The reference publication for RTK is

Rit, S., Vila Oliva, M., Brousmiche, S., Labarbe, R., Sarrut, D., & Sharp, G. C. (2014). The Reconstruction Toolkit (RTK), an open-source cone-beam CT reconstruction toolkit based on the Insight Toolkit (ITK). Journal of Physics: Conference Series, 489, 012079. doi:10.1088/1742-6596/489/1/012079

The following articles have used and cited RTK

Reynolds, T., Shieh, C.-C., Keall, P. J., & O’Brien, R. T. (2019). Dual Cardiac and Respiratory Gated Thoracic Imaging via Adaptive Gantry Velocity and Projection Rate Modulation on a Linear Accelerator: A Proof-of-Concept Simulation Study. Medical Physics. doi:10.1002/mp.13670

Pfeiffer, T., Frysch, R., Bismark, R. N., & Rose, G. (2019). CTL: modular open-source C++-library for CT-simulations. 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. doi:10.1117/12.2534517

Iuso, D., Frysch, R., Pfeiffer, T., & Rose, G. (2019). Analysis of scatter artifacts in cone-beam CT due to scattered radiation of metallic objects. 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. doi:10.1117/12.2534465

Krah, N., & Rit, S. (2019). Optimized conversion from CT numbers to proton relative stopping power based on proton radiography and scatter corrected cone-beam CT images. 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. doi:10.1117/12.2534898

Riblett, M. J., Christensen, G. E., Weiss, E., & Hugo, G. D. (2018). Data-driven respiratory motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) using groupwise deformable registration. Medical Physics, 45(10), 4471–4482. doi:10.1002/mp.13133

Landry, G., Dörringer, F., Si‐Mohamed, S., Douek, P., Abascal, J. F. P. J., Peyrin, F., … Rit, S. (2019). Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual‐layer computed tomography. Medical Physics, 46(4), 1821–1828. doi:10.1002/mp.13404

Madesta, F., Gauer, T., Sentker, T., & Werner, R. (2019). Self-consistent deep learning-based boosting of 4D cone-beam computed tomography reconstruction. Medical Imaging 2019: Image Processing. doi:10.1117/12.2512980

Landry, G., Hansen, D., Kamp, F., Li, M., Hoyle, B., Weller, J., … Kurz, C. (2019). Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations. Physics in Medicine & Biology, 64(3), 035011. doi:10.1088/1361-6560/aaf496

Cooper, B. J., O’Brien, R. T., Shieh, C.-C., & Keall, P. J. (2019). Real-time respiratory triggered four dimensional cone-beam CT halves imaging dose compared to conventional 4D CBCT. Physics in Medicine & Biology, 64(7), 07NT01. doi:10.1088/1361-6560/ab065d

Fournier, D. E., Norley, C. J. D., Pollmann, S. I., Bailey, C. S., Al Helal, F., Willmore, K. E., … Séguin, C. A. (2019). Ectopic spinal calcification associated with diffuse idiopathic skeletal hyperostosis (DISH): A quantitative micro‐ct analysis. Journal of Orthopaedic Research, 37(3), 717–726. doi:10.1002/jor.24247

Schyns, L. E., Eekers, D. B., van der Heyden, B., Almeida, I. P., Vaniqui, A., & Verhaegen, F. (2019). Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice. The British Journal of Radiology, 92(1095), 20180454. doi:10.1259/bjr.20180454

Brun, F. (2018). From Projections to the 3D Analysis of the Regenerated Tissue. Fundamental Biomedical Technologies, 69–90. doi:10.1007/978-3-030-00368-5_5

Niepel, K., Kamp, F., Kurz, C., Hansen, D., Rit, S., Neppl, S., … Landry, G. (2018). Feasibility of 4DCBCT-based proton dose calculation: An ex vivo porcine lung phantom study. Zeitschrift Für Medizinische Physik. doi:10.1016/j.zemedi.2018.10.005

Vaniqui, A., Schyns, L. E. J. R., Almeida, I. P., van der Heyden, B., Podesta, M., & Verhaegen, F. (2019). The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT. The British Journal of Radiology, 92(1095), 20180447. doi:10.1259/bjr.20180447

