Kunio Doi to Pattern Recognition, Automated
This is a "connection" page, showing publications Kunio Doi has written about Pattern Recognition, Automated.
Connection Strength
4.338
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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: 0.414
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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: 0.351
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Computer-aided diagnosis of focal liver lesions by use of physicians' subjective classification of echogenic patterns in baseline and contrast-enhanced ultrasonography. Acad Radiol. 2009 Apr; 16(4):401-11.
Score: 0.309
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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: 0.309
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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: 0.309
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Usefulness of computer-aided diagnosis schemes for vertebral fractures and lung nodules on chest radiographs. AJR Am J Roentgenol. 2008 Jul; 191(1):260-5.
Score: 0.293
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Development of a computer-aided diagnostic scheme for detection of interval changes in successive whole-body bone scans. Med Phys. 2007 Jan; 34(1):25-36.
Score: 0.264
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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: 0.251
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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: 0.242
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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: 0.241
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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: 0.232
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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: 0.210
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Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. Med Phys. 2003 Jul; 30(7):1602-17.
Score: 0.207
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A computerized scheme for lung nodule detection in multiprojection chest radiography. Med Phys. 2012 Apr; 39(4):2001-12.
Score: 0.095
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Clinical utility of temporal subtraction images in successive whole-body bone scans: evaluation in a prospective clinical study. J Digit Imaging. 2011 Aug; 24(4):680-7.
Score: 0.091
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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: 0.080
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Differentiation of common large sellar-suprasellar masses effect of artificial neural network on radiologists' diagnosis performance. Acad Radiol. 2009 Mar; 16(3):313-20.
Score: 0.077
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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: 0.064
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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: 0.062
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Investigation of misfiled cases in the PACS environment and a solution to prevent filing errors for chest radiographs. Acad Radiol. 2005 Jan; 12(1):97-103.
Score: 0.058
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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: 0.055
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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: 0.052
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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: 0.051
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Automatic detection of abnormalities in chest radiographs using local texture analysis. IEEE Trans Med Imaging. 2002 Feb; 21(2):139-49.
Score: 0.012
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Potential usefulness of an artificial neural network for differential diagnosis of interstitial lung diseases: pilot study. Radiology. 1990 Dec; 177(3):857-60.
Score: 0.005
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Pulmonary nodules: computer-aided detection in digital chest images. Radiographics. 1990 Jan; 10(1):41-51.
Score: 0.005