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For: Schmidt MA, Payne GS. Radiotherapy planning using MRI. Phys Med Biol 2015;60:R323-61. [PMID: 26509844 DOI: 10.1088/0031-9155/60/22/R323] [Cited by in Crossref: 177] [Cited by in F6Publishing: 184] [Article Influence: 25.3] [Reference Citation Analysis]
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1 Goodburn RJ, Philippens MEP, Lefebvre TL, Khalifa A, Bruijnen T, Freedman JN, Waddington DEJ, Younus E, Aliotta E, Meliadò G, Stanescu T, Bano W, Fatemi-Ardekani A, Wetscherek A, Oelfke U, van den Berg N, Mason RP, van Houdt PJ, Balter JM, Gurney-Champion OJ. The future of MRI in radiation therapy: challenges and opportunities for the MR community. Magn Reson Med 2022. [PMID: 36128894 DOI: 10.1002/mrm.29450] [Reference Citation Analysis]
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6 Kuah T, Vellayappan BA, Makmur A, Nair S, Song J, Tan JH, Kumar N, Quek ST, Hallinan JTPD. State-of-the-Art Imaging Techniques in Metastatic Spinal Cord Compression. Cancers (Basel) 2022;14:3289. [PMID: 35805059 DOI: 10.3390/cancers14133289] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
7 Tang S, Rai R, Vinod SK, Elwadia D, Forstner D, Moretti D, Tran T, Do V, King O, Lim K, Liney G, Goozee G, Holloway L. Rates of MRI simulator utilisation in a tertiary cancer therapy centre. J Med Imaging Radiat Oncol 2022. [PMID: 35687525 DOI: 10.1111/1754-9485.13422] [Reference Citation Analysis]
8 Jin H, Lee SY, An HJ, Choi CH, Chie EK, Wu HG, Park JM, Park S, Kim JI. Development of an anthropomorphic multimodality pelvic phantom for quantitative evaluation of a deep-learning-based synthetic computed tomography generation technique. J Appl Clin Med Phys 2022;:e13644. [PMID: 35579090 DOI: 10.1002/acm2.13644] [Reference Citation Analysis]
9 Masitho S, Putz F, Mengling V, Reißig L, Voigt R, Bäuerle T, Janka R, Fietkau R, Bert C. Accuracy of MRI-CT registration in brain stereotactic radiotherapy: Impact of MRI acquisition setup and registration method. Zeitschrift für Medizinische Physik 2022. [DOI: 10.1016/j.zemedi.2022.04.004] [Reference Citation Analysis]
10 Stouthandel MEJ, Pullens P, Bogaert S, Schoepen M, Vangestel C, Achten E, Veldeman L, Van Hoof T. Application of frozen Thiel-embalmed specimens for radiotherapy delineation guideline development: a method to create accurate MRI-enhanced CT datasets. Strahlenther Onkol. [DOI: 10.1007/s00066-022-01928-z] [Reference Citation Analysis]
11 Santoro M, Strolin S, Paolani G, Della Gala G, Bartoloni A, Giacometti C, Ammendolia I, Morganti AG, Strigari L. Recent Applications of Artificial Intelligence in Radiotherapy: Where We Are and Beyond. Applied Sciences 2022;12:3223. [DOI: 10.3390/app12073223] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
12 Pappas EP, Seimenis I, Kouris P, Theocharis S, Lampropoulos KI, Kollias G, Karaiskos P. Target localization accuracy in frame‐based stereotactic radiosurgery: Comparison between MR‐only and MR/CT co‐registration approaches. J Applied Clin Med Phys. [DOI: 10.1002/acm2.13580] [Reference Citation Analysis]
13 Sritharan K, Tree A. MR-guided radiotherapy for prostate cancer: state of the art and future perspectives. Br J Radiol 2022;95:20210800. [PMID: 35073158 DOI: 10.1259/bjr.20210800] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
