Film Processing Quality Control*
Russell L. Wilson in Chiropractic Radiography and Quality Assurance Handbook, 2020
The density of each step is measured using a densitometer. The densitometer’s light source generates a calibrated amount of light that is focused with the help of a small-aperture diaphragm. The image to be measured is placed between the diaphragm and the densitometer’s sensor arm. When the sensor is activated, it compares the amount of light emitted to the amount of light passing through the image on the film. The densitometer will display a number called an optical density unit that indicates the darkness of the film at the spot. The higher the number, the darker the film. After all the densities are measured, they are plotted on the vertical (y) axis of a graph against the log of their relative exposures (mAs) on the horizontal (x) axis. By connecting the points with a curve of best fit, the characteristic curve is constructed. The bottom or toe of the curve represents the low-density region of the image. The middle or straight line corresponds to the clinically useful density range. The shoulder or upper part is the high-density range of the image.
Smart Software for Real-Time Image Analysis
Abdel-Badeeh M. Salem in Innovative Smart Healthcare and Bio-Medical Systems, 2020
In conclusion, the content of the video on the external memory is genuine, meaning that there are no changes or interventions that alter the reality of the recording, as shown in the image analysis by using the software described above. In the case of medical imagery, the acquisition process is laborious. There are many optical sensors (ranging from hundreds to millions) that convert light into electricity and then into bits. All of these processes, in addition to the sensor features and errors that do not depend on the actual acquisition, such as equipment optics, lead to image deformation and noise addition. The changes we make on an image cover these drawbacks as much as possible, the resulting image being ready for further processing. The application allows us to switch to a grayscale image (simplifying both image coding and access to a wide spectrum of processing techniques) in cases in which the color is an irrelevant information (e.g., in order to determine the contours of the image). An example is presented in Figure 1.7.
Diagnosis: Nanosensors in Diagnosis and Medical Monitoring
Harry F. Tibbals in Medical Nanotechnology and Nanomedicine, 2017
In the first section of this chapter, we will review the nanotechnology upon which these sensor capabilities are based. We will see how designers are taking advantage of the special properties of matter and energy at the nanoscale to build these capabilities. In the next sections, we will give an overview of how these sensors are being used in medicine for Diagnosis and monitoring of diseases and disorders: in the research and clinical laboratory, in vivo, and in the field for epidemiology and public health.Genetic analysis and screening based on rapid and inexpensive DNA sequencing capabilities, which, when combined with systems biology and targeted nanomedicines, are opening new possibilities for personalized therapies.Personal health monitoring based on adaptable wearable and implant-able wireless devices for clinical and ambulatory use, providing improved patient health management everywhere from the intensive care unit to the patients home, work, and recreation environment.
Localized surface plasmon resonance based biosensing
Published in Expert Review of Molecular Diagnostics, 2018
Andrea Csáki, Ondrej Stranik, Wolfgang Fritzsche
The performance of the optical signal for a given sensor is primarily defined by the sensitivity of the used nanotransducer determined by material, dimension, and geometry as described before. A higher intensity of the plasmon resonance peak and a sharp bandwidth would allow for a better sensing performance. However, the sensitivity increase given by these values is limited. The thickness of the sensing layer at the sensor surface is limited to tens of nanometers because the LSPR decays exponentially with the distance [130,131]. So enhancement strategies for better signals are necessary to optimize the detection limit. For this, two main strategies are possible (Table 4). On the one hand, the local EM field can be further increased by shape anisotropy of the NP and induction of local hot spots on and between nanostructures. Such EM enhancement effect is used by different Raman spectroscopy techniques or by metal-enhanced fluorescence (MEF) or metal-quenched fluorescence. Plasmonic nanostructures can induce different effects: near plasmonic surfaces, a quenching influence can be observed, but also an increase in the quantum yield of the fluorophores, resulting in higher fluorescence signal, whereas their lifetime is decreased [132–134]. Additionally, the radiative decay rate can be increased. For MEF, typical factors are [135]: particle size, shape, distance between nanoparticle and dye (enhancement/quenching), and spectral overlap with excitation and/or emission spectra of fluorophore. Also, resonance coupling can play a role here. In conclusion, a complex parameter adjustment can lead to an optimal enhancement [136].
Advances in liquid biopsy on-chip for cancer management: Technologies, biomarkers, and clinical analysis
Published in Critical Reviews in Clinical Laboratory Sciences, 2018
Amogha Tadimety, Andrew Closson, Cathy Li, Song Yi, Ting Shen, John X. J. Zhang
Testing at the point of care allows a technology to be made available to a larger group because it can be used in a variety of settings [6]. When applying biosensors to point of care settings, there are a number of important qualities that improve their ease of use, as shown in Figure 3. In order to allow the sensor to be used in a widespread way, it should be generally low cost and easy to use. It is also advantageous for the sensor to use a small sample volume, and be high throughput with a rapid sample-to-answer format. Finally, for storage and transport of point of care devices, a small footprint, and no need for additional equipment improve their applicability.
SIT LESS: A prototype home-based system for monitoring older adults sedentary behavior
Published in Assistive Technology, 2020
Tzafit Tirkel, Yael Edan, Natalia Khvorostianov, Simona Bar-Haim
For commercial implementation price and reliability are important factors and therefore the system was based on inexpensive sensors and designed to be as simple as possible (Van de Watering, 2005). Simplicity is critical for success since the system aims for the older adults population (Fisk, Czaja, Rogers, Charness, & Sharit, 2009). Additionally, the availability and the cost of the sensor were considered along with finding a sensor that could be easily placed in the natural environment of the user without being attached to the user (i.e., not placed/worn on his/her body).
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