9,027 research outputs found
Using ordinal logistic regression to evaluate the performance of laser-Doppler predictions of burn-healing time
Background
Laser-Doppler imaging (LDI) of cutaneous blood flow is beginning to be used by burn surgeons to predict the healing time of burn wounds; predicted healing time is used to determine wound treatment as either dressings or surgery. In this paper, we do a statistical analysis of the performance of the technique.
Methods
We used data from a study carried out by five burn centers: LDI was done once between days 2 to 5 post burn, and healing was assessed at both 14 days and 21 days post burn. Random-effects ordinal logistic regression and other models such as the continuation ratio model were used to model healing-time as a function of the LDI data, and of demographic and wound history variables. Statistical methods were also used to study the false-color palette, which enables the laser-Doppler imager to be used by clinicians as a decision-support tool.
Results
Overall performance is that diagnoses are over 90% correct. Related questions addressed were what was the best blood flow summary statistic and whether, given the blood flow measurements, demographic and observational variables had any additional predictive power (age, sex, race, % total body surface area burned (%TBSA), site and cause of burn, day of LDI scan, burn center). It was found that mean laser-Doppler flux over a wound area was the best statistic, and that, given the same mean flux, women recover slightly more slowly than men. Further, the likely degradation in predictive performance on moving to a patient group with larger %TBSA than those in the data sample was studied, and shown to be small.
Conclusion
Modeling healing time is a complex statistical problem, with random effects due to multiple burn areas per individual, and censoring caused by patients missing hospital visits and undergoing surgery. This analysis applies state-of-the art statistical methods such as the bootstrap and permutation tests to a medical problem of topical interest. New medical findings are that age and %TBSA are not important predictors of healing time when the LDI results are known, whereas gender does influence recovery time, even when blood flow is controlled for.
The conclusion regarding the palette is that an optimum three-color palette can be chosen 'automatically', but the optimum choice of a 5-color palette cannot be made solely by optimizing the percentage of correct diagnoses
Digital Color Imaging
This paper surveys current technology and research in the area of digital
color imaging. In order to establish the background and lay down terminology,
fundamental concepts of color perception and measurement are first presented
us-ing vector-space notation and terminology. Present-day color recording and
reproduction systems are reviewed along with the common mathematical models
used for representing these devices. Algorithms for processing color images for
display and communication are surveyed, and a forecast of research trends is
attempted. An extensive bibliography is provided
Dual color plasmonic pixels create a polarization controlled nano color palette
Color filters based upon nanostructured metals have garnered significant interest in recent years, having been positioned as alternatives to the organic dye-based filters which provide color selectivity in image sensors, as nonfading “printing” technologies for producing images with nanometer pixel resolution, and as ultra-high-resolution, small foot-print optical storage and encoding solutions. Here, we demonstrate a plasmonic filter set with polarization-switchable color properties, based upon arrays of asymmetric cross-shaped nanoapertures in an aluminum thin-film. Acting as individual color-emitting nanopixels, the plasmonic cavity-apertures have dual-color selectivity, transmitting one of two visible colors, controlled by the polarization of the white light incident on the rear of the pixel and tuned by varying the critical dimensions of the geometry and periodicity of the array. This structural approach to switchable optical filtering enables a single nanoaperture to encode two information states within the same physical nanoaperture, an attribute we use here to create micro image displays containing duality in their optical information states
Polarization switchable two-color plasmonic nano-pixels for creating optical surfaces encoded with dual information states
We demonstrate tunable, polarization-dependent, dual-color plasmonic filters based upon arrays of asymmetric cross-shaped nano-apertures. Acting as individual color emitting nano-pixels, each aperture can selectively transmit one of 2 colors, switched by controlling the polarization of white-light incident on the rear of each pixel. By tuning the dimensions of the pixels we build a polarization sensitive color palette at resolutions far beyond the diffraction limit. Using this switchable color palette we are able to generate complex optical surfaces encoded with dual color and information states; allowing us to embed two color images within the same unit area, using the same set of nanoapertures. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only
Fast Color Quantization Using Weighted Sort-Means Clustering
Color quantization is an important operation with numerous applications in
graphics and image processing. Most quantization methods are essentially based
on data clustering algorithms. However, despite its popularity as a general
purpose clustering algorithm, k-means has not received much respect in the
color quantization literature because of its high computational requirements
and sensitivity to initialization. In this paper, a fast color quantization
method based on k-means is presented. The method involves several modifications
to the conventional (batch) k-means algorithm including data reduction, sample
weighting, and the use of triangle inequality to speed up the nearest neighbor
search. Experiments on a diverse set of images demonstrate that, with the
proposed modifications, k-means becomes very competitive with state-of-the-art
color quantization methods in terms of both effectiveness and efficiency.Comment: 30 pages, 2 figures, 4 table
Image-Processing Techniques for the Creation of Presentation-Quality Astronomical Images
The quality of modern astronomical data, the power of modern computers and
the agility of current image-processing software enable the creation of
high-quality images in a purely digital form. The combination of these
technological advancements has created a new ability to make color astronomical
images. And in many ways it has led to a new philosophy towards how to create
them. A practical guide is presented on how to generate astronomical images
from research data with powerful image-processing programs. These programs use
a layering metaphor that allows for an unlimited number of astronomical
datasets to be combined in any desired color scheme, creating an immense
parameter space to be explored using an iterative approach. Several examples of
image creation are presented.
A philosophy is also presented on how to use color and composition to create
images that simultaneously highlight scientific detail and are aesthetically
appealing. This philosophy is necessary because most datasets do not correspond
to the wavelength range of sensitivity of the human eye. The use of visual
grammar, defined as the elements which affect the interpretation of an image,
can maximize the richness and detail in an image while maintaining scientific
accuracy. By properly using visual grammar, one can imply qualities that a
two-dimensional image intrinsically cannot show, such as depth, motion and
energy. In addition, composition can be used to engage viewers and keep them
interested for a longer period of time. The use of these techniques can result
in a striking image that will effectively convey the science within the image,
to scientists and to the public.Comment: 104 pages, 38 figures, submitted to A
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