Paper
18 March 2015 A study on quality improvement of x-ray imaging of the respiratory-system based on a new image processing technique
Jun Torii, Yuichi Nagai, Tatsuya Horita, Yuuji Matsumoto, Takehiro Izumo, Mayumi Kitagawa, Kanyu Ihara, Tadashi Nakamura, Wataru Mukoyoshi, Kounosuke Tennmei, Katsumi Suzuki, Akio Hara, Shinji Sasada, Tomohiko Aso
Author Affiliations +
Abstract
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].
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jun Torii, Yuichi Nagai, Tatsuya Horita, Yuuji Matsumoto, Takehiro Izumo, Mayumi Kitagawa, Kanyu Ihara, Tadashi Nakamura, Wataru Mukoyoshi, Kounosuke Tennmei, Katsumi Suzuki, Akio Hara, Shinji Sasada, and Tomohiko Aso "A study on quality improvement of x-ray imaging of the respiratory-system based on a new image processing technique", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 941246 (18 March 2015); https://doi.org/10.1117/12.2080728
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KEYWORDS
Digital filtering

Image filtering

Image processing

Denoising

X-ray imaging

X-rays

Fluoroscopy

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