 Image Processing, Computer-Assisted
"Image Processing, Computer-Assisted" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A technique of inputting two-dimensional images into a computer and then enhancing or analyzing the imagery into a form that is more useful to the human observer.
| Descriptor ID |
D007091
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| MeSH Number(s) |
L01.224.308
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| Concept/Terms |
Image Analysis, Computer-Assisted- Image Analysis, Computer-Assisted
- Image Analysis, Computer Assisted
- Computer-Assisted Image Analysis
- Computer Assisted Image Analysis
- Analysis, Computer-Assisted Image
- Computer-Assisted Image Analyses
- Image Analyses, Computer-Assisted
Image Reconstruction- Image Reconstruction
- Image Reconstructions
- Reconstruction, Image
- Reconstructions, Image
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Below are MeSH descriptors whose meaning is more general than "Image Processing, Computer-Assisted".
Below are MeSH descriptors whose meaning is more specific than "Image Processing, Computer-Assisted".
This graph shows the total number of publications written about "Image Processing, Computer-Assisted" by people in this website by year, and whether "Image Processing, Computer-Assisted" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
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| 1987 | 1 | 2 | 3 | | 1988 | 4 | 3 | 7 | | 1989 | 7 | 2 | 9 | | 1990 | 9 | 6 | 15 | | 1991 | 10 | 5 | 15 | | 1992 | 7 | 6 | 13 | | 1993 | 6 | 3 | 9 | | 1994 | 11 | 7 | 18 | | 1995 | 8 | 5 | 13 | | 1996 | 6 | 11 | 17 | | 1997 | 11 | 4 | 15 | | 1998 | 11 | 17 | 28 | | 1999 | 12 | 11 | 23 | | 2000 | 13 | 13 | 26 | | 2001 | 9 | 16 | 25 | | 2002 | 13 | 11 | 24 | | 2003 | 21 | 14 | 35 | | 2004 | 10 | 14 | 24 | | 2005 | 3 | 25 | 28 | | 2006 | 5 | 19 | 24 | | 2007 | 8 | 19 | 27 | | 2008 | 8 | 14 | 22 | | 2009 | 10 | 18 | 28 | | 2010 | 13 | 27 | 40 | | 2011 | 10 | 20 | 30 | | 2012 | 11 | 20 | 31 | | 2013 | 11 | 16 | 27 | | 2014 | 10 | 28 | 38 | | 2015 | 10 | 23 | 33 | | 2016 | 13 | 15 | 28 | | 2017 | 11 | 17 | 28 | | 2018 | 15 | 19 | 34 | | 2019 | 18 | 12 | 30 | | 2020 | 5 | 4 | 9 | | 2021 | 8 | 13 | 21 | | 2022 | 2 | 1 | 3 |
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Below are the most recent publications written about "Image Processing, Computer-Assisted" by people in Profiles.
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Schmidt TG, Sammut BA, Barber RF, Pan X, Sidky EY. Addressing CT metal artifacts using photon-counting detectors and one-step spectral CT image reconstruction. Med Phys. 2022 May; 49(5):3021-3040.
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Kaplan S, Perrone A, Alexopoulos D, Kenley JK, Barch DM, Buss C, Elison JT, Graham AM, Neil JJ, O'Connor TG, Rasmussen JM, Rosenberg MD, Rogers CE, Sotiras A, Fair DA, Smyser CD. Synthesizing pseudo-T2w images to recapture missing data in neonatal neuroimaging with applications in rs-fMRI. Neuroimage. 2022 06; 253:119091.
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Zhang Z, Chen B, Xia D, Sidky EY, Pan X. Image reconstruction from data over two orthogonal arcs of limited-angular ranges. Med Phys. 2022 Mar; 49(3):1468-1480.
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Kaplan S, Meyer D, Miranda-Dominguez O, Perrone A, Earl E, Alexopoulos D, Barch DM, Day TKM, Dust J, Eggebrecht AT, Feczko E, Kardan O, Kenley JK, Rogers CE, Wheelock MD, Yacoub E, Rosenberg M, Elison JT, Fair DA, Smyser CD. Filtering respiratory motion artifact from resting state fMRI data in infant and toddler populations. Neuroimage. 2022 02 15; 247:118838.
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Ayan AS, Kim G, Whitaker M, Al-Hallaq H, Hsu SH, Woollard J, Roberts DA, Shtraus N, Gao S, Gupta N, Moran JM. A framework for automated and streamlined kV cone beam computed tomography image quality assurance: a multi-institutional study. Biomed Phys Eng Express. 2021 10 05; 7(6).
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Chen B, Zhang Z, Xia D, Sidky EY, Pan X. Dual-energy CT imaging with limited-angular-range data. Phys Med Biol. 2021 09 17; 66(18).
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Momin S, Lei Y, Tian Z, Wang T, Roper J, Kesarwala AH, Higgins K, Bradley JD, Liu T, Yang X. Lung tumor segmentation in 4D CT images using motion convolutional neural networks. Med Phys. 2021 Nov; 48(11):7141-7153.
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Virostko J, Craddock RC, Williams JM, Triolo TM, Hilmes MA, Kang H, Du L, Wright JJ, Kinney M, Maki JH, Medved M, Waibel M, Kay TWH, Thomas HE, Greeley SAW, Steck AK, Moore DJ, Powers AC. Development of a standardized MRI protocol for pancreas assessment in humans. PLoS One. 2021; 16(8):e0256029.
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West DJ, Cruz G, Teixeira RPAG, Schneider T, Tournier JD, Hajnal JV, Prieto C, Malik SJ. An MR fingerprinting approach for quantitative inhomogeneous magnetization transfer imaging. Magn Reson Med. 2022 01; 87(1):220-235.
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Howard FM, Dolezal J, Kochanny S, Schulte J, Chen H, Heij L, Huo D, Nanda R, Olopade OI, Kather JN, Cipriani N, Grossman RL, Pearson AT. The impact of site-specific digital histology signatures on deep learning model accuracy and bias. Nat Commun. 2021 07 20; 12(1):4423.
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