14 Kato Y, Kamomae T, Kumagai M, Oie Y, Noguchi Y, Okudaira K, Kawamura M, Taoka T, Naganawa S. Hybrid 3D T1-weighted gradient-echo sequence for fiducial marker detection and tumor delineation via magnetic resonance imaging in liver stereotactic body radiation therapy. Physica Medica 2022;95:9-15. [DOI: 10.1016/j.ejmp.2022.01.003] [Reference Citation Analysis]
15 Laskar SG, Kakoti S. Modern Radiation Oncology: From IMRT to Particle Therapy—Present Status and the Days to Come. Indian J Med Paediatr Oncol. [DOI: 10.1055/s-0042-1742446] [Reference Citation Analysis]
16 Metzner E, Bäumer C, Behrends C, Dammene Debbih A, Döhler D, van Goethem M, van der Graaf E, Kahle P, Lühr A, Teichmann T, Timmermann B, Weinberger D, Werner T, Wulff J, Kormoll T. Spectral fiber dosimetry with beryllium oxide for quality assurance in hadron radiation therapy. J Inst 2022;17:P02009. [DOI: 10.1088/1748-0221/17/02/p02009] [Reference Citation Analysis]
17 Cardenas CE, Blinde SE, Mohamed ASR, Ng SP, Raaijmakers C, Philippens M, Kotte A, Al-Mamgani AA, Karam I, Thomson DJ, Robbins J, Newbold K, Fuller CD, Terhaard C, On Behalf Of The, Bahig H, Blanchard P, Dehnad H, Doornaert P, Elhalawani H, Frank SJ, Garden A, Gunn GB, Hamming-Vrieze O, Kamal M, Kasperts N, Lee LW, McDonald BA, McPartlin A, Meheissen MA, Morrison WH, Navran A, Nutting CM, Pameijer F, Phan J, Poon I, Rosenthal DI, Smid EJ, Sykes AJ. Comprehensive Quantitative Evaluation of Variability in MR-guided Delineation of Oropharyngeal Gross Tumor Volumes and High-risk Clinical Target Volumes: An R-IDEAL Stage 0 Prospective Study. Int J Radiat Oncol Biol Phys 2022:S0360-3016(22)00096-7. [PMID: 35124134 DOI: 10.1016/j.ijrobp.2022.01.050] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
18 Wang Y, Li C, Yin G, Wang J, Li J, Wang P, Bian J. Extraction parameter optimized radiomics for neoadjuvant chemotherapy response prognosis in advanced nasopharyngeal carcinoma. Clin Transl Radiat Oncol 2022;33:37-44. [PMID: 35024463 DOI: 10.1016/j.ctro.2021.12.005] [Reference Citation Analysis]
19 Li Y, Xiao F, Liu B, Qi M, Lu X, Cai J, Zhou L, Song T. Deep learning-based 3Din vivodose reconstruction with an electronic portal imaging device for magnetic resonance-linear accelerators: a proof of concept study. Phys Med Biol 2021;66. [PMID: 34798623 DOI: 10.1088/1361-6560/ac3b66] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
20 Xie H, Lei Y, Wang T, Roper J, Dhabaan AH, Bradley JD, Liu T, Mao H, Yang X. Synthesizing high-resolution magnetic resonance imaging using parallel cycle-consistent generative adversarial networks for fast magnetic resonance imaging. Med Phys 2021. [PMID: 34821395 DOI: 10.1002/mp.15380] [Reference Citation Analysis]
21 Bird D, Nix MG, McCallum H, Teo M, Gilbert A, Casanova N, Cooper R, Buckley DL, Sebag-Montefiore D, Speight R, Al-Qaisieh B, Henry AM. The benefit of MR-only radiotherapy treatment planning for anal and rectal cancers: A planning study. J Appl Clin Med Phys 2021;22:41-53. [PMID: 34687138 DOI: 10.1002/acm2.13423] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
22 Clark RA, Garman ZG, Price RJ, Sheybani ND. Functional intersections between extracellular vesicles and oncolytic therapies. Trends Pharmacol Sci 2021;42:883-96. [PMID: 34598797 DOI: 10.1016/j.tips.2021.09.001] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
23 Olberg S, Chun J, Su Choi B, Park I, Kim H, Kim T, Sung Kim J, Green O, Park JC. Abdominal synthetic CT reconstruction with intensity projection prior for MRI-only adaptive radiotherapy. Phys Med Biol 2021;66. [PMID: 34530421 DOI: 10.1088/1361-6560/ac279e] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
