Image Manipulation Technique
Image Manipulation Technique - Related Videos
13:27
Osteopathic Manipulative Treatment as a Useful Adjunctive Tool for Pneumonia
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Cited by 50 •
2014
Pneumonia is one of the top ten leading causes of death in the U.S. Osteopathic manipulative techniques (OMT) may be utilized as an adjunctive therapy in the treatment of pneumonia to enhance biomechanical and immune function; and ultimately, to reduce hospital stay, duration of antibiotics, incidence of respiratory failure, and mortality. In this video-article, we will review randomized controlled studies on the use of OMT in pneumonia patients, as well as demonstrate specific hands-on...
14:43
Combining Single-molecule Manipulation and Imaging for the Study of Protein-DNA Interactions
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Cited by 10 •
2014
Here we describe the instrumentation and methods for detecting single fluorescently-labeled protein molecules interacting with a single DNA molecule suspended between two optically trapped microspheres.
09:05
Embryo Microinjection and Transplantation Technique for Nasonia vitripennis Genome Manipulation
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Cited by 17 •
2017
Microinjection of Nasonia vitripennis embryos is an essential method for generating heritable genome modifications. Described here is a detailed procedure for microinjection and transplantation of Nasonia vitripennis embryos, which will greatly facilitate future genome manipulation in this organism.
12:15
Isolation and Genetic Manipulation of Adult Cardiac Myocytes for Confocal Imaging
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Cited by 35 •
2009
Adult cardiac myocytes are primary cells that can be isolated from animal hearts and cultured for several days. Within this culture period adenoviral gene transfer can be used to express genetically encoded biosensors (GEBs) or fluorescent fusion proteins. Both approaches allow cellular investigations by means of confocal microscopy.
07:38
Techniques for Imaging Ca2+ Signaling in Human Sperm
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Cited by 17 •
2010
Stimulus-evoked [Ca2+]i signals of individual human sperm are assessed. Motile cells are loaded with Ca2+-sensitive fluorescent dye (AM-ester method) and immobilised in a perfusable chamber. Cells are imaged by time-lapse fluorescence microscopy and stimulated via the perfusing medium. Responses of single cells (or regions) are analysed offline using Excel.
FAQs
Contrast enhancement changes the separation between pixel values so differences between structures become more visible, while noise reduction suppresses unwanted variation that can interfere with viewing. These operations can improve visual clarity in radiographs, magnetic resonance images, computed tomography scans, and microscopy images, but excessive adjustment may remove or distort diagnostically relevant information.
Operations such as sharpening and resizing alter spatial relationships among neighboring pixels. Sharpening can make boundaries and fine features appear more distinct, whereas resizing changes image scale and may affect how structures are represented. Because these changes influence visual interpretation and later measurement, the chosen operation should preserve important anatomical or microscopic structures rather than simply produce a more dramatic image.
Segmentation separates selected structures or regions from the surrounding image, allowing researchers to examine them more consistently. After regions are identified, image data can support quantitative measurement rather than only visual inspection. In medical imaging and microscopy, this may help organize analysis of features across images, provided that processing does not obscure relevant structures or introduce misleading boundaries.
Processing can introduce artifacts, obscure findings, or create apparent features that were not represented clearly in the original image. Changes to pixel values or spatial relationships may also bias quantitative measurements. For that reason, improved visual quality alone does not establish accuracy. Interpretation should consider whether the manipulation preserved diagnostically relevant structures and whether its effects were documented and validated.
A practical workflow begins by identifying the interpretive or measurement goal, then selecting an operation such as contrast enhancement, noise reduction, sharpening, resizing, or segmentation. The processed image should be reviewed for preserved structures and possible artifacts. Researchers should document the manipulation and validate its effects before using the result for consistent analysis or quantitative measurement.
These techniques are useful when image quality or feature visibility limits interpretation in radiographs, magnetic resonance images, computed tomography scans, or microscopy images. They can clarify structures, support segmentation, and make analysis more consistent across samples or examinations. Their value extends beyond presentation because appropriately processed images may also enable quantitative measurement, provided the processing remains controlled.
Documentation records how pixel values or spatial relationships were changed, making the processing approach understandable and reproducible. Validation checks whether the result preserves diagnostically relevant structures and supports the intended interpretation or measurement. Together, these safeguards help distinguish genuine image information from processing-related artifacts and reduce the risk that manipulation will bias clinical or scientific conclusions.