Citations Report

Imaging in Medicine : Citations & Metrics Report

Articles published in Imaging in Medicine have been cited by esteemed scholars and scientists all around the world.

Imaging in Medicine has got h-index 25, which means every article in Imaging in Medicine has got 25 average citations.

Following are the list of articles that have cited the articles published in Imaging in Medicine.

• Chicheportiche A, Goshen E, Godefroy J, Grozinsky-Glasberg S, Oleinikov K, Meirovitz A, Gross DJ, Ben-Haim S. Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68 Ga-DOTATATE PET/CT studies?. EJNMMI physics. 2021 Dec;8(1):1-7. View at Publisher | View at Google Scholar | View at Indexing
• Chicheportiche A, Goshen E, Godefroy J, Grozinsky-Glasberg S, Oleinikov K, Meirovitz A, Gross DJ, Ben-Haim S. Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68 Ga-DOTATATE PET/CT studies?. EJNMMI physics. 2021 Dec;8(1):1-7. View at Publisher | View at Google Scholar | View at Indexing
• Smith AL, Barnes A. 18 F-FDG PET/CT: Brain Imaging. InPET/CT in Brain Disorders 2019 (pp. 23-36). Springer, Cham. View at Publisher | View at Google Scholar | View at Indexing
• Belcari N, Boellaard R, Morrocchi M. PET/CT and PET/MR Tomographs: Image Acquisition and Processing. InNuclear Medicine Textbook 2019 (pp. 199-217). Springer, Cham. View at Publisher | View at Google Scholar | View at Indexing
• Koš?evi? AG, Petrinovi? D. Extra-low-dose 2D PET imaging. In2021 12th International Symposium on Image and Signal Processing and Analysis (ISPA) 2021 Sep 13 (pp. 84-90). IEEE. View at Publisher | View at Google Scholar | View at Indexing
• Wu Z, Guo B, Huang B, Hao X, Wu P, Zhao B, Qin Z, Xie J, Li S. Phantom and clinical assessment of small pulmonary nodules using Q. Clear reconstruction on a silicon-photomultiplier-based time-of-flight PET/CT system. Scientific Reports. 2021 May 14;11(1):1-9. View at Publisher | View at Google Scholar | View at Indexing
• Qi W, Yang L, Chan C, Asma E. Accurate PET Projector Approximations using Ray-Driven Projectors with Image Domain PSF Modeling. In2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) (pp. 1-3). IEEE. View at Publisher | View at Google Scholar | View at Indexing
• Markiewicz PJ, Matthews JC, Ashburner J, Cash DM, Thomas DL, De Vita E, Barnes A, Cardoso MJ, Modat M, Brown R, Thielemans K. Uncertainty analysis of MR-PET image registration for precision neuro-PET imaging. NeuroImage. 2021 May 15;232:117821. View at Publisher | View at Google Scholar | View at Indexing
• Walker KA, Bilgel M. PET Neuroimaging of Neurologic Disease: Methods, Clinical and Research Applications. View at Publisher | View at Google Scholar | View at Indexing
• Zhu YM. Ordered subset expectation maximization algorithm for positron emission tomographic image reconstruction using belief kernels. Journal of Medical Imaging. 2018 Nov;5(4):044005. View at Publisher | View at Google Scholar | View at Indexing
• Lizunov A, Khilchenko A, Moiseev D, Zubarev P. Optical tomography diagnostic for study of neutral plasma component in the gas dynamic trap. arXiv preprint arXiv:2102.10945. 2021 Feb 22. View at Publisher | View at Google Scholar | View at Indexing
• Lizunov A, Khilchenko A, Moiseev D, Zubarev P. Optical tomography diagnostic for study of neutral plasma component in the gas dynamic trap. arXiv preprint arXiv:2102.10945. 2021 Feb 22. View at Publisher | View at Google Scholar | View at Indexing