Merlin, T., Stute, S., Benoit, D., Bert, J., Carlier, T., Comtat, C., … Visvikis, D. (2018). CASToR: a generic data organization and processing code framework for multi-modal and multi-dimensional tomographic reconstruction. Physics in Medicine & Biology, 63(18), 185005. doi:10.1088/1361-6560/aadac1

Hansen, D. C., Landry, G., Kamp, F., Li, M., Belka, C., Parodi, K., & Kurz, C. (2018). ScatterNet: A convolutional neural network for cone‐beam CT intensity correction. Medical Physics, 45(11), 4916–4926. doi:10.1002/mp.13175

Van der Heyden, B., Podesta, M., Eekers, D. B., Vaniqui, A., Almeida, I. P., Schyns, L. E., … Verhaegen, F. (2019). Automatic multiatlas based organ at risk segmentation in mice. The British Journal of Radiology, 92(1095), 20180364. doi:10.1259/bjr.20180364

Rodriguez-Alvarez, M. J., Sanchez, F., Soriano, A., Moliner, L., Sanchez, S., & Benlloch, J. (2018). QR-Factorization Algorithm for Computed Tomography (CT): Comparison With FDK and Conjugate Gradient (CG) Algorithms. IEEE Transactions on Radiation and Plasma Medical Sciences, 2(5), 459–469. doi:10.1109/trpms.2018.2843803

Kim, J., Park, Y.-K., Edmunds, D., Oh, K., Sharp, G. C., & Winey, B. (2018). Kilovoltage projection streaming-based tracking application (KiPSTA): First clinical implementation during spine stereotactic radiation surgery. Advances in Radiation Oncology, 3(4), 682–692. doi:10.1016/j.adro.2018.06.002

Castonguay-Henri, A., Matenine, D., Schmittbuhl, M., & de Guise, J. A. (2018). Image Quality Optimization and Soft Tissue Visualization in Cone-Beam CT Imaging. World Congress on Medical Physics and Biomedical Engineering 2018, 283–288. doi:10.1007/978-981-10-9035-6_51

Van der Heyden, B., Schyns, L. E. J. R., Podesta, M., Vaniqui, A., Almeida, I. P., Landry, G., & Verhaegen, F. (2018). VOXSI: A voxelized single- and dual-energy CT scenario generator for quantitative imaging. Physics and Imaging in Radiation Oncology, 6, 47–52. doi:10.1016/j.phro.2018.05.004

Cajgfinger, T., Rit, S., Létang, J. M., Halty, A., & Sarrut, D. (2018). Fixed forced detection for fast SPECT Monte-Carlo simulation. Physics in Medicine & Biology, 63(5), 055011. doi:10.1088/1361-6560/aa9e32

Tisseur, D., Bhatia, N., Estre, N., Berge, L., Eck, D., & Payan, E. (2018). Evaluation of a scattering correction method for high energy tomography. EPJ Web of Conferences, 170, 06006. doi:10.1051/epjconf/201817006006

Liu, Y. (2017). Improve Industrial Cone-Beam Computed Tomography by Integrating Prior Information. ETH Zurich.

Jensen, K. R., Brink, C., Hansen, O., & Bernchou, U. (2017). Ventilation measured on clinical 4D-CBCT: Increased ventilation accuracy through improved image quality. Radiotherapy and Oncology, 125(3), 459–463. doi:10.1016/j.radonc.2017.10.024

Lesaint, J., Rit, S., Clackdoyle, R., & Desbat, L. (2017). Calibration for Circular Cone-Beam CT Based on Consistency Conditions. IEEE Transactions on Radiation and Plasma Medical Sciences, 1(6), 517–526. doi:10.1109/trpms.2017.2734844

Zöllner, C., Rit, S., Kurz, C., Vilches-Freixas, G., Kamp, F., Dedes, G., … Landry, G. (2017). Decomposing a prior-CT-based cone-beam CT projection correction algorithm into scatter and beam hardening components. Physics and Imaging in Radiation Oncology, 3, 49–52. doi:10.1016/j.phro.2017.09.002

Perez Juste Abascal, J. F., Abella, M., Mory, C., de Molina, C., Ducros, N., Marinetto, E., … Desco, M. (2017). Sparse reconstruction methods in x-ray CT. Developments in X-Ray Tomography XI. doi:10.1117/12.2272711

