The harmful effects of ionizing radiation, as employed in a variety of medical imaging procedures, have
been well studied and documented. To minimize risk to patients, operators must continually assess the
dose rate and cumulative dose to the patient at each area of exposure. We have developed a computer
graphic dose management display system which provides this operator feedback. The system is comprised
of a signal processing module which reads the state of a fluoroscopy machine, a transmission ionization
chamber for exposure measurement, and a visualization of the patient that displays the current level of
radiation intensity and accumulated dose at every location on the body. The system shows the beam
projection and orientation of the machine and color-coded dose metrics on the patient graphic model in real
time. Additionally, a database system has been incorporated to allow for recording and playback of the
entire procedure.
Recent developments in CMOS image detectors are changing the way digital imaging is performed for many applications. The replacement of charge coupled devices (CCDs), with CMOS detectors is a desirable paradigm shift that will depend on the ability to match the high performance characteristics of CCDs. Digital X-ray imaging applications (chest X-ray, mammography) would benefit greatly from this shift because CMOS detectors have the following inherent characteristics: (1) Low operating power (5 - 10 times lower than CCD/processing electronics). (2) Standard CMOS manufacturing process (CCD requires special manufacturing). (3) On-chip integration of analog/digital processing functions (difficult with CCD). (4) Low Cost (5 - 10 times lower cost than CCD). The achievement of both low cost and low power is highly desirable for portable applications as well as situations where large, expensive X-ray imaging machines are not feasible (small hospitals and clinics, emergency medical vehicles, remote sites). Achieving this goal using commercially available components would allow rapid development of such digital X-ray systems as compared with the development difficulties incurred through specialized direct detectors and systems. The focus of this paper is to evaluate a CMOS image detector for medical X-ray applications and to demonstrate the results obtained from a prototype CMOS digital X-ray camera. Results from the images collected from this optically-coupled camera are presented for a particular lens, X-ray conversion screen, and demagnification factor. Further, an overview of the overall power consumption and cost of a multi-sensor CMOS mosaic compared to its CCD counterpart are also reported.
The development of an efficient parallel hardware architecture suitable for CCD-mosaic digital mammography has been accomplished. This paper presents this architecture including both the analog and digital portions of the imaging hardware. A two dimensional array of CCD sensors are used to capture the mammographic image synchronously and simultaneously. Each CCD's analog signal is converted to a 12 bits/pixel digital value through an array of high speed analog-to-digital converters. A parallel array of mesh connected TMS320C40 DSP processors then takes in the digital image data simultaneously. The DSP's are used to precisely register the mosaic of individual images to form the final large format digital mammogram. Also, they are used to control CCD characteristics and parallel data transport to the viewing workstation. One master DSP is located on the workstation's PCI bus which controls the parallel DSP array and collects compressed image data through a 60MB/s port. Since all computations are performed in parallel using local memory on each DSP, the overall acquisition, image registration, and transmission to display of the final mammogram is performed in less than 30 seconds. This allows the physician to perform a preliminary observation of the patient's mammogram.
Digital mosaic imaging techniques provide a cost effective means to acquiring high resolution images. Constrained mosaic imaging techniques make use of special purpose fiducial patterns in order to define a priori the relation between images on each tile. This 'inter-tile' relation is applied to any images acquired subsequently. A simulation study was carried out where a model of the digital mosaic imager was used. By doing so, it was possible to compare the original data to that reconstructed using different techniques. The effects of these technique so the quality of the final digital mosaic image wee investigated. The techniques were applied towards reconstructing mammogram images. In order to evaluate performance of the approach, a set of features of interest were selected to measure image quality. Features that are important to visual perception include micro-calcifications and other fine details on the image, as per a radiologist's suggestion. Features important to the computerized diagnostic software include, edge maps and other common features used in existing computerized mammogram analysis approaches. Results of this experimental study provide a better understanding of how mosaic reconstruction approaches affect the quality of the final image. The study is also helpful in defining the role that features of interest, be it from a visual perception or computer software point of view, play towards selecting the image reconstruction scheme better suited for digital mosaic mammography.
