Junji Shiraishi to Tomography, X-Ray Computed
This is a "connection" page, showing publications Junji Shiraishi has written about Tomography, X-Ray Computed.
Connection Strength
2.941
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Improved detection of cholesterol gallstones using quasi-material decomposition images generated from single-energy computed tomography images via deep learning. Radiol Phys Technol. 2024 Jun; 17(2):360-366.
Score: 0.442
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Task-based assessment of resolution properties of CT images with a new index using deep convolutional neural network. Radiol Phys Technol. 2024 Mar; 17(1):83-92.
Score: 0.433
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[Application of Convolutional Neural Network for Evaluating CT Dose Using Image Noise Classification: A Phantom Study]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2020; 76(11):1143-1151.
Score: 0.331
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[Image Evaluation with Paired Comparison Method Using Automatic Analysis Software: Comparison of CT Images with Simulated Levels of Exposure Dose]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2019; 75(1):32-39.
Score: 0.309
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[Development of Automated Positioning System in General Radiography Examination-Application to Four Directions Cervical Spine Radiography]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2019; 75(4):305-313.
Score: 0.309
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A computer simulation method for low-dose CT images by use of real high-dose images: a phantom study. Radiol Phys Technol. 2016 Jan; 9(1):44-52.
Score: 0.245
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Modulation transfer function measurement of CT images by use of a circular edge method with a logistic curve-fitting technique. Radiol Phys Technol. 2015 Jan; 8(1):53-9.
Score: 0.229
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Development of an individual display optimization system based on deep convolutional neural network transition learning for somatostatin receptor scintigraphy. Radiol Phys Technol. 2024 Mar; 17(1):195-206.
Score: 0.109
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[Radiomics for Estimating Recurrence Risk of Patients with Lung Cancer by Using Survival Analysis]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2021; 77(2):153-159.
Score: 0.089
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Incident reports related to tasks performed by radiological technologists: an analysis of ten years of incident reports. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2015 02; 71(2):99-107.
Score: 0.059
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Temporal subtraction method for lung nodule detection on successive thoracic CT soft-copy images. Radiology. 2014 Apr; 271(1):255-61.
Score: 0.054
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Computer-aided diagnosis and artificial intelligence in clinical imaging. Semin Nucl Med. 2011 Nov; 41(6):449-62.
Score: 0.047
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[ROC analysis for evaluating the detectability of image unsharpness due to the patient's movement: phantom study comparing preview and diagnostic LCDs]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011; 67(7):772-8.
Score: 0.044
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Subjective similarity of patterns of diffuse interstitial lung disease on thin-section CT: an observer performance study. Acad Radiol. 2009 Apr; 16(4):477-85.
Score: 0.039
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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. Acad Radiol. 2008 Dec; 15(12):1505-12.
Score: 0.038
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Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization. Radiology. 2005 Nov; 237(2):684-90.
Score: 0.031
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Computer-aided diagnosis in thoracic CT. Semin Ultrasound CT MR. 2005 Oct; 26(5):357-63.
Score: 0.031
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Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. AJR Am J Roentgenol. 2004 Nov; 183(5):1209-15.
Score: 0.029
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Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening. Acad Radiol. 2004 Jun; 11(6):617-29.
Score: 0.028
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Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography. Med Phys. 2003 Sep; 30(9):2440-54.
Score: 0.027
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An investigation of radiologists' perception of lesion similarity: observations with paired breast masses on mammograms and paired lung nodules on CT images. Acad Radiol. 2008 Jul; 15(7):887-94.
Score: 0.009
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Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules. Med Phys. 2003 Oct; 30(10):2584-93.
Score: 0.007