Digital Photography Measurement
Digital Photography Measurement - Related Videos
05:51
Smartphone Fundus Photography
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Cited by 49 •
2017
Fundus photography normally requires specialized fundus cameras that are not always available in all clinical settings. Here, a simple method to record ocular fundus images using a smartphone camera and a conventional high-plus handheld indirect ophthalmoscopy lens is described.
06:49
A Standardized Approach to Extra-Oral and Intra-Oral Digital Photography
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Cited by 8 •
2022
The present protocol describes a method to capture intra- and extra-oral photographs for digital documentation in the clinical practice of dentistry. The protocol highlights all the critical components involved and the commonly utilized settings to capture dental photographs for clinical documentation.
14:02
Measuring Engagement of Spectators of Social Digital Games
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2021
We propose a methodology that enables measuring engagement of spectators in a social digital game combining physiological and self-reported data. As this digital game involves a group of freely moving people, the experience is filmed using a synchronizing technique that links physiological data with events in the game.
06:27
Rodent Heart and Brain Tissue Preparation for Digital Macro Photography after Ischemia-reperfusion
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Cited by 5 •
2022
Presented here is a protocol for the standardized methodology of rodent tissue preparation after the ischemia-reperfusion experiment and guidelines for establishing lighting and camera setups for high-resolution image acquisition. This method is applicable to all experimental small-animal organ photography.
06:49
Visualization of Ambient Mass Spectrometry with the Use of Schlieren Photography
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Cited by 4 •
2016
This paper presents a protocol for the visualization of gaseous streams of an ambient ionization source using schlieren photography and mass spectrometry.
FAQs
Calibrated pixels establish a consistent relationship between image features and numerical values, while a reference scale provides a known dimension within the photograph. Together, they allow image-analysis software to estimate measurements such as size or spatial relationships more consistently than visual judgment alone. This calibration is especially important when comparing images from different patients, examinations, or time points.
Lighting conditions directly affect the recorded appearance of color and brightness. Standardized lighting helps ensure that observed differences reflect changes in the photographed tissue or specimen rather than changes in image acquisition. Consistent illumination therefore improves comparability across photographs and supports more reproducible assessment of skin changes, wounds, surgical outcomes, and microscopy specimens.
Image-analysis software converts selected visual features into numerical measurements, reducing dependence on subjective visual estimates. Depending on the image and calibration, the measured features may include size, color, brightness, shape, or spatial relationships. This quantitative approach gives clinicians and researchers a more consistent basis for documenting findings and evaluating change over time.
A typical workflow begins with acquiring a photograph using a digital sensor under consistent conditions. The image is then associated with a reference scale or calibrated pixel relationship, and standardized lighting supports reliable recording of visual features. Image-analysis software can subsequently quantify the selected feature, producing numerical information for documentation, comparison, or further clinical study.
In medicine, this approach is useful for documenting and assessing wounds, skin changes, surgical outcomes, anatomical features, and microscopy specimens. Its value is greatest when clinicians or investigators need comparable records rather than isolated visual impressions. Repeated measurements can help describe disease progression or treatment response while supporting more objective monitoring across examinations.
The method can produce numerical descriptions of image-based features, including dimensions, color, brightness, shape, and spatial relationships. When acquisition and calibration remain consistent, these values can be compared across patients, study time points, or treatment conditions. Such comparisons support documentation, assessment of surgical results, and monitoring of whether disease-related changes or treatment responses are progressing.