KEYWORDS: Distortion, Digital mammography, Digital imaging, CCD image sensors, Imaging systems, Cameras, Mammography, Digital signal processing, Charge-coupled devices, Image processing
Investigations in the area of digital mammography have been limited by the resolution of the sensor devices employed. We have proposed a multiple camera or mosaic architecture in which adjacent sensors observe an overlapping field of view. Such a technique can deliver extremely high resolution while simultaneously maintaining a moderate cost for the resultant instrument. However, this technique's clinical efficacy will be limited by the ability to accurately and precisely reconstruct a single continuous image from multiple CCD sensors. We present an integrated algorithm which will correct distortions introduced by the camera while addressing the problem of image reconstruction or 're- stitching.' Such a technique will minimize pixel loss by limiting image re-sampling to a single incident. Custom designed calibration screens were employed for the calculation of camera distortion and intra-camera disparity. A parallel digital signal processor architecture has been developed to accelerate system performance when employing a large number of camera inputs. We present a quantitative evaluation of our reconstruction technique and an analysis with respect to similar methods of image reconstruction. We have previously constructed and presented a prototype imager for digital radiography based upon a similar sensor architecture. The algorithm presented will significantly enhance the feasibility of our multiple camera architecture for both digital radiography and mammography. We believe that such a methodology will enhance diagnostic accuracy at a moderate cost when compared with system of similar imaging resolution.
Pre-production prototype of a low-cost, portable, compact digital radiographic imaging device which replaces current film based systems has been constructed and tested. Currently, it is in the process of full utilization for field hospitals where immediate verification of the results is essential. For the particular pre-production unit, image acquisition is performed by a 3 by 4 matrix of charge-coupled-device (CCD) imaging sensors which view the output of a standard x-ray scintillation screen via an off-the-shelf optical system. The use of multiple, moderately priced CCD sensors results in a high resolution system with a low cost of production relative to other digital imaging systems of comparable resolution. The field of view each CCD are purposefully overlapped so as to facilitate image reconstruction. The acquisition of each radiographic image formed on a scintillation screen results in the production of twelve sub- images. A software algorithm is employed to detect the regions of overlap and create a single continuous digital radiograph from the raw CCD data. Software methods are utilized to correct for barrel distortion affects that are caused by the use of low cost lens components.
A high-resolution, portable, digital x-ray imaging device which replaces current film based systems has been developed. The system is intended to be used in field hospitals where on-line verification is required during treatment. Image acquisition is performed by a 3 X 4 matrix of charge-coupled-device (CCD) imaging sensors which view the output of a standard x-ray scintillation screen via an off-the-shelf optical system. The use of multiple, moderately priced CCD units results in a high resolution system with a low cost of production relative to other digital imaging systems of comparable resolution. The fields of view of each CCD are purposefully overlapped so as to facilitate image reconstruction. The acquisition of each radiographic image formed on a scintillation screen results in the production of twelve sub- images. A software algorithm is employed to detect the regions of overlap and create a single, continuous digital radiograph from the raw CCD data. Software methods are utilized to correct for barrel distortion affects that are caused by the use of low cost lens components.
In determining temperature of surfaces by their blackbody emission, simultaneous acquisition of infrared emission at different wavelengths can provide a set of parameters needed to compute the absolute temperature of the object. A graybody model can be used to derive a set of equations that correlates the effects of emissivity variation and reflection of ambient radiation on the apparent and true temperatures of the object. Such a model is presented and its sensitivities to noise are evaluated. A four-wavelength digital thermal imager has been constructed to evaluate the practical implementation of the model. Finally, utilizing a phantom that simulates a graybody, and human skin data, the validity of the model has been demonstrated. It is shown that the system noise and the computational errors of series expansion are the factors that limit the precision of the computed temperature.
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