Recently, the double contrast technique in a gastrointestinal examination and the transbronchial lung biopsy in an examination for the respiratory system [1-3] have made a remarkable progress. Especially in the transbronchial lung biopsy, better quality of x-ray fluoroscopic images is requested because this examination is performed under a guidance of x-ray fluoroscopic images. On the other hand, various image processing methods [4] for x-ray fluoroscopic images have been developed as an x-ray system with a flat panel detector [5-7] is widely used. New noise reduction processing, Adaptive Noise Reduction [ANR], was announced in SPIE last year.[8] ANR is a new image processing technique which is capable of extracting and reducing noise components regardless of moving objects in fluoroscopy images. However, for further enhancement of noise reduction effect in clinical use, it was used in combination with a recursive filter, which is a time axis direction filter. Due to this, the recursive filter generated image lags when there are moving objects in the fluoroscopic images, and these image lags sometimes became hindrance in performing smooth bronchoscopy. This is because recursive filters reduce noise by adding multiple fluoroscopy images. Therefore, we have developed new image processing technique, Motion Tracking Noise Reduction [MTNR] for decreasing image lags as well as noise. This ground-breaking image processing technique detects global motion in images with high accuracy, determines the pixels to track the motion, and applies a motion tracking-type time filter. With this, image lags are removed remarkably while realizing the effective noise reduction. In this report, we will explain the effect of MTNR by comparing the performance of MTNR images [MTNR] and ANR + Recursive filter-applied images [ANR + Recursive filter].
Recently, the double contrast technique in a gastrointestinal examination and the transbronchial lung biopsy in an
examination for the respiratory system [1-3] have made a remarkable progress. Especially in the transbronchial lung
biopsy, better quality of x-ray fluoroscopic images is requested because this examination is performed under a guidance
of x-ray fluoroscopic images. On the other hand, various image processing methods [4] for x-ray fluoroscopic images
have been developed as an x-ray system with a flat panel detector [5-7] is widely used.
A recursive filtering is an effective method to reduce a random noise in x-ray fluoroscopic images. However it has a
limitation for its effectiveness of a noise reduction in case of a moving object exists in x-ray fluoroscopic images because
the recursive filtering is a noise reduction method by adding last few images. After recursive filtering a residual signal
was produced if a moving object existed in x-ray images, and this residual signal disturbed a smooth procedure of the
examinations.
To improve this situation, new noise reduction method has been developed. The Adaptive Noise Reduction [ANR] is
the brand-new noise reduction technique which can be reduced only a noise regardless of the moving object in x-ray
fluoroscopic images. Therefore the ANR is a very suitable noise reduction method for the transbronchial lung biopsy
under a guidance of x-ray fluoroscopic images because the residual signal caused of the moving object in x-ray
fluoroscopic images is never produced after the ANR. In this paper, we will explain an advantage of the ANR by
comparing of a performance between the ANR images and the conventional recursive filtering images.
KEYWORDS: Gain switching, Imaging systems, Radiography, Image quality, Medical imaging, Sensors, Algorithm development, X-ray imaging, Fluoroscopy, Signal to noise ratio
A digital radiography system using a flat-panel imager, which has a novel imaging technique for a radiography mode, has been developed. A radiographic image captured by the new imaging technique has a wide dynamic range in comparison with conventional radiographic images. The purpose of this presentation is to show the basic performance of the image quality acquired by the new imaging technique and compare it with an image taken by a conventional technique.
The flat-panel imager has a gain switching capability, normally used in a dynamic imaging mode for a cone-beam CT study. The gain switching method has two gain settings and switches between them automatically, depending on the incident dose to each pixel of flat-panel imager. As a result of the gain switching method, an image having wide dynamic range is achieved. In this study, we applied the gain switching method to the radiography mode, and achieved a radiographic image with wider dynamic range than a conventional radiograph. Furthermore, we have also developed an algorithm for calibration of the gain switching method in radiography mode.
A scintillator type Flat Panel Detector (FPD)1 has a good noise performance especially in Fluoroscopic images because of high DQE. Almost same dose as I.I. and CCD system is accepted in clinical use. According to the clinical study, the dose in fluoroscopy will be decreased if we can reduce the line noise coming from gate line of the Thin Film Transistor (TFT). The purpose of this study is to detect and reduce this line noise from the fluoroscopic images making it possible to perform a lower dose of fluoroscopy imaging. We detected the line noise by acquiring a dark image (without exposure) and then comparing the average of the line data along to the gate line to the neighborhood lines. We have applied this method to the dark area taken by the collimator of the Lucite phantom image and detected it. The detected line will be compensated by interpolation with neighborhood lines. The FPD of our system2 has a big detecting area (40cm x 30cm) and a zoom mode is selected in fluoroscopy because the doctor is watching an edge of the guide-wire and a contrast medium. The collimated area of the detector is displayed in a monitor after the zooming process and we can take a collimated dark area for detecting the line noise. As we applied this method to the dark image (1024pixels x 1024lines) including 54 lines with noise, we can improve 10% of SD. Visible line noise of chest phantom image was reduced with this method. It will help to lower the fluoroscopy dose.
