Number | Cited Articles |
1 |
Pau Xiberta, Anton Bardera, Imma Boada, Marina Gispert, Albert Brun, Maria Font-i-Furnols. Evaluation of an automatic lean meat percentage quantification method based on a partial volume model from computed tomography scans. Computers and Electronics in Agriculture 2018; 151: 365 doi: 10.1016/j.compag.2018.06.019
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2 |
Marcello Moccia, Nicola Valsecchi, Olga Ciccarelli, Ronald Van Schijndel, Frederik Barkhof, Ferran Prados. Spinal cord atrophy in a primary progressive multiple sclerosis trial: Improved sample size using GBSI. NeuroImage: Clinical 2020; 28: 102418 doi: 10.1016/j.nicl.2020.102418
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3 |
Debra F. McGivney, Rasim Boyacıoğlu, Yun Jiang, Megan E. Poorman, Nicole Seiberlich, Vikas Gulani, Kathryn E. Keenan, Mark A. Griswold, Dan Ma. Magnetic resonance fingerprinting review part 2: Technique and directions. Journal of Magnetic Resonance Imaging 2020; 51(4): 993 doi: 10.1002/jmri.26877
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4 |
Jingjing Wang, Changjun Hu, Huaqiang Xu, Yan Leng, Liren Zhang, Yuefeng Zhao. A novel multi-atlas and multi-channel (MAMC) approach for multiple sclerosis lesion segmentation in brain MRI. Signal, Image and Video Processing 2019; 13(5): 1019 doi: 10.1007/s11760-019-01440-5
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5 |
Soonchan Park, Joon Jang, Jang-Hoon Oh, Chang-Woo Ryu, Geon-Ho Jahng. Assessment of the Cerebrospinal Fluid Effect on the Chemical Exchange Saturation Transfer Map Obtained from the Full Z-Spectrum in the Elderly Human Brain. Progress in Medical Physics 2019; 30(4): 139 doi: 10.14316/pmp.2019.30.4.139
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6 |
Buda Bajić. Sparsity promoting super-resolution coverage segmentation by linear unmixing in presence of blur and noise. Journal of Electronic Imaging 2019; 28(01): 1 doi: 10.1117/1.JEI.28.1.013046
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7 |
Reshma Hiralal, Hema P Menon. Intelligent Systems Technologies and Applications 2016. Advances in Intelligent Systems and Computing 2016; 530: 245 doi: 10.1007/978-3-319-47952-1_19
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8 |
Roberto Duarte, Audrey Repetti, Pedro A Gómez, Mike Davies, Yves Wiaux. Greedy approximate projection for magnetic resonance fingerprinting with partial volumes. Inverse Problems 2020; 36(3): 035015 doi: 10.1088/1361-6420/ab356d
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9 |
Jessica L. Panman, Yang Yang To, Emma L. van der Ende, Jackie M. Poos, Lize C. Jiskoot, Lieke H. H. Meeter, Elise G. P. Dopper, Mark J. R. J. Bouts, Matthias J. P. van Osch, Serge A. R. B. Rombouts, John C. van Swieten, Jeroen van der Grond, Janne M. Papma, Anne Hafkemeijer. Bias Introduced by Multiple Head Coils in MRI Research: An 8 Channel and 32 Channel Coil Comparison. Frontiers in Neuroscience 2019; 13 doi: 10.3389/fnins.2019.00729
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10 |
Sunli Tang, Carlos Fernandez-Granda, Sylvain Lannuzel, Brett Bernstein, Riccardo Lattanzi, Martijn Cloos, Florian Knoll, Jakob Assländer. Multicompartment magnetic resonance fingerprinting. Inverse Problems 2018; 34(9): 094005 doi: 10.1088/1361-6420/aad1c3
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11 |
V. C. Obmann, N. Mertineit, C. Marx, A. Berzigotti, L. Ebner, J. T. Heverhagen, A. Christe, A. T. Huber. Liver MR relaxometry at 3T – segmental normal T1 and T2* values in patients without focal or diffuse liver disease and in patients with increased liver fat and elevated liver stiffness. Scientific Reports 2019; 9(1) doi: 10.1038/s41598-019-44377-y
