Improving biomedical image quality with computers
Computerized image enhancement techniques used on biomedical radiographs and photomicrographs
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Computerized image enhancement techniques used on biomedical radiographs and photomicrographs
Computer program PROCSCAN developed to monitor profile of executable image during execution. Purpose to identify routines in which program is spending most of its time. PROSCAN very useful first step in optimization of program. PROSCAN samples program counter of executing image and compares its value to table of entry-point addresses to determine which subroutine is executing. Written in C (77 percent), Assembler (13 percent), and FORTRAN 77 (10 percent).
Computed tomography imaging spectrometers ("CTISs") employing a single lens are provided. The CTISs may be either transmissive or reflective, and the single lens is either configured to transmit and receive uncollimated light (in transmissive systems), or is configured to reflect and receive uncollimated light (in reflective systems). An exemplary transmissive CTIS includes a focal plane array detector, a single lens configured to transmit and receive uncollimated light, a two-dimensional grating, and a field stop aperture. An exemplary reflective CTIS includes a focal plane array detector, a single mirror configured to reflect and receive uncollimated light, a two-dimensional grating, and a field stop aperture.
Very high resolution stereoscopic images of high temperature loop structures observed at UV and X-ray wavelengths in the solar corona can be used to understand physical processes in the corona. An existing computational model is described and sample results are given to demonstrate that computational modeling of coronal structures can indeed take advantage of very high resolution images. The sample results include the run of temperature and number density along a typical loop and the variation of the differential emission measure with temperature. The integration of the differential emission measure with temperature along a column commensurate with an instrument's spatial resolution is the relevant parameter obtained from UV and X-ray observations. The effects of loop geometry and energy input are examined.
Computer algorithms to remove two types of degradations in IRAS sky-flux images, namely slowly varying background illumination (strongly effected by the presence of zodiacal light) and periodic stripes, are presented. This paper discusses both algorithms in detail and shows results of its use on various sky-flux images. Focus of the work was on the implementation within a workstation environment, and its value as a preprocessing tool for researchers. Speed of the process, usability of the programs, and correctness of the results were the main goals in developing these tools.
Fourier-transform spectroscopy using holographic imaging without computing and with stationary interferometers
In this study, we address the challenge of enhancing image quality and spatial resolution in computed tomography (CT) imaging by introducing simulation and fabrication of high aspect ratio, point-like transmission targets. Utilizing advanced electroplating techniques, traditionally employed in the fabrication of Through Substrate Via (TSV) interconnects for CMOS circuitry, we successfully embed copper targets within silicon substrates. This method allows us to create high-aspect-ratio features specifically designed for X-ray transmission targets, resulting in micro targets that exhibit a volume increase compared to conventional evaporated surface targets. Furthermore, we present simulation results of the X-ray spectrum generated by these targets, demonstrating their potential to significantly improve both image quality and spatial resolution in CT applications. Our findings suggest that leveraging advanced fabrication techniques can open new avenues for the development of enhanced imaging technologies in medical diagnostics and beyond.
Micrographs of PICA (Phenolic Impregnated Carbon Ablator) taken using a Scanning Electron Microscope (SEM) and 3D images taken with a Computed Tomography (CT) system are examined. PICA is a carbon fiber based composite (Fiberform ) with a phenolic polymer matrix. The micrographs are taken at different surface depths and at different magnifications in a sample after arc jet testing and show different levels of oxidative removal of the charred matrix (Figs 1 though 13). CT scans, courtesy of Xradia, Inc. of Concord CA, were captured for samples of virgin PICA, charred PICA and raw Fiberform (Fig. 14). We use these images to calculate the thermal conductivity (TC) of these materials using correlation function (CF) methods. CF methods give a mathematical description of how one material is embedded in another and is thus ideally suited for modeling composites like PICA. We will evaluate how the TC of the materials changes as a function of surface depth. This work is in collaboration with ETH-Zurich, which has expertise in high temperature materials and TC modeling (including CF methods).
Computer compatible tapes from LANDSAT were used to compartmentalize the Ires Marias reservoir according to respective grey level spectral response. Interactive and automatic, supervised classification, was executed from the IMAGE-100 system. From the simple correlation analysis and graphic representation, it is shown that grey tone levels are inversely proportional to Secchi Depth values. It is further shown that the most favorable period to conduct an analysis of this type is during the rainy season.
Computer-enhancement techniques applied to the SIR-A data from the Lisbon Valley area in the northern portion of the Paradox basin increased the value of the imagery in the development of geologically useful maps. The enhancement techniques include filtering to remove image speckle from the SIR-A data and combining these data with Landsat multispectral scanner data. A method well-suited for the combination of the data sets utilized a three-dimensional domain defined by intensity-hue-saturation (IHS) coordinates. Such a system allows the Landsat data to modulate image intensity, while the SIR-A data control image hue and saturation. Whereas the addition of Landsat data to the SIR-A image by means of a pixel-by-pixel ratio accentuated textural variations within the image, the addition of color to the combined images enabled isolation of areas in which gray-tone contrast was minimal. This isolation resulted in a more precise definition of stratigraphic units.
