Kunio Doi to Radiographic Image Interpretation, Computer-Assisted
This is a "connection" page, showing publications Kunio Doi has written about Radiographic Image Interpretation, Computer-Assisted.
Connection Strength
10.922
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Quantitative measurements of emphysema in ultra-high resolution computed tomography using model-based iterative reconstruction in comparison to that using hybrid iterative reconstruction. Phys Eng Sci Med. 2022 Mar; 45(1):115-124.
Score: 0.655
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Computerized image-searching method for finding correct patients for misfiled chest radiographs in a PACS server by use of biological fingerprints. Radiol Phys Technol. 2013 Jul; 6(2):437-43.
Score: 0.361
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Computer-aided diagnosis and artificial intelligence in clinical imaging. Semin Nucl Med. 2011 Nov; 41(6):449-62.
Score: 0.323
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Evaluation of objective similarity measures for selecting similar images of mammographic lesions. J Digit Imaging. 2011 Feb; 24(1):75-85.
Score: 0.307
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Determination of similarity measures for pairs of mass lesions on mammograms by use of BI-RADS lesion descriptors and image features. Acad Radiol. 2009 Apr; 16(4):443-9.
Score: 0.270
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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: 0.270
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Observer study for evaluating potential utility of a super-high-resolution LCD in the detection of clustered microcalcifications on digital mammograms. J Digit Imaging. 2010 Apr; 23(2):161-9.
Score: 0.269
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Development of a voxel-matching technique for substantial reduction of subtraction artifacts in temporal subtraction images obtained from thoracic MDCT. J Digit Imaging. 2010 Feb; 23(1):31-8.
Score: 0.263
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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: 0.256
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Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier. Acad Radiol. 2008 Feb; 15(2):165-75.
Score: 0.249
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Determination of subjective similarity for pairs of masses and pairs of clustered microcalcifications on mammograms: comparison of similarity ranking scores and absolute similarity ratings. Med Phys. 2007 Jul; 34(7):2890-5.
Score: 0.239
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Evaluation of the image quality of temporal subtraction images produced automatically in a PACS environment. J Digit Imaging. 2006 Dec; 19(4):383-90.
Score: 0.230
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Computer-aided nodule detection on digital chest radiography: validation test on consecutive T1 cases of resectable lung cancer. J Digit Imaging. 2006 Dec; 19(4):376-82.
Score: 0.230
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Computerized detection of vertebral compression fractures on lateral chest radiographs: preliminary results with a tool for early detection of osteoporosis. Med Phys. 2006 Dec; 33(12):4664-74.
Score: 0.230
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Improving radiologists' recommendations with computer-aided diagnosis for management of small nodules detected by CT. Acad Radiol. 2006 Aug; 13(8):943-50.
Score: 0.224
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Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Acad Radiol. 2006 Aug; 13(8):995-1003.
Score: 0.224
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Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method. J Nucl Med. 2006 Jul; 47(7):1075-80.
Score: 0.223
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Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification. Med Phys. 2006 Jul; 33(7):2642-53.
Score: 0.223
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Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN). IEEE Trans Med Imaging. 2006 Apr; 25(4):406-16.
Score: 0.219
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Analysis and minimization of overtraining effect in rule-based classifiers for computer-aided diagnosis. Med Phys. 2006 Feb; 33(2):320-8.
Score: 0.217
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Computerized detection of intracranial aneurysms for three-dimensional MR angiography: feature extraction of small protrusions based on a shape-based difference image technique. Med Phys. 2006 Feb; 33(2):394-401.
Score: 0.217
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How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT? Acad Radiol. 2005 Oct; 12(10):1333-41.
Score: 0.212
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Computer-aided diagnosis in thoracic CT. Semin Ultrasound CT MR. 2005 Oct; 26(5):357-63.
Score: 0.212
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Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network. IEEE Trans Med Imaging. 2005 Sep; 24(9):1138-50.
Score: 0.211
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Investigation of psychophysical measure for evaluation of similar images for mammographic masses: preliminary results. Med Phys. 2005 Jul; 32(7):2295-304.
Score: 0.208
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False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network. Acad Radiol. 2005 Feb; 12(2):191-201.
Score: 0.202
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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: 0.199
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Computer-aided diagnosis scheme for histological classification of clustered microcalcifications on magnification mammograms. Med Phys. 2004 Apr; 31(4):789-99.
Score: 0.191
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Effect of high sensitivity in a computerized scheme for detecting extremely subtle solitary pulmonary nodules in chest radiographs: observer performance study. Acad Radiol. 2003 Nov; 10(11):1302-11.
