
4688:Thermography
4443:scintigraphy
4433:Radionuclide
4421:pre-hospital
4267:Tractography
4186:Radiodensity
4088:calcium scan
4049:Quantitative
3809:. Retrieved
3805:
3775:. Retrieved
3771:
3751:. Retrieved
3747:
3682:
3674:
3647:
3643:
3629:
3618:
3609:
3556:
3552:
3542:
3497:
3493:
3483:
3448:
3444:
3430:
3387:
3383:
3373:
3330:
3326:
3315:
3304:
3277:
3271:
3228:
3224:
3218:
3185:
3181:
3174:
3129:
3125:
3115:
3098:
3092:
3083:
3077:
3044:
3040:
3034:
3025:1721.1/13788
3007:
3003:
2985:
2976:
2949:. Retrieved
2929:
2916:
2823:
2815:
2792:
2788:
2779:
2758:
2742:
2310:
2270:
2268:
2246:
2244:
2159:
1922:
1911:
1902:
1872:
1772:
1706:
1690:
1557:
1515:
1413:
1288:. Using the
920:
915:
809:
654:
523:
318:
113:
80:
60:Johann Radon
47:
46:
4611:Cardiac PET
4384:renal tract
4359:Gynecologic
4291:Techniques
4262:restriction
4237:Angiography
4220:Neurography
4166:Fluoroscopy
4112:Angiography
4093:angiography
4037:Techniques:
3998:Aortography
3988:Angiography
3968:Cystography
3958:Mammography
3900:Myelography
3895:Sialography
3864:radiography
3811:7 September
3777:7 September
3753:7 September
3710:Avinash Kak
2803:iTomography
1920:algorithm.
1914:discretized
845:represents
233:in tissue:
227:Attenuation
56:projections
4791:Tomography
4760:Categories
4524:Full body:
4310:endoscopic
4284:Ultrasound
4213:functional
4010:Lymphogram
4005:Venography
3973:Arthrogram
3748:Slaney.org
3692:2307.05801
3566:1904.13342
3437:Bals, Sara
3287:1908.06792
3238:1707.06474
3139:1907.01992
3101:. MICCAI.
2951:5 November
2908:References
2799:InstaRecon
2761:collimated
1693:algorithms
83:tomography
4781:Radiology
4727:Pregnancy
4606:Brain PET
4574:gamma ray
4510:DMSA scan
4364:Obstetric
4257:diffusion
4252:Sequences
4230:perfusion
4122:Pulmonary
4069:Cone beam
3963:Pyelogram
3806:Itoms.com
3666:2057-1976
3451:: 35–47.
2705:−
2684:−
2664:θ
2646:λ
2625:∑
2598:−
2514:θ
2499:λ
2478:∑
2417:λ
2387:θ
2245:The name
2225:ω
2171:θ
2168:Δ
2133:⋅
2119:θ
2097:θ
2062:θ
2058:
2040:θ
2036:
2016:θ
2001:θ
1997:Δ
1989:−
1971:∑
1964:π
1847:θ
1844:
1825:θ
1822:
1785:θ
1654:π
1558:Assuming
1491:θ
1459:θ
1456:
1444:θ
1441:
1427:θ
1399:θ
1390:θ
1387:
1375:θ
1372:
1358:θ
1348:π
1339:∫
1332:π
1276:θ
1268:at angle
1218:ω
1210:θ
1182:θ
1179:
1173:ω
1161:Ω
1154:θ
1151:
1145:ω
1133:Ω
1103:Ω
1090:Ω
1057:θ
1054:
1042:θ
1039:
1027:ω
1021:−
1015:
989:∞
984:∞
981:−
977:∫
971:∞
966:∞
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