• Cascio D, Fauci F, Iacomi M, Raso G, Magro R, Castrogiovanni D, Filosto G, Ienzi R, Vasile MS. Computer-aided diagnosis in digital mammography: comparison of two commercial systems. Imaging in Medicine. 2014 Feb 1;6(1):13-20. View at Publisher | View at Google Scholar | View at Indexing
• Rangarajan AA. MULTIMODAL MAGNETIC RESONANCE IMAGING PREDICTS REGIONAL AMYLOID BURDEN IN THE BRAIN: A PATTERN RECOGNITION APPROACH TO AMYLOID PREDICTION (Doctoral dissertation, University of Pittsburgh). View at Publisher | View at Google Scholar | View at Indexing
• Øynes M, Strøm B, Tveito B, Hafslund B. Digital zoom of the full-field digital mammogram versus magnification mammography: a systematic review. European radiology. 2020 Aug;30(8):4223-33. View at Publisher | View at Google Scholar | View at Indexing
• Chakravorty A, Steel T, Chaganti J. Accuracy of percentage of signal intensity recovery and relative cerebral blood volume derived from dynamic susceptibility-weighted, contrast-enhanced MRI in the preoperative diagnosis of cerebral tumours. The neuroradiology journal. 2015 Dec;28(6):574-83. View at Publisher | View at Google Scholar | View at Indexing
• Pinto SO, Narciso L, da Silva AM. Optimization of reconstruction parameters in [18F] FDG PET brain images aiming scan time reduction. Brazilian Journal of Physics Medicine (Online). 2021. View at Publisher | View at Google Scholar | View at Indexing
• Fink AZ, Mogil LB, Lipton ML. Advanced neuroimaging in the clinic: critical appraisal of the evidence base. The British journal of radiology. 2016 Aug;89(1064):20150753. View at Publisher | View at Google Scholar | View at Indexing
• Alkanhal H, Das K, Poptani H. Diffusion-and Perfusion-Weighted Magnetic Resonance Imaging Methods in Nonenhancing Gliomas. World Neurosurgery. 2020 Sep 1;141:123-30. View at Publisher | View at Google Scholar | View at Indexing
• Cruz-Roa A, Arévalo J, Basavanhally A, Madabhushi A, González F. A comparative evaluation of supervised and unsupervised representation learning approaches for anaplastic medulloblastoma differentiation. In10th International Symposium on Medical Information Processing and Analysis 2015 Jan 28 (Vol. 9287, p. 92870G). International Society for Optics and Photonics. View at Publisher | View at Google Scholar | View at Indexing
• Cheok S, Hansen JE, Chiang VL. Recognition and Management of Adverse Radiation Effects. InIntracranial Stereotactic Radiosurgery (pp. 391-404). CRC Press. View at Publisher | View at Google Scholar | View at Indexing
• Otálora S, Atzori M, Andrearczyk V, Khan A, Müller H. Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology. Frontiers in bioengineering and biotechnology. 2019 Aug 23;7:198. View at Publisher | View at Google Scholar | View at Indexing
• Kang H, Kiess A, Chung CH. Emerging biomarkers in head and neck cancer in the era of genomics. Nature reviews Clinical oncology. 2015 Jan;12(1):11-26. View at Publisher | View at Google Scholar | View at Indexing
• Pak K, Cheon GJ, Nam HY, Kim SJ, Kang KW, Chung JK, Kim EE, Lee DS. Prognostic value of metabolic tumor volume and total lesion glycolysis in head and neck cancer: a systematic review and meta-analysis. Journal of Nuclear Medicine. 2014 Jun 1;55(6):884-90. View at Publisher | View at Google Scholar | View at Indexing
• Braicu C, Tomuleasa C, Monroig P, Cucuianu A, Berindan-Neagoe I, Calin GA. Exosomes as divine messengers: are they the Hermes of modern molecular oncology?. Cell Death & Differentiation. 2015 Jan;22(1):34-45. View at Publisher | View at Google Scholar | View at Indexing