Score: 0.186
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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: 0.183
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[Report on the 88th Scientific Assembly and Annual Meeting of the Radiological Society of North America: development of an image processing scheme for chest radiographs by using a dot printer]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2003 May; 59(5):619-20.
Score: 0.179
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Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images. Med Phys. 2003 Mar; 30(3):387-94.
Score: 0.177
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Computerized detection of pulmonary embolism in spiral CT angiography based on volumetric image analysis. IEEE Trans Med Imaging. 2002 Dec; 21(12):1517-23.
Score: 0.174
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[Development of an image processing scheme for chest radiographs using a dot printer]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2002 Sep; 58(9):1268-77.
Score: 0.171
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Automated computerized scheme for distinction between benign and malignant solitary pulmonary nodules on chest images. Med Phys. 2002 May; 29(5):701-8.
Score: 0.167
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Usefulness of an artificial neural network for differentiating benign from malignant pulmonary nodules on high-resolution CT: evaluation with receiver operating characteristic analysis. AJR Am J Roentgenol. 2002 Mar; 178(3):657-63.
Score: 0.165
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Use of an artificial neural network to determine the diagnostic value of specific clinical and radiologic parameters in the diagnosis of interstitial lung disease on chest radiographs. Acad Radiol. 2002 Jan; 9(1):13-7.
Score: 0.163
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Computer-aided diagnosis for detection of interstitial opacities on chest radiographs. AJR Am J Roentgenol. 1998 Dec; 171(6):1651-6.
Score: 0.132
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Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms. Med Phys. 1998 Aug; 25(8):1502-6.
Score: 0.129
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Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol. 1998 Mar; 5(3):155-68.
Score: 0.125
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Image feature analysis for computer-aided diagnosis: detection of right and left hemidiaphragm edges and delineation of lung field in chest radiographs. Med Phys. 1996 Sep; 23(9):1613-24.
Score: 0.113
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Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
Score: 0.109
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Computerized analysis of interstitial infiltrates on chest radiographs: a new scheme based on geometric pattern features and Fourier analysis. Acad Radiol. 1995 Jun; 2(6):455-62.
Score: 0.104
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Representation of lesion similarity by use of multidimensional scaling for breast masses on mammograms. J Digit Imaging. 2013 Aug; 26(4):740-7.
Score: 0.091
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Computer-aided diagnosis: development of automated schemes for quantitative analysis of radiographic images. Semin Ultrasound CT MR. 1992 Apr; 13(2):140-52.
Score: 0.083
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A computerized scheme for lung nodule detection in multiprojection chest radiography. Med Phys. 2012 Apr; 39(4):2001-12.
Score: 0.083
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[Science of similar images: quantitative evaluation on the similarity of images to be used in the next generation CAD]. Nihon Hoshasen Gijutsu Gakkai Zasshi. 2011; 67(4):400-12.
Score: 0.076
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Presentation of similar images as a reference for distinction between benign and malignant masses on mammograms: analysis of initial observer study. J Digit Imaging. 2010 Oct; 23(5):592-602.
Score: 0.071
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Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features. Phys Med Biol. 2009 Nov 21; 54(22):6881-99.
Score: 0.070
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Potential usefulness of similar images in the differential diagnosis of clustered microcalcifications on mammograms. Radiology. 2009 Dec; 253(3):625-31.
Score: 0.070
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Usefulness of texture analysis for computerized classification of breast lesions on mammograms. J Digit Imaging. 2007 Sep; 20(3):248-55.
Score: 0.060
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Comparison of typical evaluation methods for computer-aided diagnostic schemes: Monte Carlo simulation study. Med Phys. 2007 Mar; 34(3):871-6.
Score: 0.058
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Effect of temporal subtraction technique on interpretation time and diagnostic accuracy of chest radiography. AJR Am J Roentgenol. 2006 Nov; 187(5):1253-9.
Score: 0.057
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Computer-aided diagnosis scheme for identifying histological classification of clustered microcalcifications by use of follow-up magnification mammograms. Acad Radiol. 2006 Oct; 13(10):1219-28.
Score: 0.057
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Current status and future potential of computer-aided diagnosis in medical imaging. Br J Radiol. 2005; 78 Spec No 1:S3-S19.
Score: 0.050
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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: 0.048
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Automated lung nodule classification following automated nodule detection on CT: a serial approach. Med Phys. 2003 Jun; 30(6):1188-97.
