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Proceedings Paper

A study on quality improvement of x-ray imaging of the respiratory-system based on a new image processing technique
Author(s): 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
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Paper 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].

Paper Details

Date Published: 18 March 2015
PDF: 7 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 941246 (18 March 2015); doi: 10.1117/12.2080728
Show Author Affiliations
Jun Torii, National Cancer Ctr. Hospital (Japan)
Yuichi Nagai, National Cancer Ctr. Hospital (Japan)
Tatsuya Horita, National Cancer Ctr. Hospital (Japan)
Yuuji Matsumoto, National Cancer Ctr. Hospital (Japan)
Takehiro Izumo, National Cancer Ctr. Hospital (Japan)
Mayumi Kitagawa, National Cancer Ctr. Hospital (Japan)
Kanyu Ihara, National Cancer Ctr. Hospital (Japan)
Tadashi Nakamura, Hitachi Medical Corp. (Japan)
Wataru Mukoyoshi, Hitachi Medical Corp. (Japan)
Kounosuke Tennmei, Hitachi Medical Corp. (Japan)
Katsumi Suzuki, Hitachi Medical Corp. (Japan)
Akio Hara, Hitachi Medical Corp. (Japan)
Shinji Sasada, National Cancer Ctr. Hospital (Japan)
Tomohiko Aso, National Cancer Ctr. Hospital (Japan)


Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

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