• Im HJ, Pak K, Cheon GJ, Kang KW, Kim SJ, Kim IJ, Chung JK, Kim EE, Lee DS. Prognostic value of volumetric parameters of 18 F-FDG PET in non-small-cell lung cancer: a meta-analysis. European journal of nuclear medicine and molecular imaging. 2015 Feb;42(2):241-51. View at Publisher | View at Google Scholar | View at Indexing
• Liu J, Dong M, Sun X, Li W, Xing L, Yu J. Prognostic value of 18F-FDG PET/CT in surgical non-small cell lung cancer: a meta-analysis. PloS one. 2016 Jan 4;11(1):e0146195. View at Publisher | View at Google Scholar | View at Indexing
• Shivamurthy VK, Tahari AK, Marcus C, Subramaniam RM. Brain FDG PET and the diagnosis of dementia. American Journal of Roentgenology. 2015 Jan;204(1):W76-85. View at Publisher | View at Google Scholar | View at Indexing
• Marcus C, Ciarallo A, Tahari AK, Mena E, Koch W, Wahl RL, Kiess AP, Kang H, Subramaniam RM. Head and neck PET/CT: therapy response interpretation criteria (Hopkins criteria)—interreader reliability, accuracy, and survival outcomes. Journal of Nuclear Medicine. 2014 Sep 1;55(9):1411-6. View at Publisher | View at Google Scholar | View at Indexing
• Marcus C, Whitworth PW, Surasi DS, Pai SI, Subramaniam RM. PET/CT in the management of thyroid cancers. American Journal of Roentgenology. 2014 Jun;202(6):1316-29. View at Publisher | View at Google Scholar | View at Indexing
• Otálora S, Atzori M, Andrearczyk V, Khan A, Müller H. Staining invariant features for improving generalization of deep convolutional neural networks in computational pathology. Frontiers in bioengineering and biotechnology. 2019 Aug 23;7:198. View at Publisher | View at Google Scholar | View at Indexing
• Bogowicz M, Riesterer O, Stark LS, Studer G, Unkelbach J, Guckenberger M, Tanadini-Lang S. Comparison of PET and CT radiomics for prediction of local tumor control in head and neck squamous cell carcinoma. Acta oncologica. 2017 Nov 2;56(11):1531-6. View at Publisher | View at Google Scholar | View at Indexing
• Manera M, Dezfuli BS, DePasquale JA, Giari L. Multivariate approach to gill pathology in European sea bass after experimental exposure to cadmium and terbuthylazine. Ecotoxicology and environmental safety. 2016 Jul 1;129:282-90. View at Publisher | View at Google Scholar | View at Indexing
• Tahari AK, Alluri K, Quon H, Koch W, Wahl RL, Subramaniam RM. FDG PET/CT imaging of Oropharyngeal SCC: Characteristics of HPV positive and negative tumors. Clinical nuclear medicine. 2014 Mar;39(3):225. View at Publisher | View at Google Scholar | View at Indexing
• Nirschl JJ, Janowczyk A, Peyster EG, Frank R, Margulies KB, Feldman MD, Madabhushi A. Deep learning tissue segmentation in cardiac histopathology images. InDeep learning for medical image analysis 2017 Jan 1 (pp. 179-195). Academic Press. View at Publisher | View at Google Scholar | View at Indexing
• Held C, Nattkemper T, Palmisano R, Wittenberg T. Approaches to automatic parameter fitting in a microscopy image segmentation pipeline: An exploratory parameter space analysis. Journal of pathology informatics. 2013;4(Suppl). View at Publisher | View at Google Scholar | View at Indexing
• Samstein RM, Carvajal RD, Postow MA, Callahan MK, Shoushtari AN, Patel SG, Lee NY, Barker CA. Localized sinonasal mucosal melanoma: outcomes and associations with stage, radiotherapy, and positron emission tomography response. Head & neck. 2016 Sep;38(9):1310-7. View at Publisher | View at Google Scholar | View at Indexing