The optical system of this invention is an unique type of imaging spectrometer, i.e. an instrument that can determine the spectra of all points in a two-dimensional scene. The general type of imaging spectrometer under which this invention falls has been termed a computed-tomography imaging spectrometer (CTIS). CTIS's have the ability to perform spectral imaging of scenes containing rapidly moving objects or evolving features, hereafter referred to as transient scenes. This invention, a reflective CTIS with an unique two-dimensional reflective grating, can operate in any wavelength band from the ultraviolet through long-wave infrared. Although this spectrometer is especially useful for events it is also for investigation of some slow moving phenomena as in the life sciences.
The optical system of this invention is an unique type of imaging spectrometer, i.e. an instrument that can determine the spectra of all points in a two-dimensional scene. The general type of imaging spectrometer under which this invention falls has been termed a computed-tomography imaging spectrometer (CTIS). CTIS's have the ability to perform spectral imaging of scenes containing rapidly moving objects or evolving features, hereafter referred to as transient scenes. This invention, a reflective CTIS with an unique two-dimensional reflective grating, can operate in any wavelength band from the ultraviolet through long-wave infrared. Although this spectrometer is especially useful for rapidly occurring events it is also useful for investigation of some slow moving phenomena as in the life sciences.
This is an implementation of the hyperdimensional computing technique to classify images. It consists of a python script that trains the system for a set of images from a set of images (dataset) specified by the user. This training produces hardware configuration parameters and description vectors that are then loaded into the hardware description part of the project. The hardware description consists of hardware described in Verilog (a well known language for this purpose) that is synthesizable and can be implemented in a real chip. This hardware received the training information generated by python, and then is able to accept images to produce answers for each image on which category (class) from the pre-=trained ones the image belongs to. The hardware and python training scripts are configurable and documented. The advantage of hyperdimensional computing is its robustness to errors and the easy capability for online learning (refining the training during inference slowly over time), which this implementation supports.
Scientific requirements for He(+)(304 A) and energetic neutral atom (ENA) magnetospheric imaging, as well as the derived instrumental requirements are presented. Both ENA imaging of the hot plasma and EUV imaging of the cold plasma are highlighted. The question of the accuracy with which physically significant parameters can be extracted from actual images using computerized algorithms is addressed. An example of an ENA image analyzed by means of the Powell minimization algorithm is given. Automated unfolding of global magnetospheric images is also discussed. A Mercator projection of a model INA image is shown.
This review aims to provide valuable insights into how energy consumption in magnetic resonance imaging (MRI) and computed tomography (CT) scanners can be effectively monitored, managed, and reduced, thereby contributing to more sustainable medical imaging practices. Demand for advanced imaging technologies such as MRI and CT scanners continues to increase, and understanding the resultant impact on greenhouse gas emissions requires a thorough evaluation of their energy consumption. Here, this review examines the energy monitoring and consumption characteristics of MRI and CT scanners, highlighting potential approaches for energy savings. An overview of MRI and CT principles, hardware components, and their associated energy consumption is provided. After addressing the technical aspects, the hardware and software requirements essential for accurate energy metering are detailed. Baseline measurements of energy consumption data are then provided as a foundation to understand current usage patterns and identify areas for improvement. Ongoing efforts to reduce energy consumption are categorized into 3 main strategies: operations, scanner design enhancements, and active scanning techniques, including accelerated MRI protocols. Ultimately, we emphasize that achieving sustainability in medical imaging requires collaboration across disciplines. By incorporating eco-friendly design in new imaging equipment, we can reduce the environmental impact, promote sustainability, and set a health care industry standard for a healthier planet.
The author has identified the following significant results. The Iowa Geological Survey developed its own capability for producing color products from digitally enhanced LANDSAT data. Research showed that efficient production of enhanced images required full utilization of both computer and photographic enhancement procedures. The 29 August 1972 photo-optically enhanced color composite was more easily interpreted for land classification purposes than standard color composites.
An experimental, personal computer image processing system has been developed which provides a variety of processing functions in an environment that connects programs by means of a 'menu' for both casual and experienced users. The system is implemented by a compiled BASIC program that is coupled to assembly language subroutines. Image processing functions encompass subimage extraction, image coloring, area classification, histogramming, contrast enhancement, filtering, and pixel extraction.
A nonintrusive auxonometric system, based on the DARWIN image processor (Telewski et al. 1983 Plant Physiol 72: 177-181), is described and demonstrated in the analysis of gravitropism and thigmomorphogenesis in corn seedlings (Zea mays). Using this system, growth and bending of regularly shaped plants or organs can be quickly and accurately measured without, in any way, interfering with the plant. Furthermore, the growth and bending curves are automatically plotted. Thigmomorphogenesis in the aerial part of corn seedlings involves growth promotion at a low force load and growth retardation at higher force loads. The time courses of the two kinds of response are somewhat different, with retardation occurring immediately after mechanical perturbation and growth promotion taking somewhat longer to begin. Gravitropic experiments show that when dark-grown corn seedlings are placed on their side in the light, the resulting curvature is due to two consecutive morphological mechanisms. In the first instance, lasting for about 15 minutes, the elongation of the bottom edge of the plant accelerates, while the elongation of the top edge remains constant. After that, for the next 1.75 hours, the elongation of the top edge decelerates and stops while that of the bottom edge remains constant at the increased rate for most of the period. The measurements taken from both experiments at relatively high resolution (0.08-0.1 millimeter) show that the growth curves are not smooth but show many small irregularities which may or may not involve micronutations.