Després, P., & Jia, X. (2017). A review of GPU-based medical image reconstruction. Physica Medica, 42, 76–92. doi:10.1016/j.ejmp.2017.07.024

Vilches-Freixas, G., Taasti, V. T., Muren, L. P., Petersen, J. B. B., Létang, J. M., Hansen, D. C., & Rit, S. (2017). Comparison of projection- and image-based methods for proton stopping power estimation using dual energy CT. Physics and Imaging in Radiation Oncology, 3, 28–36. doi:10.1016/j.phro.2017.08.001

WEBER, L., HÄNSCH, A., WOLFRAM, U., PACUREANU, A., CLOETENS, P., PEYRIN, F., … LANGER, M. (2017). Registration of phase-contrast images in propagation-based X-ray phase tomography. Journal of Microscopy, 269(1), 36–47. doi:10.1111/jmi.12606

Vilches-Freixas, G., Létang, J. M., Ducros, N., & Rit, S. (2017). Optimization of dual-energy CT acquisitions for proton therapy using projection-based decomposition. Medical Physics, 44(9), 4548–4558. doi:10.1002/mp.12448

Clackdoyle, R., Noo, F., Momey, F., Desbat, L., & Rit, S. (2017). Accurate Transaxial Region-of-Interest Reconstruction in Helical CT? IEEE Transactions on Radiation and Plasma Medical Sciences, 1(4), 334–345. doi:10.1109/trpms.2017.2706196

O’Brien, R. T., Stankovic, U., Sonke, J.-J., & Keall, P. J. (2017). Reducing 4DCBCT imaging time and dose: the first implementation of variable gantry speed 4DCBCT on a linear accelerator. Physics in Medicine and Biology, 62(11), 4300–4317. doi:10.1088/1361-6560/62/11/4300

Park, S., Kim, S., Yi, B., Hugo, G., Gach, H. M., & Motai, Y. (2017). A Novel Method of Cone Beam CT Projection Binning Based on Image Registration. IEEE Transactions on Medical Imaging, 36(8), 1733–1745. doi:10.1109/tmi.2017.2690260

Shieh, C.-C., Caillet, V., Dunbar, M., Keall, P. J., Booth, J. T., Hardcastle, N., … Feain, I. (2017). A Bayesian approach for three-dimensional markerless tumor tracking using kV imaging during lung radiotherapy. Physics in Medicine and Biology, 62(8), 3065–3080. doi:10.1088/1361-6560/aa6393

Chen, H., Rottmann, J., Yip, S. S., Morf, D., Füglistaller, R., Star-Lack, J., … Berbeco, R. (2017). Super-resolution imaging in a multiple layer EPID. Biomedical Physics & Engineering Express, 3(2), 025004. doi:10.1088/2057-1976/aa5d20

Varray, F., Mirea, I., Langer, M., Peyrin, F., Fanton, L., & Magnin, I. E. (2017). Extraction of the 3D local orientation of myocytes in human cardiac tissue using X-ray phase-contrast micro-tomography and multi-scale analysis. Medical Image Analysis, 38, 117–132. doi:10.1016/

Thing, R. S., Bernchou, U., Hansen, O., & Brink, C. (2017). Accuracy of dose calculation based on artefact corrected Cone Beam CT images of lung cancer patients. Physics and Imaging in Radiation Oncology, 1, 6–11. doi:10.1016/j.phro.2016.11.001

Veiga, C., Janssens, G., Baudier, T., Hotoiu, L., Brousmiche, S., McClelland, J., … Teo, B.-K. K. (2017). A comprehensive evaluation of the accuracy of CBCT and deformable registration based dose calculation in lung proton therapy. Biomedical Physics & Engineering Express, 3(1), 015003. doi:10.1088/2057-1976/3/1/015003

Keuschnigg, P., Kellner, D., Fritscher, K., Zechner, A., Mayer, U., Huber, P., … Steininger, P. (2017). Nine-degrees-of-freedom flexmap for a cone-beam computed tomography imaging device with independently movable source and detector. Medical Physics, 44(1), 132–142. doi:10.1002/mp.12033

Collins-Fekete, C.-A., Brousmiche, S., Portillo, S. K. N., Beaulieu, L., & Seco, J. (2016). A maximum likelihood method for high resolution proton radiography/proton CT. Physics in Medicine and Biology, 61(23), 8232–8248. doi:10.1088/0031-9155/61/23/8232

