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
|
MeSH Number(s) |
L01.224.308
|
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
|
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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1994 | 0 | 1 | 1 |
2000 | 0 | 1 | 1 |
2001 | 0 | 1 | 1 |
2003 | 0 | 1 | 1 |
2004 | 1 | 1 | 2 |
2005 | 0 | 7 | 7 |
2006 | 0 | 3 | 3 |
2008 | 0 | 1 | 1 |
2009 | 0 | 2 | 2 |
2010 | 1 | 2 | 3 |
2011 | 2 | 0 | 2 |
2012 | 1 | 3 | 4 |
2013 | 0 | 3 | 3 |
2014 | 1 | 2 | 3 |
2015 | 2 | 6 | 8 |
2016 | 4 | 1 | 5 |
2017 | 61 | 102 | 163 |
2018 | 67 | 103 | 170 |
2019 | 14 | 13 | 27 |
2020 | 6 | 10 | 16 |
2021 | 4 | 4 | 8 |
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Below are the most recent publications written about "Image Processing, Computer-Assisted" by people in Profiles.
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AAN-Face: Attention Augmented Networks for Face Recognition. IEEE Trans Image Process. 2021; 30:7636-7648.
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Automated processing of thermal imaging to detect COVID-19. Sci Rep. 2021 09 01; 11(1):17489.
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Digital Pathology Initiatives and Experience of a Large Academic Institution During the Coronavirus Disease 2019 (COVID-19) Pandemic. Arch Pathol Lab Med. 2021 09 01; 145(9):1051-1061.
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Precise Segmentation of COVID-19 Infected Lung from CT Images Based on Adaptive First-Order Appearance Model with Morphological/Anatomical Constraints. Sensors (Basel). 2021 Aug 14; 21(16).
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Deep-learning based detection of COVID-19 using lung ultrasound imagery. PLoS One. 2021; 16(8):e0255886.
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A bagging dynamic deep learning network for diagnosing COVID-19. Sci Rep. 2021 08 11; 11(1):16280.
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Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples. Sci Rep. 2021 08 10; 11(1):16201.
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Automated Detection and Quantification of COVID-19 Airspace Disease on Chest Radiographs: A Novel Approach Achieving Expert Radiologist-Level Performance Using a Deep Convolutional Neural Network Trained on Digital Reconstructed Radiographs From Computed Tomography-Derived Ground Truth. Invest Radiol. 2021 08 01; 56(8):471-479.
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CoLe-CNN+: Context learning - Convolutional neural network for COVID-19-Ground-Glass-Opacities detection and segmentation. Comput Biol Med. 2021 09; 136:104689.
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User-friendly, High-throughput, and Fully Automated Data Acquisition Software for Single-particle Cryo-electron Microscopy. J Vis Exp. 2021 07 29; (173).