KEYWORDS: Angiography, Sensors, Spatial resolution, Imaging systems, X-rays, Medical imaging, X-ray imaging, Modulation transfer functions, 3D image reconstruction, Detector development
A novel angiography system with cone-beam reconstruction using a large-area flat panel detector (FPD), with 40x30cm active area and 2048x1536 matrixes with a 194μm pixel pitch, has been developed. We present results on a basic performance, spatial resolution and contrast detectability obtained on this angiography system with cone-beam function using the FPD, and compare with a conventional angiography system with an image intensifier (I.I.) and charge-coupled device (CCD) camera.
We’d achieved a fast acquisition, 15 seconds as for a subtraction mode by rotating a ceiling suspended C-arm at a speed of 40 degrees per second, and ensured a large reconstructed columnar volume, φ250mmx180mm, by using the large-area detector. As a result of the evaluation, the 3D image acquired from the FPD system has a high spatial resolution with no distortion and good contrast detectability.
We developed prototype Digital Subtraction Angiography (DSA) System with a new large area FPD. Dynamic range, MTF, Contrast ratio and line noise were much improved. The improved FPD is a scintillator-type detector, and has a 40 x 30 cm active area, 2048 x 1536 matrix with 194um pixel pitch. The Prototype DSA system has two x-ray detectors, the FPD and the I.I.-CCD camera, and we can choose them on demand. All images captured from both detectors at 3 frames/sec in DSA mode and 30 frames/sec in Fluoroscopy mode are forwarded to our image-processing unit. We applied the new DSA system to more than 150 studies and compared the results with images from the I.I.-CCD. In DSA mode, FPD System, which has a wide dynamic range, large detecting area, and good contrast ratio yielded superior angiogram images compared with the I.I-CCD system. In Fluoroscopy mode, we improved line noise and increased the contrast of catheters and guide wires with a new image processing technique. With these improvements, the image quality of the FPD System is superior to the I.I.-CCD system at the exposure range of over 2uR/frame (17.4 nGy/frame).
KEYWORDS: Imaging systems, Cameras, Radiography, Signal to noise ratio, Modulation transfer functions, Sensors, Medical imaging, Fluoroscopy, X-ray detectors, Image quality
A new DR system using a large-area flat panel detector (FPD) with a 40 by 30 cm active area and a 194 micrometers pixel pitch, has been developed to compare with a conventional image intensifier and charge-coupled device camera type DR system. After measuring basic characteristics of the new DR system such as signal-to-noise ratio, modulation transfer function, and detective quantum efficiency, we applied the FPD to a Gastro-Intestinal study with contrast media, and discussed its potential for clinical use with a medical doctor. In radiography mode, the new DR system with a large-are FPD has superior image quality compared with the conventional I.I.- CCD camera type DR system because of high SNR and DQE. In fluoroscopy mode, the SNR of the new DR system at the exposure range of over 2(mu) R/frame is similar with the conventional I.I.-CCD camera type DR system. As a result, we considered that new DR system with a large-area FPD could be applied to a clinical study replacing an I.I.-CCD camera type. In the evaluation using various clinical images taken with the new DR system by a medical doctor, the new DR system with a large-are FPD performed sufficiently for a GI study.
In order to study the advantage and remaining problems of FPD (flat panel detector) for clinical use by the real-time DR (digital radiography) system, we developed a prototype system using a scintillator type FPD and which was compared with previous I.I.-CCD type real-time DR. We replaced the X- ray detector of DR-2000X from I.I.-4M (4 million pixels)-CCD camera to the scintillator type dynamic FPD(7' X 9', 127 micrometers ), which can take both radiographic and fluoroscopic images. We obtained the images of head and stomach phantoms, and discussed about the image quality with medical doctors.
We developed the automatically controlled X-rays compensating filter system (Automatic Filter System) to prevent the halation area that catheter's operation of the doctor in the angiography is obstructed. The algorithm which we have developed consists of the following five steps. 'Capture:' We take in a fluoroscopic image. 'Correction:' We correct the amount of decline by the X-rays compensating filter (filter) if the filter is already inserted. 'Detection:' We detect the halation area. 'Calculation:' We calculate an insertion position and rotate angle. 'Control:' We control the filter. We were able to get the following effects by the development of the Automatic Filter System. First, it was possible that the fluoroscopic image was displayed without losing contrast. Second, we were able to establish the most suitable X-rays conditions, such as tube voltage and tube current, for the region of interest (ROI), for example catheter and cardiovascular. And third, as the most important effect, we were able to decrease the exposure dose during the fluoroscopic procedure. Moreover, to confirm the validity of the Automatic Filter System, we applied this system to the angiography. As a result, we made sure that the operator could conduct the fluoroscopic procedure without manually control.
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