Score: 0.045
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An automated patient recognition method based on an image-matching technique using previous chest radiographs in the picture archiving and communication system environment. Med Phys. 2001 Jun; 28(6):1093-7.
Score: 0.039
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Density correction of peripheral breast tissue on digital mammograms. Radiographics. 1996 Nov; 16(6):1403-11.
Score: 0.029
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Quantitative analysis of geometric-pattern features of interstitial infiltrates in digital chest radiographs: preliminary results. J Digit Imaging. 1996 Aug; 9(3):137-44.
Score: 0.028
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An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms. Med Phys. 1996 Apr; 23(4):595-601.
Score: 0.027
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Toward consensus on quantitative assessment of medical imaging systems. Med Phys. 1995 Jul; 22(7):1057-61.
Score: 0.026
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Computer-aided detection of clustered microcalcifications on digital mammograms. Med Biol Eng Comput. 1995 Mar; 33(2):174-8.
Score: 0.025
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Reduction of false positives in computerized detection of lung nodules in chest radiographs using artificial neural networks, discriminant analysis, and a rule-based scheme. J Digit Imaging. 1994 Nov; 7(4):196-207.
Score: 0.025
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Computer-aided diagnosis in chest radiography. Preliminary experience. Invest Radiol. 1993 Nov; 28(11):987-93.
Score: 0.023
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Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals. Med Phys. 1993 Nov-Dec; 20(6):1661-6.
Score: 0.023
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[Evaluation of the potential benefit of computer-aided diagnosis (CAD) for lung cancer screenings using photofluorography: analysis of an observer study]. Nihon Igaku Hoshasen Gakkai Zasshi. 1993 Oct 25; 53(10):1195-207.
Score: 0.023
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Automated selection of regions of interest for quantitative analysis of lung textures in digital chest radiographs. Med Phys. 1993 Jul-Aug; 20(4):975-82.
Score: 0.023
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Comparison of bilateral-subtraction and single-image processing techniques in the computerized detection of mammographic masses. Invest Radiol. 1993 Jun; 28(6):473-81.
Score: 0.023
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An "intelligent" workstation for computer-aided diagnosis. Radiographics. 1993 May; 13(3):647-56.
Score: 0.022
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Artificial neural networks in mammography: application to decision making in the diagnosis of breast cancer. Radiology. 1993 Apr; 187(1):81-7.
Score: 0.022
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Image feature analysis and computer-aided diagnosis in digital radiography: automated detection of pneumothorax in chest images. Med Phys. 1992 Sep-Oct; 19(5):1153-60.
Score: 0.021
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Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules. Invest Radiol. 1992 Aug; 27(8):587-97.
Score: 0.021
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Potential usefulness of computerized nodule detection in screening programs for lung cancer. Invest Radiol. 1992 Jun; 27(6):471-5.
Score: 0.021
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Small lung cancers: improved detection by use of bone suppression imaging--comparison with dual-energy subtraction chest radiography. Radiology. 2011 Dec; 261(3):937-49.
Score: 0.020
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Effect of heart-size parameters computed from digital chest radiographs on detection of cardiomegaly. Potential usefulness for computer-aided diagnosis. Invest Radiol. 1991 Jun; 26(6):546-50.
Score: 0.020
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[Computer-aided diagnosis of interstitial lung diseases]. Nihon Igaku Hoshasen Gakkai Zasshi. 1990 Jul 25; 50(7):753-66.
Score: 0.018
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Image feature analysis and computer-aided diagnosis in digital radiography: automated analysis of sizes of heart and lung in chest images. Med Phys. 1990 May-Jun; 17(3):342-50.
Score: 0.018
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Pulmonary nodules: computer-aided detection in digital chest images. Radiographics. 1990 Jan; 10(1):41-51.
Score: 0.018
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Computer-aided detection of microcalcifications in mammograms. Methodology and preliminary clinical study. Invest Radiol. 1988 Sep; 23(9):664-71.
Score: 0.016
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Image feature analysis and computer-aided diagnosis in digital radiography: detection and characterization of interstitial lung disease in digital chest radiographs. Med Phys. 1988 May-Jun; 15(3):311-9.
Score: 0.016
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Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields. Med Phys. 1988 Mar-Apr; 15(2):158-66.
Score: 0.016
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Digital image processing of dentomaxillofacial radiographs. Oral Surg Oral Med Oral Pathol. 1987 Oct; 64(4):485-93.
Score: 0.015
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Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. Med Phys. 1997 Sep; 24(9):1395-403.
Score: 0.008