Pulmonary nodules: effect of adaptive statistical iterative reconstruction (ASIR) technique on performance of a computer-aided detection (CAD) system-comparison of performance between different-dose CT scans.
暂无分享,去创建一个
Noriyuki Tomiyama | Osamu Honda | Masahiro Yanagawa | Tomoko Gyobu | Mitsuhiro Koyama | Hiromitsu Sumikawa | T. Gyobu | O. Honda | N. Tomiyama | M. Koyama | H. Sumikawa | M. Yanagawa | Ayano Kikuyama | A. Kikuyama
[1] Cynthia H McCollough,et al. Estimating effective dose for CT using dose-length product compared with using organ doses: consequences of adopting International Commission on Radiological Protection publication 103 or dual-energy scanning. , 2010, AJR. American journal of roentgenology.
[2] Thin-section CT of lung without ECG gating: 64-detector row CT can markedly reduce cardiac motion artifact which can simulate lung lesions. , 2009, European journal of radiology.
[3] J. Austin,et al. Glossary of terms for CT of the lungs: recommendations of the Nomenclature Committee of the Fleischner Society. , 1996, Radiology.
[4] Alvin C. Silva,et al. Innovations in CT dose reduction strategy: application of the adaptive statistical iterative reconstruction algorithm. , 2010, AJR. American journal of roentgenology.
[5] Hironobu Nakamura,et al. Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases. , 2009, Academic radiology.
[6] Marco Das,et al. Small pulmonary nodules: effect of two computer-aided detection systems on radiologist performance. , 2006, Radiology.
[7] K. Bae,et al. Automated detection of pulmonary nodules on CT images: effect of section thickness and reconstruction interval--initial results. , 2005, Radiology.
[8] Jiang Hsieh,et al. Abdominal CT: comparison of adaptive statistical iterative and filtered back projection reconstruction techniques. , 2010, Radiology.
[9] K. Marten,et al. Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings , 2005, European Radiology.
[10] Anthony J. Sherbondy,et al. Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection. , 2005, Radiology.
[11] Lubomir M. Hadjiiski,et al. Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size. , 2009, Academic radiology.
[12] Kenji Suzuki. A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD). , 2009, Physics in medicine and biology.
[13] Jiang Hsieh,et al. Diffuse lung disease: CT of the chest with adaptive statistical iterative reconstruction technique. , 2010, Radiology.
[14] W. Heindel,et al. Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader , 2007, European Radiology.
[15] S. Swensen,et al. Lung cancer screening with CT: Mayo Clinic experience. , 2003, Radiology.
[16] Kyung Soo Lee,et al. Computer-Aided Detection of Lung Nodules: Influence of the Image Reconstruction Kernel for Computer-Aided Detection Performance , 2010, Journal of computer assisted tomography.
[17] Giang Nguyen,et al. A prospective evaluation of dose reduction and image quality in chest CT using adaptive statistical iterative reconstruction. , 2010, AJR. American journal of roentgenology.
[18] Samuel G Armato,et al. Automated detection of lung nodules in CT scans: effect of image reconstruction algorithm. , 2003, Medical physics.
[19] G Gamsu,et al. High-resolution CT of the lungs: an optimal approach. , 1987, Radiology.
[20] M. Kalra,et al. Radiation Dose Reduction With Chest Computed Tomography Using Adaptive Statistical Iterative Reconstruction Technique: Initial Experience , 2010, Journal of computer assisted tomography.
[21] M. Buchsbaum,et al. A new iterative reconstruction technique for attenuation correction in high-resolution positron emission tomography , 1996, European Journal of Nuclear Medicine.
[22] Suzuki Kenji. コンピュータ支援診断(CAD)における大規模トレーニング人工ニューラルネットワーク(MTANN)の利用による監視つき「病変拡張」フィルタ , 2009 .
[23] O. Miettinen,et al. Early Lung Cancer Action Project: overall design and findings from baseline screening , 1999, The Lancet.
[24] E. Samei,et al. Low-tube-voltage, high-tube-current multidetector abdominal CT: improved image quality and decreased radiation dose with adaptive statistical iterative reconstruction algorithm--initial clinical experience. , 2010, Radiology.
[25] T. Hirose,et al. Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy. , 2008, Academic radiology.
[26] K. Doi,et al. Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier. , 2008, Academic Radiology.
[27] Noriyuki Tomiyama,et al. Multidetector CT of the lung: image quality with garnet-based detectors. , 2010, Radiology.
[28] R. Sievert,et al. Book Reviews : Recommendations of the International Commission on Radiological Protection (as amended 1959 and revised 1962). I.C.R.P. Publication 6. 70 pp. PERGAMON PRESS. Oxford, London and New York, 1964. £1 5s. 0d. [TB/54] , 1964 .