24 Ding H, Velasco C, Ye H, Lindner T, Grech-Sollars M, O'Callaghan J, Hiley C, Chouhan MD, Niendorf T, Koh DM, Prieto C, Adeleke S. Current Applications and Future Development of Magnetic Resonance Fingerprinting in Diagnosis, Characterization, and Response Monitoring in Cancer. Cancers (Basel) 2021;13:4742. [PMID: 34638229 DOI: 10.3390/cancers13194742] [Reference Citation Analysis]
25 Olanloye EE, Ramlaul A, Ntekim AI, Adeyemi SS. FDG-PET/CT and MR imaging for target volume delineation in rectal cancer radiotherapy treatment planning: a systematic review. J Radiother Pract. [DOI: 10.1017/s1460396921000388] [Reference Citation Analysis]
26 Jiang X, Ma J, Xiao G, Shao Z, Guo X. A review of multimodal image matching: Methods and applications. Information Fusion 2021;73:22-71. [DOI: 10.1016/j.inffus.2021.02.012] [Cited by in Crossref: 26] [Cited by in F6Publishing: 44] [Article Influence: 26.0] [Reference Citation Analysis]
27 Yousefi Moteghaed N, Mostaar A, Azadeh P. Generating pseudo-computerized tomography (P-CT) scan images from magnetic resonance imaging (MRI) images using machine learning algorithms based on fuzzy theory for radiotherapy treatment planning. Med Phys 2021;48:7016-27. [PMID: 34418104 DOI: 10.1002/mp.15174] [Reference Citation Analysis]
28 Keyriläinen J, Sjöblom O, Turnbull-Smith S, Hovirinta T, Minn H. Clinical experience and cost evaluation of magnetic resonance imaging -only workflow in radiation therapy planning of prostate cancer. Phys Imaging Radiat Oncol 2021;19:66-71. [PMID: 34307921 DOI: 10.1016/j.phro.2021.07.004] [Reference Citation Analysis]
29 Xue H, Qiu B, Wang H, Jiang P, Sukocheva O, Fan R, Xue L, Wang J. Stereotactic Ablative Brachytherapy: Recent Advances in Optimization of Radiobiological Cancer Therapy. Cancers (Basel) 2021;13:3493. [PMID: 34298703 DOI: 10.3390/cancers13143493] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
30 Hou KY, Lu HY, Yang CC. Applying MRI Intensity Normalization on Non-Bone Tissues to Facilitate Pseudo-CT Synthesis from MRI. Diagnostics (Basel) 2021;11:816. [PMID: 33946436 DOI: 10.3390/diagnostics11050816] [Reference Citation Analysis]
31 Li Y, Li W, Xiong J, Xia J, Xie Y. Comparison of Supervised and Unsupervised Deep Learning Methods for Medical Image Synthesis between Computed Tomography and Magnetic Resonance Images. Biomed Res Int 2020;2020:5193707. [PMID: 33204701 DOI: 10.1155/2020/5193707] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 6.0] [Reference Citation Analysis]
32 Freedman JN, Gurney-Champion OJ, Nill S, Shiarli AM, Bainbridge HE, Mandeville HC, Koh DM, McDonald F, Kachelrieß M, Oelfke U, Wetscherek A. Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula. Radiother Oncol 2021;159:209-17. [PMID: 33812914 DOI: 10.1016/j.radonc.2021.03.034] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
33 Cardenas CE, Mohamed ASR, Yang J, Gooding M, Veeraraghavan H, Kalpathy-Cramer J, Ng SP, Ding Y, Wang J, Lai SY, Fuller CD, Sharp G. Head and neck cancer patient images for determining auto-segmentation accuracy in T2-weighted magnetic resonance imaging through expert manual segmentations. Med Phys 2020;47:2317-22. [PMID: 32418343 DOI: 10.1002/mp.13942] [Cited by in Crossref: 5] [Cited by in F6Publishing: 9] [Article Influence: 5.0] [Reference Citation Analysis]
34 Tang B, Wu F, Fu Y, Wang X, Wang P, Orlandini LC, Li J, Hou Q. Dosimetric evaluation of synthetic CT image generated using a neural network for MR-only brain radiotherapy. J Appl Clin Med Phys 2021;22:55-62. [PMID: 33527712 DOI: 10.1002/acm2.13176] [Cited by in Crossref: 2] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