Kurz, C., Kamp, F., Park, Y.-K., Zöllner, C., Rit, S., Hansen, D., … Landry, G. (2016). Investigating deformable image registration and scatter correction for CBCT-based dose calculation in adaptive IMPT. Medical Physics, 43(10), 5635–5646. doi:10.1118/1.4962933

Mory, C., Janssens, G., & Rit, S. (2016). Motion-aware temporal regularization for improved 4D cone-beam computed tomography. Physics in Medicine and Biology, 61(18), 6856–6877. doi:10.1088/0031-9155/61/18/6856

Biguri, A., Dosanjh, M., Hancock, S., & Soleimani, M. (2016). TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction. Biomedical Physics & Engineering Express, 2(5), 055010. doi:10.1088/2057-1976/2/5/055010

Thing, R. S., Bernchou, U., Mainegra-Hing, E., Hansen, O., & Brink, C. (2016). Hounsfield unit recovery in clinical cone beam CT images of the thorax acquired for image guided radiation therapy. Physics in Medicine and Biology, 61(15), 5781–5802. doi:10.1088/0031-9155/61/15/5781

O’Brien, R. T., Cooper, B. J., Shieh, C.-C., Stankovic, U., Keall, P. J., & Sonke, J.-J. (2016). The first implementation of respiratory triggered 4DCBCT on a linear accelerator. Physics in Medicine and Biology, 61(9), 3488–3499. doi:10.1088/0031-9155/61/9/3488

Huang, H.-M., & Hsiao, I.-T. (2016). Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization. PLOS ONE, 11(4), e0153421. doi:10.1371/journal.pone.0153421

Rit, S., Clackdoyle, R., Keuschnigg, P., & Steininger, P. (2016). Filtered-backprojection reconstruction for a cone-beam computed tomography scanner with independent source and detector rotations. Medical Physics, 43(5), 2344–2352. doi:10.1118/1.4945418

Veiga, C., Janssens, G., Teng, C.-L., Baudier, T., Hotoiu, L., McClelland, J. R., … Kevin Teo, B.-K. (2016). First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer. International Journal of Radiation Oncology*Biology*Physics, 95(1), 549–559. doi:10.1016/j.ijrobp.2016.01.055

Ihsani, A., & Farncombe, T. (2016). An Adaptation of the Distance Driven Projection Method for Single Pinhole Collimators in SPECT Imaging. IEEE Transactions on Nuclear Science, 63(1), 140–150. doi:10.1109/tns.2015.2504405

Hoffman, J., Young, S., Noo, F., & McNitt-Gray, M. (2016). Technical Note: FreeCT_wFBP: A robust, efficient, open-source implementation of weighted filtered backprojection for helical, fan-beam CT. Medical Physics, 43(3), 1411–1420. doi:10.1118/1.4941953

Cai, W., Dhou, S., Cifter, F., Myronakis, M., Hurwitz, M. H., Williams, C. L., … Lewis, J. H. (2015). 4D cone beam CT-based dose assessment for SBRT lung cancer treatment. Physics in Medicine and Biology, 61(2), 554–568. doi:10.1088/0031-9155/61/2/554

Shieh, C.-C., Keall, P. J., Kuncic, Z., Huang, C.-Y., & Feain, I. (2015). Markerless tumor tracking using short kilovoltage imaging arcs for lung image-guided radiotherapy. Physics in Medicine and Biology, 60(24), 9437–9454. doi:10.1088/0031-9155/60/24/9437

[1]Andrei Shkarin et al., “An Open Source GPU Accelerated Framework for Flexible Algebraic Reconstruction at Synchrotron Light Sources,” FI, vol. 141, no. 2–3, pp. 259–274, Oct. 2015.