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12 |
Peifang Guo. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures. Lecture Notes in Computer Science 2019; 11840: 85 doi: 10.1007/978-3-030-32689-0_9
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13 |
Eileanoir B. Johnson, Sarah Gregory, Hans J. Johnson, Alexandra Durr, Blair R. Leavitt, Raymund A. Roos, Geraint Rees, Sarah J. Tabrizi, Rachael I. Scahill. Recommendations for the Use of Automated Gray Matter Segmentation Tools: Evidence from Huntington’s Disease. Frontiers in Neurology 2017; 8 doi: 10.3389/fneur.2017.00519
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14 |
Vladimir Kanchev, Roumen Kountchev. New Approaches in Intelligent Image Analysis. Intelligent Systems Reference Library 2016; 108: 183 doi: 10.1007/978-3-319-32192-9_6
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15 |
Ali Hasan, Farid Meziane, Rob Aspin, Hamid Jalab. Segmentation of Brain Tumors in MRI Images Using Three-Dimensional Active Contour without Edge. Symmetry 2016; 8(11): 132 doi: 10.3390/sym8110132
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16 |
Debra McGivney, Anagha Deshmane, Yun Jiang, Dan Ma, Chaitra Badve, Andrew Sloan, Vikas Gulani, Mark Griswold. Bayesian estimation of multicomponent relaxation parameters in magnetic resonance fingerprinting. Magnetic Resonance in Medicine 2018; 80(1): 159 doi: 10.1002/mrm.27017
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17 |
Peifang Guo. Brain tissue classification method for clinical decision-support systems. Engineering Applications of Artificial Intelligence 2017; 64: 232 doi: 10.1016/j.engappai.2017.05.015
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18 |
Yasser Alemán‐Gómez, Elena Najdenovska, Timo Roine, Mário João Fartaria, Erick J. Canales‐Rodríguez, Zita Rovó, Patric Hagmann, Philippe Conus, Kim Q. Do, Paul Klauser, Pascal Steullet, Philipp S. Baumann, Meritxell Bach Cuadra. Partial‐volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia. Human Brain Mapping 2020; 41(14): 4041 doi: 10.1002/hbm.25108
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19 |
Peifang Guo. A tissue-based biomarker model for predicting disease patterns. Knowledge-Based Systems 2017; 131: 160 doi: 10.1016/j.knosys.2017.05.019
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20 |
Farzad Mortazavi, Samantha E. Romano, Douglas L. Rosene, Kathleen S. Rockland. A Survey of White Matter Neurons at the Gyral Crowns and Sulcal Depths in the Rhesus Monkey. Frontiers in Neuroanatomy 2017; 11 doi: 10.3389/fnana.2017.00069
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21 |
Martijn Nagtegaal, Peter Koken, Thomas Amthor, Mariya Doneva. Fast multi‐component analysis using a joint sparsity constraint for MR fingerprinting. Magnetic Resonance in Medicine 2020; 83(2): 521 doi: 10.1002/mrm.27947
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22 |
Peifang Guo, Alan Evans, Prabir Bhattacharya. Nuclei Segmentation for Quantification of Brain Tumors in Digital Pathology Images. International Journal of Software Science and Computational Intelligence 2018; 10(2): 36 doi: 10.4018/IJSSCI.2018040103
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23 |
Suraj D. Serai, Jonathan Dudley, James L. Leach. Comparison of whole brain segmentation and volume estimation in children and young adults using SPM and SyMRI. Clinical Imaging 2019; 57: 77 doi: 10.1016/j.clinimag.2019.05.008
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24 |
Dayana Hayek, Friederike Thams, Agnes Flöel, Daria Antonenko. Dentate Gyrus Volume Mediates the Effect of Fornix Microstructure on Memory Formation in Older Adults. Frontiers in Aging Neuroscience 2020; 12 doi: 10.3389/fnagi.2020.00079