35 Mengling V, Putz F, Laun FB, Perrin R, Eisenhut F, Dörfler A, Fietkau R, Bert C. Evaluation of the influence of susceptibility-induced magnetic field distortions on the precision of contouring intracranial organs at risk for stereotactic radiosurgery. Phys Imaging Radiat Oncol 2020;15:91-7. [PMID: 33458332 DOI: 10.1016/j.phro.2020.08.001] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
36 McDonald BA, Vedam S, Yang J, Wang J, Castillo P, Lee B, Sobremonte A, Ahmed S, Ding Y, Mohamed ASR, Balter P, Hughes N, Thorwarth D, Nachbar M, Philippens MEP, Terhaard CHJ, Zips D, Böke S, Awan MJ, Christodouleas J, Fuller CD; MR-Linac Consortium Head and Neck Tumor Site Group. Initial Feasibility and Clinical Implementation of Daily MR-Guided Adaptive Head and Neck Cancer Radiation Therapy on a 1.5T MR-Linac System: Prospective R-IDEAL 2a/2b Systematic Clinical Evaluation of Technical Innovation. Int J Radiat Oncol Biol Phys 2021;109:1606-18. [PMID: 33340604 DOI: 10.1016/j.ijrobp.2020.12.015] [Cited by in Crossref: 1] [Cited by in F6Publishing: 14] [Article Influence: 0.5] [Reference Citation Analysis]
37 Tocco BR, Kishan AU, Ma TM, Kerkmeijer LGW, Tree AC. MR-Guided Radiotherapy for Prostate Cancer. Front Oncol 2020;10:616291. [PMID: 33363041 DOI: 10.3389/fonc.2020.616291] [Cited by in Crossref: 8] [Cited by in F6Publishing: 24] [Article Influence: 4.0] [Reference Citation Analysis]
38 Kavaluus H, Seppälä T, Koivula L, Salli E, Collan J, Saarilahti K, Tenhunen M. Retrospective four-dimensional magnetic resonance imaging of liver: Method development. J Appl Clin Med Phys 2020;21:304-13. [PMID: 33270997 DOI: 10.1002/acm2.13108] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
39 Clement P, Booth T, Borovečki F, Emblem KE, Figueiredo P, Hirschler L, Jančálek R, Keil VC, Maumet C, Özsunar Y, Pernet C, Petr J, Pinto J, Smits M, Warnert EAH. GliMR: Cross-Border Collaborations to Promote Advanced MRI Biomarkers for Glioma. J Med Biol Eng 2020;:1-11. [PMID: 33293909 DOI: 10.1007/s40846-020-00582-z] [Cited by in Crossref: 1] [Cited by in F6Publishing: 6] [Article Influence: 0.5] [Reference Citation Analysis]
40 Dai X, Lei Y, Liu Y, Wang T, Ren L, Curran WJ, Patel P, Liu T, Yang X. Intensity non-uniformity correction in MR imaging using residual cycle generative adversarial network. Phys Med Biol 2020;65:215025. [PMID: 33245059 DOI: 10.1088/1361-6560/abb31f] [Cited by in Crossref: 5] [Cited by in F6Publishing: 9] [Article Influence: 2.5] [Reference Citation Analysis]
41 Mengling V, Bert C, Perrin R, Masitho S, Weissmann T, Mansoorian S, Siavooshhaghighi H, Janka R, Doussin S, Habatsch M, Fietkau R, Putz F. Implementation of a dedicated 1.5 T MR scanner for radiotherapy treatment planning featuring a novel high-channel coil setup for brain imaging in treatment position. Strahlenther Onkol 2021;197:246-56. [PMID: 33103231 DOI: 10.1007/s00066-020-01703-y] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
42 Singhrao K, Fu J, Parikh NR, Mikaeilian AG, Ruan D, Kishan AU, Lewis JH. A generative adversarial network‐based (GAN‐based) architecture for automatic fiducial marker detection in prostate MRI‐only radiotherapy simulation images. Med Phys 2020;47:6405-13. [DOI: 10.1002/mp.14498] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
