Reference Image Acquisition
Reference Image Acquisition - Related Videos
09:17
Point-of-Care Lung Ultrasound in Adults: Image Acquisition
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Cited by 15 •
2023
Point-of-care ultrasound (POCUS) of the lungs provides quick answers in rapidly changing clinical scenarios. We present an efficient and informative protocol for image acquisition for use in acute care settings.
03:19
Point-of-Care Kidney and Genitourinary Ultrasound in Adults: Image Acquisition
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2024
Point-of-care ultrasound (POCUS) of the renal and genitourinary (renal-GU) system can help to screen for certain causes of kidney dysfunction. However, despite its clinical utility, renal-GU POCUS remains underutilized due to a lack of training among clinicians. To address this gap, this article describes renal-GU image acquisition and interpretation.
01:23
Reference & Citation Tools in Practice
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2026
Citations play a key role in academic writing by documenting the evidence that supports scholarly claims. Beyond giving credit to original authors, they show engagement with existing research and strengthen the credibility of an argument. Effective citation practices are central to research literacy because they reflect a writer’s ability to locate, evaluate, and integrate reliable sources into their work. Digital Tools for Citation Management Advances in digital technology have simplified the...
04:00
Identifying Frailty Using Point-of-Care Ultrasonography: Image Acquisition and Assessment
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2024
Here, we present a protocol to assess frailty in the perioperative setting using point-of-care ultrasound to measure quadriceps thickness. This method offers a practical, non-invasive alternative to traditional assessment methods, potentially enhancing perioperative care by quickly identifying frail patients.
07:27
Rapid Acquisition of 3D Images Using High-resolution Episcopic Microscopy
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Cited by 2 •
2016
We describe a detailed protocol using high-resolution episcopic microscopy to acquire three-dimensional (3D) images of mouse embryos. This improved protocol utilizes a modified tissue preparation method to enhance penetration of the fluorescent dye, thereby permitting morphometric analysis of both small and large-sized specimens.
FAQs
Illumination, magnification, focus, field of view, and scale directly influence how biological structures appear and how they can be compared. Controlling these factors reduces visual differences caused by the imaging setup rather than by the samples themselves. This consistency is especially important when images support morphology assessment, quantitative measurements, segmentation, or classification.
Scale establishes the size relationship between image features and the biological specimen, while field of view determines which structures are included in the image. If either varies substantially, apparent differences in cell morphology, tissue organization, or developmental features may reflect image framing rather than biology. Consistent settings therefore support more meaningful comparisons across samples and time points.
Sample and instrument information provides context for interpreting an image and checking whether images were acquired under comparable conditions. These records help connect visual findings with the specimen and imaging system that produced them. In turn, they support experimental reproducibility, make comparisons easier to evaluate, and provide a documented basis for later image analysis or method validation.
A practical workflow begins by capturing or selecting images that represent the intended biological comparison, then controlling illumination, magnification, focus, field of view, and scale. Researchers should also record relevant sample and instrument information. The resulting images can serve as a consistent visual baseline for examining morphology, tissue organization, developmental features, or experimental changes.
They are useful whenever researchers need to compare biological features across samples or time points. Examples supported by the topic include microscopy, digital pathology, phenotyping, and studies of cell morphology, tissue organization, or development. A consistent visual baseline helps distinguish experimental or biological differences from variation introduced by image capture and interpretation.
Consistent reference images provide a dependable basis for developing, evaluating, or validating computational imaging methods. Controlled visual conditions can improve the interpretation of image features used for segmentation, classification, and quantitative measurement. In biological research, this support helps computational results align more closely with observable cell, tissue, developmental, or experimental characteristics.