• Dahiya K, Dhankhar R. Updated overview of current biomarkers in head and neck carcinoma. World journal of methodology. 2016 Mar 26;6(1):77. View at Publisher | View at Google Scholar | View at Indexing
• Alluri KC, Tahari AK, Wahl RL, Koch W, Chung CH, Subramaniam RM. Prognostic value of FDG PET metabolic tumor volume in human papillomavirus–positive stage III and IV oropharyngeal squamous cell carcinoma. AJR. American journal of roentgenology. 2014 Oct;203(4):897. View at Publisher | View at Google Scholar | View at Indexing
• Sparks R, Madabhushi A. Gleason grading of prostate histology utilizing manifold regularization via statistical shape model of manifolds. InMedical Imaging 2012: Computer-Aided Diagnosis 2012 Feb 23 (Vol. 8315, p. 83151J). International Society for Optics and Photonics. View at Publisher | View at Google Scholar | View at Indexing
• Economopoulou P, de Bree R, Kotsantis I, Psyrri A. Diagnostic tumor markers in head and neck squamous cell carcinoma (HNSCC) in the clinical setting. Frontiers in oncology. 2019 Aug 29;9:827. View at Publisher | View at Google Scholar | View at Indexing
• Rony J, Belharbi S, Dolz J, Ayed IB, McCaffrey L, Granger E. Deep weakly-supervised learning methods for classification and localization in histology images: a survey. arXiv preprint arXiv:1909.03354. 2019 Sep 8. View at Publisher | View at Google Scholar | View at Indexing
• Perng P, Marcus C, Subramaniam RM. 18F-FDG PET/CT and melanoma: staging, immune modulation and mutation-targeted therapy assessment, and prognosis. American Journal of Roentgenology. 2015 Aug;205(2):259-70. View at Publisher | View at Google Scholar | View at Indexing
• Paidpally V, Tahari AK, Lam S, Alluri K, Marur S, Koch W, Wahl RL, Subramaniam RM. Addition of 18F-FDG PET/CT to clinical assessment predicts overall survival in HNSCC: a retrospective analysis with follow-up for 12 years. Journal of Nuclear Medicine. 2013 Dec 1;54(12):2039-45. View at Publisher | View at Google Scholar | View at Indexing
• Russell H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, Maryland View at Publisher | View at Google Scholar | View at Indexing
• Schäfer A. Axiomatisation and decidability of multi-dimensional duration calculus. Information and Computation. 2007 Jan 1;205(1):25-64. View at Publisher | View at Google Scholar | View at Indexing
• Subramaniam RM, Alluri KC, Tahari AK, Aygun N, Quon H. PET/CT imaging and human papilloma virus–positive oropharyngeal squamous cell cancer: evolving clinical imaging paradigm. Journal of Nuclear Medicine. 2014 Mar 1;55(3):431-8. View at Publisher | View at Google Scholar | View at Indexing
• Sheikhbahaei S, Marcus C, Hafezi-Nejad N, Taghipour M, Subramaniam RM. Value of FDG PET/CT in patient management and outcome of skeletal and soft tissue sarcomas. PET clinics. 2015 Jul 1;10(3):375-93. View at Publisher | View at Google Scholar | View at Indexing
• Mena E, Taghipour M, Sheikhbahaei S, Jha AK, Rahmim A, Solnes L, Subramaniam RM. Value of intra-tumoral metabolic heterogeneity and quantitative 18F-FDG PET/CT parameters to predict prognosis, in patients with HPV-positive primary oropharyngeal squamous cell carcinoma. Clinical nuclear medicine. 2017 May;42(5):e227. View at Publisher | View at Google Scholar | View at Indexing
• Parikh U, Marcus C, Sarangi R, Taghipour M, Subramaniam RM. FDG PET/CT in pancreatic and hepatobiliary carcinomas: value to patient management and patient outcomes. PET clinics. 2015 Jul 1;10(3):327-43. View at Publisher | View at Google Scholar | View at Indexing