43 H Morris R, R Geraldi N, C Pike L, Pawelke J, L Hoffmann A, Doy N, L Stafford J, Spicer A, I Newton M. Advanced Sandwich Composite Cores for Patient Support in Advanced Clinical Imaging and Oncology Treatment. Materials (Basel) 2020;13:E3549. [PMID: 32806610 DOI: 10.3390/ma13163549] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
44 Groot Koerkamp ML, Vasmel JE, Russell NS, Shaitelman SF, Anandadas CN, Currey A, Vesprini D, Keller BM, De-Colle C, Han K, Braunstein LZ, Mahmood F, Lorenzen EL, Philippens MEP, Verkooijen HM, Lagendijk JJW, Houweling AC, van den Bongard HJGD, Kirby AM. Optimizing MR-Guided Radiotherapy for Breast Cancer Patients. Front Oncol 2020;10:1107. [PMID: 32850318 DOI: 10.3389/fonc.2020.01107] [Cited by in Crossref: 8] [Cited by in F6Publishing: 16] [Article Influence: 4.0] [Reference Citation Analysis]
45 Yousefi Moteghaed N, Mostaar A, Maghooli K, Houshyari M, Ameri A. Estimation and evaluation of pseudo-CT images using linear regression models and texture feature extraction from MRI images in the brain region to design external radiotherapy planning. Rep Pract Oncol Radiother 2020;25:738-45. [PMID: 32684863 DOI: 10.1016/j.rpor.2020.05.005] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
46 Alzahrani M, Broadbent DA, Chuter R, Al-Qaisieh B, Jackson S, Michael H, Johnstone RI, Shah S, Wetscherek A, Chick HJ, Wyatt JJ, McCallum HM, Speight R. Audit feasibility for geometric distortion in magnetic resonance imaging for radiotherapy. Phys Imaging Radiat Oncol 2020;15:80-4. [PMID: 33163632 DOI: 10.1016/j.phro.2020.07.004] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
47 Savenije MHF, Maspero M, Sikkes GG, van der Voort van Zyp JRN, T J Kotte AN, Bol GH, T van den Berg CA. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy. Radiat Oncol. 2020;15:104. [PMID: 32393280 DOI: 10.1186/s13014-020-01528-0] [Cited by in Crossref: 13] [Cited by in F6Publishing: 21] [Article Influence: 6.5] [Reference Citation Analysis]
48 Persson E, Jamtheim Gustafsson C, Ambolt P, Engelholm S, Ceberg S, Bäck S, Olsson LE, Gunnlaugsson A. MR-PROTECT: Clinical feasibility of a prostate MRI-only radiotherapy treatment workflow and investigation of acceptance criteria. Radiat Oncol 2020;15:77. [PMID: 32272943 DOI: 10.1186/s13014-020-01513-7] [Cited by in Crossref: 9] [Cited by in F6Publishing: 12] [Article Influence: 4.5] [Reference Citation Analysis]
49 Schmitt D, Blanck O, Gauer T, Fix MK, Brunner TB, Fleckenstein J, Loutfi-Krauss B, Manser P, Werner R, Wilhelm ML, Baus WW, Moustakis C. Technological quality requirements for stereotactic radiotherapy : Expert review group consensus from the DGMP Working Group for Physics and Technology in Stereotactic Radiotherapy. Strahlenther Onkol 2020;196:421-43. [PMID: 32211939 DOI: 10.1007/s00066-020-01583-2] [Cited by in Crossref: 20] [Cited by in F6Publishing: 36] [Article Influence: 10.0] [Reference Citation Analysis]
50 Putz F, Mengling V, Perrin R, Masitho S, Weissmann T, Rösch J, Bäuerle T, Janka R, Cavallaro A, Uder M, Amarteifio P, Doussin S, Schmidt MA, Dörfler A, Semrau S, Lettmaier S, Fietkau R, Bert C. Magnetic resonance imaging for brain stereotactic radiotherapy : A review of requirements and pitfalls. Strahlenther Onkol 2020;196:444-56. [PMID: 32206842 DOI: 10.1007/s00066-020-01604-0] [Cited by in Crossref: 11] [Cited by in F6Publishing: 20] [Article Influence: 5.5] [Reference Citation Analysis]
51 Kuisma A, Ranta I, Keyriläinen J, Suilamo S, Wright P, Pesola M, Warner L, Löyttyniemi E, Minn H. Validation of automated magnetic resonance image segmentation for radiation therapy planning in prostate cancer. Phys Imaging Radiat Oncol 2020;13:14-20. [PMID: 33458302 DOI: 10.1016/j.phro.2020.02.004] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
