Successive iterative restoration applied to streak artifact reduction in X-ray CT image of dento-alveolar region

Purpose X-ray computed tomography (CT) images in the dento-alveolar region are sometimes rendered unusable for diagnostic purposes due to the appearance of streak artifacts. The purpose of the study is to reduce streak artifacts appeared on dental and maxillofacial X-ray CT images by the application...

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Vydané v:International journal for computer assisted radiology and surgery Ročník 6; číslo 5; s. 635 - 640
Hlavní autori: Dong, Jian, Kondo, Atsushi, Abe, Kosuke, Hayakawa, Yoshihiko
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer-Verlag 01.09.2011
Predmet:
Algorithms
Computer Imaging
Computer Science
Health Informatics
Humans
Imaging
Maxilla - diagnostic imaging
Medicine
Medicine & Public Health
Original Article
Pattern Recognition and Graphics
Phantoms, Imaging
Radiographic Image Interpretation, Computer-Assisted
Radiography, Dental - methods
Radiology
Sensitivity and Specificity
Surgery
Tomography, X-Ray Computed - methods
Vision
Dento-alveolar imaging
X-ray CT image
Iterative restoration
Streak artifact reduction
Maxillofacial imaging
ISSN:1861-6410, 1861-6429, 1861-6429
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Shrnutí:Purpose X-ray computed tomography (CT) images in the dento-alveolar region are sometimes rendered unusable for diagnostic purposes due to the appearance of streak artifacts. The purpose of the study is to reduce streak artifacts appeared on dental and maxillofacial X-ray CT images by the application of modified iterative restoration method. Methods We took advantage of the aspect that adjacent CT images often depict very similar anatomical structures within the resulting collection of thin-slice images. CT images having streak artifacts were processed using the projection data of adjacent CT images. A modified iterative correction, the maximum likelihood-expectation maximization (ML-EM) reconstruction algorithm, was employed to reduce the streak artifact caused by metallic materials in the oral cavity. It approximates between the processed image and the original projection data. First, the projection data of an intact image were obtained, and then, the next image that had streak artifacts was processed. The projection data of the processed image were obtained, and the ML-EM method was applied to the next image again. Then, the successive iterative restoration was carried out. Results Twelve adjacent images were processed. Each iterative restoration was carried out fifty times. Streak artifacts were observed on processed images at the initial stage, but some of them either suppressed or disappeared as the iteration progressed. Conclusions The modified ML-EM method was effective to reduce streak artifacts in X-ray CT images in dento-alveolar region.
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ISSN:1861-6410
1861-6429
1861-6429
DOI:10.1007/s11548-010-0544-2