 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 Reconstruction- Image Reconstruction
- Image Reconstructions
- Reconstruction, Image
- Reconstructions, Image
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
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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 |
|---|
| 1995 | 2 | 3 | 5 | | 1996 | 2 | 4 | 6 | | 1997 | 5 | 10 | 15 | | 1998 | 4 | 9 | 13 | | 1999 | 1 | 7 | 8 | | 2000 | 2 | 10 | 12 | | 2001 | 0 | 8 | 8 | | 2002 | 6 | 7 | 13 | | 2003 | 5 | 8 | 13 | | 2004 | 4 | 19 | 23 | | 2005 | 9 | 13 | 22 | | 2006 | 3 | 10 | 13 | | 2007 | 10 | 17 | 27 | | 2008 | 6 | 16 | 22 | | 2009 | 4 | 17 | 21 | | 2010 | 4 | 20 | 24 | | 2011 | 4 | 10 | 14 | | 2012 | 3 | 20 | 23 | | 2013 | 9 | 19 | 28 | | 2014 | 11 | 18 | 29 | | 2015 | 10 | 15 | 25 | | 2016 | 10 | 16 | 26 | | 2017 | 10 | 26 | 36 | | 2018 | 15 | 12 | 27 | | 2019 | 14 | 12 | 26 | | 2020 | 8 | 9 | 17 | | 2021 | 14 | 5 | 19 | | 2022 | 4 | 1 | 5 | | 2023 | 4 | 7 | 11 | | 2024 | 1 | 6 | 7 | | 2025 | 6 | 5 | 11 |
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Below are the most recent publications written about "Image Processing, Computer-Assisted" by people in Profiles.
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Briggs JK, Jin E, Merrins MJ, Benninger RKP. CRISP: correlation-refined image segmentation process. BMC Bioinformatics. 2025 May 26; 26(1):135.
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Khang A, Barmore A, Tseropoulos G, Bera K, Batan D, Anseth KS. Automated prediction of fibroblast phenotypes using mathematical descriptors of cellular features. Nat Commun. 2025 Mar 22; 16(1):2841.
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Robinson CJ, Dickie B, Lindner C, Herrera J, Dingle L, Reid AJ, Wong JKF, Hiebert P, Cootes TF, Kurinna S. Complex wound analysis using AI. Comput Biol Med. 2025 May; 190:109945.
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Serrano E, Chandrasekaran SN, Bunten D, Brewer KI, Tomkinson J, Kern R, Bornholdt M, Fleming SJ, Pei R, Arevalo J, Tsang H, Rubinetti V, Tromans-Coia C, Becker T, Weisbart E, Bunne C, Kalinin AA, Senft R, Taylor SJ, Jamali N, Adeboye A, Abbasi HS, Goodman A, Caicedo JC, Carpenter AE, Cimini BA, Singh S, Way GP. Reproducible image-based profiling with Pycytominer. Nat Methods. 2025 Apr; 22(4):677-680.
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Ahmed SR, Befano B, Egemen D, Rodriguez AC, Desai KT, Jeronimo J, Ajenifuja KO, Clark C, Perkins R, Campos NG, Inturrisi F, Wentzensen N, Han P, Guillen D, Norman J, Goldstein AT, Madeleine MM, Donastorg Y, Schiffman M, de Sanjose S, Kalpathy-Cramer J. Generalizable deep neural networks for image quality classification of cervical images. Sci Rep. 2025 Feb 21; 15(1):6312.
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Huffine CA, Maas ZL, Avramov A, Brininger CM, Cameron JC, Tay JW. Machine learning models for segmentation and classification of cyanobacterial cells. Photosynth Res. 2025 Feb 08; 163(1):16.
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Zhao J, Vaios E, Yang Z, Lu K, Floyd S, Yang D, Ji H, Reitman ZJ, Lafata KJ, Fecci P, Kirkpatrick JP, Wang C. Radiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis. Med Phys. 2025 Apr; 52(4):2661-2674.
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Greenblott DN, Calderon CP, Randolph TW. Representative training data sets are critical for accurate machine-learning classification of microscopy images of particles formed by lipase-catalyzed polysorbate hydrolysis. J Pharm Sci. 2025 Feb; 114(2):1254-1263.
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Lippitt WL, Maier LA, Fingerlin TE, Lynch DA, Yadav R, Rieck J, Hill AC, Liao SY, Mroz MM, Barkes BQ, Ju Chae K, Jeon Hwang H, Carlson NE. The textures of sarcoidosis: quantifying lung disease through variograms. Phys Med Biol. 2025 Jan 13; 70(2).
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Abbott RE, Nishimwe A, Wiputra H, Breighner RE, Ellingson AM. A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion. Sci Rep. 2025 01 09; 15(1):1382.
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