52 Gurney-Champion OJ, Mahmood F, van Schie M, Julian R, George B, Philippens MEP, van der Heide UA, Thorwarth D, Redalen KR. Quantitative imaging for radiotherapy purposes. Radiother Oncol 2020;146:66-75. [PMID: 32114268 DOI: 10.1016/j.radonc.2020.01.026] [Cited by in Crossref: 25] [Cited by in F6Publishing: 31] [Article Influence: 12.5] [Reference Citation Analysis]
53 Eppenhof KAJ, Maspero M, Savenije MHF, de Boer JCJ, van der Voort van Zyp JRN, Raaymakers BW, Raaijmakers AJE, Veta M, van den Berg CAT, Pluim JPW. Fast contour propagation for MR-guided prostate radiotherapy using convolutional neural networks. Med Phys. 2020;47:1238-1248. [PMID: 31876300 DOI: 10.1002/mp.13994] [Cited by in Crossref: 7] [Cited by in F6Publishing: 11] [Article Influence: 3.5] [Reference Citation Analysis]
54 Cho IJ, Chung WK, Lee JK, Lee MC, Paek J, Kim YH, Jeong JU, Yoon MS, Song JY, Nam TK, Ahn SJ, Lee DH, Yoon TM, Lim SC. Intensity-modulated radiotherapy for stage I glottic cancer: a short-term outcomes compared with three-dimensional conformal radiotherapy. Radiat Oncol J 2019;37:271-8. [PMID: 31918465 DOI: 10.3857/roj.2019.00283] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 1.3] [Reference Citation Analysis]
55 Osman SOS, Russell E, King RB, Crowther K, Jain S, McGrath C, Hounsell AR, Prise KM, McGarry CK. Fiducial markers visibility and artefacts in prostate cancer radiotherapy multi-modality imaging. Radiat Oncol 2019;14:237. [PMID: 31878967 DOI: 10.1186/s13014-019-1447-1] [Cited by in Crossref: 4] [Cited by in F6Publishing: 7] [Article Influence: 1.3] [Reference Citation Analysis]
56 Eccles CL, Adair Smith G, Bower L, Hafeez S, Herbert T, Hunt A, McNair HA, Ofuya M, Oelfke U, Nill S, Huddart RA; PRIMER TMG. Magnetic resonance imaging sequence evaluation of an MR Linac system; early clinical experience. Tech Innov Patient Support Radiat Oncol 2019;12:56-63. [PMID: 32095556 DOI: 10.1016/j.tipsro.2019.11.004] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
57 Dwihapsari Y, Asdiantoro E, Maulidiyah N. On the Assessment of Image Inhomogeneity Using T2 Magnetic Resonance Imaging in Head Phantom for Radiotherapy Treatment Planning: Preliminary Study. Appl Magn Reson 2020;51:59-69. [DOI: 10.1007/s00723-019-01177-x] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
58 Wang Y, Liu C, Zhang X, Deng W. Synthetic CT Generation Based on T2 Weighted MRI of Nasopharyngeal Carcinoma (NPC) Using a Deep Convolutional Neural Network (DCNN). Front Oncol 2019;9:1333. [PMID: 31850218 DOI: 10.3389/fonc.2019.01333] [Cited by in Crossref: 15] [Cited by in F6Publishing: 24] [Article Influence: 5.0] [Reference Citation Analysis]
59 Johnstone RI, Guerrero-Urbano T, Michaelidou A, Greener T, Miles E, Eaton D, Thomas C. Guidance on the use of MRI for treatment planning in radiotherapy clinical trials. Br J Radiol 2020;93:20190161. [PMID: 31724876 DOI: 10.1259/bjr.20190161] [Reference Citation Analysis]
60 Shafai-Erfani G, Lei Y, Liu Y, Wang Y, Wang T, Zhong J, Liu T, McDonald M, Curran WJ, Zhou J, Shu HK, Yang X. MRI-Based Proton Treatment Planning for Base of Skull Tumors. Int J Part Ther 2019;6:12-25. [PMID: 31998817 DOI: 10.14338/IJPT-19-00062.1] [Cited by in Crossref: 8] [Cited by in F6Publishing: 11] [Article Influence: 2.7] [Reference Citation Analysis]
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