Bernchou, U., Hansen, O., Schytte, T., Bertelsen, A., Hope, A., Moseley, D., & Brink, C. (2015). Prediction of lung density changes after radiotherapy by cone beam computed tomography response markers and pre-treatment factors for non-small cell lung cancer patients. Radiotherapy and Oncology, 117(1), 17–22. doi:10.1016/j.radonc.2015.07.021

Moreira, A. H. J., Queirós, S., Morais, P., Rodrigues, N. F., Correia, A. R., Fernandes, V., … Vilaça, J. L. (2015). Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation. Medical Imaging 2015: Computer-Aided Diagnosis. doi:10.1117/12.2082806

Beaudry, J., Cropp, R., & Bergman, A. (2015). SU-E-J-153: Reconstructing 4D Cone Beam CT Images for Clinical QA of Lung SABR Treatments. Medical Physics, 42(6Part9), 3300–3300. doi:10.1118/1.4924238

Park, Y.-K., Sharp, G. C., Phillips, J., & Winey, B. A. (2015). Proton dose calculation on scatter-corrected CBCT image: Feasibility study for adaptive proton therapy. Medical Physics, 42(8), 4449–4459. doi:10.1118/1.4923179

Dhou, S., Hurwitz, M., Mishra, P., Cai, W., Rottmann, J., Li, R., … Lewis, J. H. (2015). 3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models. Physics in Medicine and Biology, 60(9), 3807–3824. doi:10.1088/0031-9155/60/9/3807

Fassi, A., Schaerer, J., Riboldi, M., Sarrut, D., & Baroni, G. (2015). An image-based method to synchronize cone-beam CT and optical surface tracking. Journal of Applied Clinical Medical Physics, 16(2), 117–128. doi:10.1120/jacmp.v16i2.5152

Shieh, C.-C., Kipritidis, J., O’Brien, R. T., Cooper, B. J., Kuncic, Z., & Keall, P. J. (2015). Improving thoracic four-dimensional cone-beam CT reconstruction with anatomical-adaptive image regularization (AAIR). Physics in Medicine and Biology, 60(2), 841–868. doi:10.1088/0031-9155/60/2/841

Cazoulat, G., Simon, A., Dumenil, A., Gnep, K., de Crevoisier, R., Acosta, O., & Haigron, P. (2014). Surface-Constrained Nonrigid Registration for Dose Monitoring in Prostate Cancer Radiotherapy. IEEE Transactions on Medical Imaging, 33(7), 1464–1474. doi:10.1109/tmi.2014.2314574

Leeser, M., Mukherjee, S., & Brock, J. (2014). Fast reconstruction of 3D volumes from 2D CT projection data with GPUs. BMC Research Notes, 7(1). doi:10.1186/1756-0500-7-582

Park, Y., Winey, B., & Sharp, G. (2014). SU-E-J-175: Proton Dose Calculation On Scatter-Corrected CBCT Image: Feasibility Study for Adaptive Proton Therapy. Medical Physics, 41(6Part9), 197–197. doi:10.1118/1.4888228

Shieh, C.-C., Kipritidis, J., O’Brien, R. T., Kuncic, Z., & Keall, P. J. (2014). Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing. Medical Physics, 41(4), 041912. doi:10.1118/1.4868510

Mory, C., Auvray, V., Zhang, B., Grass, M., Schäfer, D., Chen, S. J., … Boussel, L. (2014). Cardiac C-arm computed tomography using a 3D + time ROI reconstruction method with spatial and temporal regularization. Medical Physics, 41(2), 021903. doi:10.1118/1.4860215

Wang, M., Sharp, G. C., Rit, S., Delmon, V., & Wang, G. (2014). 2D/4D marker-free tumor tracking using 4D CBCT as the reference image. Physics in Medicine and Biology, 59(9), 2219–2233. doi:10.1088/0031-9155/59/9/2219

Rit, S., Dedes, G., Freud, N., Sarrut, D., & Létang, J. M. (2013). Filtered backprojection proton CT reconstruction along most likely paths. Medical Physics, 40(3), 031103. doi:10.1118/1.4789589

Delmon, V., Vandemeulebroucke, J., Pinho, R., Vila Oliva, M., Sarrut, D., & Rit, S. (2014). In-room breathing motion estimation from limited projection views using a sliding deformation model. Journal of Physics: Conference Series, 489, 012026. doi:10.1088/1742-6596/489/1/012026

Martin, J., McClelland, J., Yip, C., Thomas, C., Hartill, C., Ahmad, S., … Hawkes, D. (2013). Building motion models of lung tumours from cone-beam CT for radiotherapy applications. Physics in Medicine and Biology, 58(6), 1809–1822. doi:10.1088/0031-9155/58/6/1809