X-ray: Medical & Dental

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Motion Control AC/DC Adaptor

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Description

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Integrate and save power with the AFE0064, 64 channel analog front end for flat panel digital X-Ray systems. This device includes 64 integrators, a PGA for full scale charge level selection, correlated double sample, 64 as-to-2 multiplexer, two differential output drivers and a power saving nap feature.

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Digital x-ray imaging is revolutionizing diagnostic radiology. With conventional x-ray systems, the signal degradation from each component consumes more than 60% of the original x-ray signal. At each system stage, the x-ray signal is degraded to some extent, even if the individual components are optimized for the application. As a result, typically less than 40% of the original image information is available to produce an image. By adding a digital detector to digital x-ray imaging, it’s possible to capture more than 80% of the original image information and use a wide-range of post-processing tools to further improve the image. Other digital x-ray technology advantages include: reduced patient dosage, reduced diagnosis time by elimination of photographic processing, reduced costs by eliminating photographic processing chemicals, processing image data to highlight regions of interest and suppress irrelevant information; combining image data with other pertinent patient RIS/HIS systems information available; quickly transmitting the information anywhere over network connections; and archiving all desired information in a minimal space. There are two different approaches to digital x-ray technology, direct and indirect.

Direct Conversion

In direct conversion, flat-panel selenium detectors absorb x-rays directly and convert them into individual pixel electrical charges. In indirect conversion, x-ray signals first are converted to light, then converted to electric charges. Both tiled CCD (charge-coupled device) arrays and computed tomography use indirect conversion technology. Tiled CCD transitional technology employs multiple CCDs coupled to a scintillator plate via fiber optics. Computed tomography involves trapping electrons on photo-stimulated plates and then exposing them to generate image data. In both approaches, charges proportional to x-ray intensity seen by the pixel is stored in the Thin Film Transistor (TFT) storage cap. A number of such pixels form the Flat Detector Panel (FDP). The charges are deciphered by read-out electronics from the FDP and transformed into digital data.

The following block diagram shows the readout electronics required for direct imaging to convert the charge in the FDP to digital data. It has two chains: the acquisition and the biasing ones. At the beginning of the acquisition chain, an analog front-end is capable of multiplexing the charges on different FDP (channels) storage caps and converting these charges into voltage. The biasing chain generates bias voltages for the TFT array through intermediate bias-and-gate control circuitry. Digital control and data conditioning is controlled by an FPGA, which also manages high-speed serial communications with the external image processing unit through a high-speed interface (serialized, LVDS, optical). Temperature sensors, DACs, amplifiers and high-input voltage capable switching regulators are other key system blocks. Each block must have an enable pin and synchronize frequencies to avoid crosstalk with other blocks in the acquisition chain. The number of FDP pixels will determine the number of ADC channels vs. the ADC speed. Static or dynamic acquisition also determines the ADC speed. While static acquisition means a single image in less than 1s, dynamic means an image is refreshed at 30Hz, for more specific cardiovascular, fluoroscopic or related applications that require much faster data conversion with the same number of channels. An ADC in the range of 2MSPS and more with excellent DC performance will work well.

Indirect Conversion

For indirect conversion, the  CCD output requires correlated double sampling (CDS). The signal level’s reset voltages and image signal level are converted to digital data by an Analog Front End (AFE).. The sampling speed of the AFE is determined by the number of pixels in the CCD array and the frame rate. In addition, the AFE corrects sensor errors such as dark current correction, offset voltages and defective pixels. Depending on the signal level, the presence of Programmable Gain Amplifiers (PGAs), the linearity of the PGAs and the range of gains available may also be important. During digitization, the number of bits will determine the contrast of the image. Typically, one wants to digitize the initial data with two to four bits more precision than is desired in the final image. Thus, if 8-bits of final image data are required, then initially digitize to 10-bits to allow for rounding errors during image processing.

The main metric for image quality is “Detection Quantum Efficiency” (DQE), a combination of contrast and SNR expressed in percentage. The higher the contrast and lower the noise, the higher is the DQE. Contrast is the number of shades of gray, determined by the ADC’s output resolution Generally, 14-bits or 16-bits will be suitable for the application. SNR indicates not only SNR from the ADC, but system SNR impact from x-ray dose, pixel size and all electronic components. SNR can be improved by increasing x-ray dose, increasing photodiode spacing and decreasing electronics noise. Increasing the x-ray dose is not suitable for patients or operators. Increasing photodiode spacing may also not be suitable, because this decreases spatial resolution. Decreasing the noise from the system’s electronics is the main challenge. The total noise in the system is: root-square-sum of all noise contributions over the signal chain assuming all are uncorrelated. This means that all parts have to be ultra-low noise or heavily filtered when applicable including ADCs, op amps and references. Stability over temperature is another important challenge. Internal temperature increases due to power dissipation may off-set gray levels and distort an image especially during dynamic acquisitions. Hence, temperature stability of ADCs, op amps and references should be high.

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Application Notes (3)

Title Abstract Type Size (KB) Date Views
HTM 8 KB 29 Aug 2012 1061
HTM 9 KB 08 Jun 2010 201
HTM 8 KB 08 Jun 2010 70
    

Selection and Solution Guides

Selection Guides (2)

Title Abstract Type Size (KB) Date Views
PDF 9.09 MB 02 May 2013 3003
PDF 2.38 MB 08 Jun 2010 731

Solution Guides (1)

Title Abstract Type Size (KB) Date Views
PDF 2.05 MB 31 Oct 2014 15249

Tools and Software

Name Part # Company Software/Tool Type
Medical Imaging Software Tool Kits (STK) S2MEDDUS Texas Instruments Application Software & Frameworks

Product Bulletin & White Papers

White Papers (5)

Title Abstract Type Size (MB) Date Views
PDF 333 KB 08 Jun 2010 248
PDF 180 KB 26 Oct 2009 264
PDF 358 KB 18 Mar 2009 12
PDF 115 KB 03 Nov 2008 222
PDF 187 KB 31 Oct 2008 230

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