To suppress artifacts in X-ray digital tomosynthesis, a method which combines 3D and 2D region growing was proposed. However, it could not extract small metals such as pins, due to the discontinuity of the metal in the 3D projection data. A novel method is proposed to separate the metal from the projection data by combining pattern matching between neighboring projection angles and interpolating image pixels of enlarged projection data for each projection angle. The proposed method was compared with the conventional method based on 3D region growing. In a phantom experiment, the proposed method reduced the artifacts close to the metals. At a distance within 1 mm from the metal object, the mean absolute error evaluated without metal artifact correction (No MAC), with the conventional and proposed methods were 461.2, 461.2, and 100.2, respectively, and an improvement of more than 78% was demonstrated. When the distance from the object was shorter, the artifact became more significant in the No MAC and conventional methods, so the effectiveness of the proposed method was higher. Applying a suitable artifact correction on the basis of metal extraction makes it possible to effectively reduce artifacts in DT images.
We propose a new metal artifact correction method for the X-ray digital tomosynthesis by accurately detecting metal in the projection data. We combined 3D region growing for growing a few points in the metal to other projection angles and 2D region growing for growing the points further in order not to force the user to set the starting points at each projection angle. We compared the proposed method with the conventional FBP. In the phantom experiment with a mimicked artificial joint using the proposed method, the metal artifacts around the metal object were reduced. At the distance within 5 mm from the metal object, the root mean square errors evaluated with the conventional and proposed methods were 2700 and 200, respectively, and the root mean square errors improvement of more than 90% was demonstrated. When the distance from the metal object was shorter, the metal artifact became more significant in the conventional method, and the effectiveness of the proposed metal artifact correction was higher.
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].
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.
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