Comparison of Image Quality Obtained with Optical and Radiographic Magnification Techniques in Fine-Detail Skeletal Radiography: Effect of Object Thinkness

Noise is an extremely important image quality factor. Camera manufacturers go to great lengths to source sensors and develop algorithms to minimize it. Illustrations of its effects are familiar, but it is not well known that noise itself, which is not constant over an image, can be represented as an image. Noise varies over images for two reasons. (1) Noise voltage in raw images is predicted to be proportional to a constant plus the square root of the number of photons reaching each pixel. (2) The most commonly applied image processing in consumer cameras, bilateral filtering [1], sharpens regions of the image near contrasty features such as edges and smooths (applies lowpass filtering to reduce noise) the image elsewhere. Noise is normally measured in flat, uniformly-illuminated patches, where bilateral filter smoothing has its maximum effect, often at the expense of fine detail. Significant insight into the behavior of image processing can be gained by measuring the noise throughout the image, not just in flat patches. We describe a method for obtaining noise images, then illustrate an important application— observing texture loss— and compare noise images for JPEG and raw-converted images. The method, derived from the EMVA 1288 analysis of flat-field images, requires the acquisition of a large number of identical images. It is somewhat cumbersome when individual image files need to be saved, but it’s fast and convenient when direct image acquisition is available.

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Improvement of image quality applying iterative scatter correction for grid-less skeletal radiography in trauma room setting

Acta Radiologica ◽

10.1177/0284185119878348 ◽

2019 ◽

Vol 61 (6) ◽

pp. 768-775

Author(s):

Christoph G Lisson ◽

Catharina S Lisson ◽

Daniel Vogele ◽

Beatrice Strauss ◽

Konrad Schuetze ◽

...

Keyword(s):

Image Quality ◽

Rating Scale ◽

Scatter Correction ◽

Iterative Algorithms ◽

Trauma Room ◽

Body Regions ◽

Wide Range ◽

Characteristics Analysis ◽

Skeletal Radiography ◽

The Future Method

Background Iterative reconstruction is well established for CT. Plain radiography also takes advantage of iterative algorithms to reduce scatter radiation and improve image quality. First applications have been described for bedside chest X-ray. A recent experimental approach also provided proof of principle for skeletal imaging. Purpose To examine clinical applicability of iterative scatter correction for skeletal imaging in the trauma setting. Material and Methods In this retrospective single-center study, 209 grid-less radiographs were routinely acquired in the trauma room for 12 months, with imaging of the chest (n = 31), knee (n = 111), pelvis (n = 14), shoulder (n = 24), and other regions close to the trunk (n = 29). Radiographs were postprocessed with iterative scatter correction, doubling the number of images. The radiographs were then independently evaluated by three radiologists and three surgeons. A five-step rating scale and visual grading characteristics analysis were used. The area under the VGC curve (AUCVGC) quantified differences in image quality. Results Images with iterative scatter correction were generally rated significantly better (AUCVGC = 0.59, P < 0.01). This included both radiologists (AUCVGC = 0.61, P < 0.01) and surgeons (AUCVGC = 0.56, P < 0.01). The image-improving effect was significant for all body regions; in detail: chest (AUCVGC = 0.64, P < 0.01), knee (AUCVGC = 0.61, P < 0.01), pelvis (AUCVGC = 0.60, P = 0.01), shoulder (AUCVGC = 0.59, P = 0.02), and others close to the trunk (AUCVGC = 0.59, P < 0.01). Conclusion Iterative scatter correction improves the image quality of grid-less skeletal radiography in the clinical setting for a wide range of body regions. Therefore, iterative scatter correction may be the future method of choice for free exposure imaging when an anti-scatter grid is omitted due to high risk of tube-detector misalignment.

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An Introduction to 3D Microscopy Techniques

Microscopy Today ◽

10.1017/s1551929500054286 ◽

2008 ◽

Vol 16 (1) ◽

pp. 20-23

Author(s):

Megan MacNeil ◽

Duncan McMillan

Keyword(s):

Image Quality ◽

Biomedical Research ◽

3D Imaging ◽

Fluorescence Labeling ◽

3D Microscopy ◽

Fine Detail ◽

Microscopic Studies ◽

Microscopy Techniques ◽

Thin Samples

In the earliest years of microscopy, it was well understood that visualization of the finest details was often limited by the ‘intrusion’ of light from out-of-focus planes. For many decades the only solution to this dilemma was to limit microscopic studies to very thin samples or to physically squash or slice thicker samples. More recently, biomedical research has driven the need for microscopes that can resolve very fine detail in 3 dimensions within intact, and often living, specimens. The use of fluorescence labeling further exacerbates the problem of out-of-focus light because signal is generated throughout the volume of the sample. The following article describes the most prevalent techniques for 3D imaging and important optical considerations for achieving highest image quality.

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Clinical application of a flat-panel X-ray detector based on amorphous silicon technology: image quality and potential for radiation dose reduction in skeletal radiography.

American Journal of Roentgenology ◽

10.2214/ajr.171.1.9648757 ◽

1998 ◽

Vol 171 (1) ◽

pp. 23-27 ◽

Cited By ~ 37

Author(s):

M Strotzer ◽

J Gmeinwieser ◽

M Völk ◽

R Fründ ◽

J Seitz ◽

...

Keyword(s):

Image Quality ◽

Radiation Dose ◽

Amorphous Silicon ◽

Dose Reduction ◽

Clinical Application ◽

Radiation Dose Reduction ◽

Flat Panel ◽

X Ray ◽

Silicon Technology ◽

Skeletal Radiography

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Image quality is resilient against tube voltage variations in post-mortem skeletal radiography with a digital flat-panel detector

Scientific Reports ◽

10.1038/s41598-021-87294-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

S. Notohamiprodjo ◽

K. M. Roeper ◽

K. M. Treitl ◽

B. Hoberg ◽

F. Wanninger ◽

...

Keyword(s):

Image Quality ◽

Patient Exposure ◽

Signal To Noise ◽

Flat Panel ◽

Tube Voltage ◽

Low Contrast ◽

Body Regions ◽

Human Cadavers ◽

Skeletal Radiography ◽

Phantom Studies

AbstractIn recent phantom studies low-contrast detectability was shown to be independent from variations in tube voltage in digital radiography (DR) systems. To investigate the transferability to a clinical setting, the lower extremities of human cadavers were exposed at constant detector doses with different tube voltages in a certain range, as proposed in the phantom studies. Three radiologists independently graded different aspects of image quality (IQ) in a comparative analysis. The grades show no correlation between IQ and kV, which means that the readers were not able to recognize a significant IQ difference at different kV. Signal-to-noise and contrast-to-noise ratios showed no significant differences in IQ despite the kV-setting variations. These findings were observed from a limited kV range setting. Higher kV-settings resulted in lowest patient exposure at constant IQ. These results confirm the potential of DR-systems to contribute to standardization of examination protocols comparable to computed tomography. This may prevent the trend to overexpose. Further investigations in other body regions and other DR-systems are encouraged to determine transferability.

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