Digital Image Enhancement
Digital Image Enhancement - Related Videos
05:50
Contrast Enhanced Vessel Imaging using MicroCT
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Cited by 17 •
2011
Contrast enhanced small animal vessel imaging by microCT is a rapid, cost-effective and high-throughput technique for serial in situ examination for tumor development, for analyzing the network of blood vessels that nourish them, and for following the response of tumors to preclinical therapeutic intervention(s).
15:57
Brain Imaging Investigation of the Memory-Enhancing Effect of Emotion
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Cited by 19 •
2011
We present a protocol that uses functional magnetic resonance imaging to investigate the neural correlates of the memory-enhancing effect of emotion. This protocol allows identification of brain activity specifically linked to memory-related processing, contrary to more general perceptual processing, and can be used with healthy and clinical populations.
11:34
High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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Cited by 9 •
2013
This video describes the fundamentals of digital fringe projection techniques, which provide dense 3D measurements of dynamically changing surfaces. It also demonstrates the design and operation of a high-speed binary defocusing system based on these techniques.
08:45
Shrinkage of Dental Composite in Simulated Cavity Measured with Digital Image Correlation
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Cited by 12 •
2014
In order to understand the spatial development of polymerization shrinkage stress in dental resin-composite restorations, Digital Image Correlation was used to provide full-field displacement/strain measurement of restored model glass cavities by correlating images of the restoration taken before and after polymerization.
09:29
Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
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Cited by 19 •
2016
We describe the use of digital image correlation to characterize the local surface strain field on vascular tissue samples subjected to uniaxial tensile testing. These measurements facilitate precise quantification of the sample mechanical response and the generation of constitutive stress-strain relations.
FAQs
Intensity transformations modify how digital pixel values are displayed, allowing differences in brightness or contrast to become more apparent. This can make subtle anatomical features or abnormalities easier to distinguish without changing the underlying imaging modality. In practice, the approach helps clinicians inspect structures that may be difficult to see when tissue contrast or acquisition conditions limit the original image.
Edge-preserving processing is important because enhancement should increase visibility without compromising clinically relevant anatomical boundaries. Unlike processing focused only on overall visual changes, it is designed to retain meaningful structures while improving aspects such as contrast, sharpness, or noise appearance. This balance supports clearer interpretation and helps preserve features needed for diagnostic review or later analysis.
Digital image enhancement can adjust contrast, brightness, sharpness, noise, and spatial resolution. Each property addresses a different limitation: contrast and brightness affect visibility, sharpness influences the apparent definition of structures, noise reduction can improve visual clarity, and spatial-resolution changes affect the representation of detail. Selecting the relevant adjustment depends on the image quality problem and the clinical feature being examined.
A practical workflow begins by identifying whether limited contrast, brightness, noise, sharpness, or spatial resolution is interfering with interpretation. Researchers can then select an appropriate intensity transformation, filter, or edge-preserving process and examine whether clinically relevant structures become clearer. The enhanced image can support visual review, quantitative analysis, or computer-aided diagnosis, depending on the study objective.
Applications span radiographs, ultrasound, computed tomography, magnetic resonance imaging, and microscopy. Enhancement is useful when acquisition conditions or inherent tissue contrast make anatomical features or abnormalities difficult to visualize. Applying suitable processing across these modalities can improve image interpretation while also supporting research tasks that require clearer visualization of structures in different types of medical data.
The enhanced representation can support more than clinical viewing. It may improve quantitative analysis by making relevant structures easier to assess and can contribute to computer-aided diagnosis. In research, these capabilities are valuable when image quality is limited, because clearer visualization may assist the examination of anatomical features, abnormalities, or tissue patterns in medical images and microscopy.