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25 |
A.G. Beejesh, Varun P. Gopi, Jude Hemanth. Brain MR kurtosis imaging study: Contrasting gray and white matter. Cognitive Systems Research 2019; 55: 135 doi: 10.1016/j.cogsys.2019.01.005
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26 |
Anu Venkatesh, Shauna M. Stark, Craig E.L. Stark, Ilana J. Bennett. Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging. Neurobiology of Aging 2020; 96: 12 doi: 10.1016/j.neurobiolaging.2020.08.004
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27 |
Xiaoliang Gong, Chao Ma, Panpan Yang, Yufei Chen, Chaolin Du, Caixia Fu, Jian-Ping Lu. Computer-aided pancreas segmentation based on 3D GRE Dixon MRI: a feasibility study. Acta Radiologica Open 2019; 8(3): 205846011983469 doi: 10.1177/2058460119834690
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28 |
Richa Gandhi, Charalampos Tsoumpas. Preclinical Imaging Biomarkers for Postischaemic Neurovascular Remodelling. Contrast Media & Molecular Imaging 2019; 2019: 1 doi: 10.1155/2019/3128529
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29 |
Jannike Nickander, Magnus Lundin, Goran Abdula, Peder Sörensson, Stefania Rosmini, James C. Moon, Peter Kellman, Andreas Sigfridsson, Martin Ugander. Blood correction reduces variability and gender differences in native myocardial T1 values at 1.5 T cardiovascular magnetic resonance – a derivation/validation approach. Journal of Cardiovascular Magnetic Resonance 2017; 19(1) doi: 10.1186/s12968-017-0353-7
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30 |
Juliane Dinse, Andreas Schäfer, Pierre-Louis Bazin, Nikolaus Weiskopf. Bildverarbeitung für die Medizin 2016. Informatik aktuell 2016; : 14 doi: 10.1007/978-3-662-49465-3_5
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31 |
Peifang Guo. Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. Lecture Notes in Computer Science 2017; 10549: 78 doi: 10.1007/978-3-319-67552-7_10
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32 |
J. Neikter, S. Agerskov, P. Hellström, M. Tullberg, G. Starck, D. Ziegelitz, D. Farahmand. Ventricular Volume Is More Strongly Associated with Clinical Improvement Than the Evans Index after Shunting in Idiopathic Normal Pressure Hydrocephalus. American Journal of Neuroradiology 2020; 41(7): 1187 doi: 10.3174/ajnr.A6620
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33 |
John Au, Diana M. Perriman, Mark R. Pickering, Graham Buirski, Paul N. Smith, Alexandra L. Webb. Magnetic resonance imaging atlas of the cervical spine musculature. Clinical Anatomy 2016; 29(5): 643 doi: 10.1002/ca.22731
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34 |
Peifang Guo, Prabir Bhattacharya. A novel brain image processing method for the application of detecting the GBM disease patterns in anatomic sections of T1-weighted 3D magnetic resonance imaging. 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC) 2017; : 146 doi: 10.1109/ICCI-CC.2017.8109743
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35 |
Peifang Guo, Prabir Bhattacharya. An Innovative Model for Detecting Brain Tumors and Glioblastoma Multiforme Disease Patterns. International Journal of Software Science and Computational Intelligence 2017; 9(4): 34 doi: 10.4018/IJSSCI.2017100103
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36 |
Hamid A. Jalab, Ali M. Hasan. Magnetic Resonance Imaging Segmentation Techniques of Brain Tumors: A Review. Archives of Neuroscience 2019; 6(Brain Mapping) doi: 10.5812/ans.84920
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