Maryellen L. Giger to Breast Neoplasms
This is a "connection" page, showing publications Maryellen L. Giger has written about Breast Neoplasms.
Connection Strength
8.406
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Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI. Med Phys. 2024 Mar; 51(3):1812-1821.
Score: 0.355
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Past, Present, and Future of Machine Learning and Artificial Intelligence for Breast Cancer Screening. J Breast Imaging. 2022 Oct 10; 4(5):451-459.
Score: 0.334
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Clinical Artificial Intelligence Applications: Breast Imaging. Radiol Clin North Am. 2021 Nov; 59(6):1027-1043.
Score: 0.313
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Robustness of radiomic features of benign breast lesions and hormone receptor positive/HER2-negative cancers across DCE-MR magnet strengths. Magn Reson Imaging. 2021 10; 82:111-121.
Score: 0.306
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A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI. Sci Rep. 2020 06 29; 10(1):10536.
Score: 0.286
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Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution. Cancer Imaging. 2019 Sep 18; 19(1):64.
Score: 0.270
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Artificial intelligence in the interpretation of breast cancer on MRI. J Magn Reson Imaging. 2020 05; 51(5):1310-1324.
Score: 0.268
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Radiomics robustness assessment and classification evaluation: A two-stage method demonstrated on multivendor FFDM. Med Phys. 2019 May; 46(5):2145-2156.
Score: 0.261
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Digital Mammography in Breast Cancer: Additive Value of Radiomics of Breast Parenchyma. Radiology. 2019 04; 291(1):15-20.
Score: 0.260
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Transfer Learning From Convolutional Neural Networks for Computer-Aided Diagnosis: A Comparison of Digital Breast Tomosynthesis and Full-Field Digital Mammography. Acad Radiol. 2019 06; 26(6):735-743.
Score: 0.250
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Additive Benefit of Radiomics Over Size Alone in the Distinction Between Benign Lesions and Luminal A Cancers on a Large Clinical Breast MRI Dataset. Acad Radiol. 2019 02; 26(2):202-209.
Score: 0.246
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Most-enhancing tumor volume by MRI radiomics predicts recurrence-free survival "early on" in neoadjuvant treatment of breast cancer. Cancer Imaging. 2018 Apr 13; 18(1):12.
Score: 0.245
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A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets. Med Phys. 2017 Oct; 44(10):5162-5171.
Score: 0.234
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MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays. Radiology. 2016 Nov; 281(2):382-391.
Score: 0.214
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Automated Breast Ultrasound in Breast Cancer Screening of Women With Dense Breasts: Reader Study of Mammography-Negative and Mammography-Positive Cancers. AJR Am J Roentgenol. 2016 Jun; 206(6):1341-50.
Score: 0.213
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Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage. Cancer. 2016 Mar 01; 122(5):748-57.
Score: 0.208
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Using quantitative image analysis to classify axillary lymph nodes on breast MRI: a new application for the Z 0011 Era. Eur J Radiol. 2015 Mar; 84(3):392-397.
Score: 0.194
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Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study. Breast Cancer Res. 2014; 16(4):424.
Score: 0.190
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Residual analysis of the water resonance signal in breast lesions imaged with high spectral and spatial resolution (HiSS) MRI: a pilot study. Med Phys. 2014 Jan; 41(1):012303.
Score: 0.182
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Computerized detection of breast cancer on automated breast ultrasound imaging of women with dense breasts. Med Phys. 2014 Jan; 41(1):012901.
Score: 0.182
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Breast image analysis for risk assessment, detection, diagnosis, and treatment of cancer. Annu Rev Biomed Eng. 2013; 15:327-57.
Score: 0.174
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Interreader scoring variability in an observer study using dual-modality imaging for breast cancer detection in women with dense breasts. Acad Radiol. 2013 Jul; 20(7):847-53.
Score: 0.173
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Repeatability in computer-aided diagnosis: application to breast cancer diagnosis on sonography. Med Phys. 2010 Jun; 37(6):2659-69.
Score: 0.142
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Update on the potential of computer-aided diagnosis for breast cancer. Future Oncol. 2010 Jan; 6(1):1-4.
Score: 0.138
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Automated method for improving system performance of computer-aided diagnosis in breast ultrasound. IEEE Trans Med Imaging. 2009 Jan; 28(1):122-8.
Score: 0.129
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Breast US computer-aided diagnosis workstation: performance with a large clinical diagnostic population. Radiology. 2008 Aug; 248(2):392-7.
Score: 0.124
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Multimodality computerized diagnosis of breast lesions using mammography and sonography. Acad Radiol. 2005 Aug; 12(8):970-9.
Score: 0.102
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Computerized analysis of images in the detection and diagnosis of breast cancer. Semin Ultrasound CT MR. 2004 Oct; 25(5):411-8.
Score: 0.096
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Differences in Molecular Subtype Reference Standards Impact AI-based Breast Cancer Classification with Dynamic Contrast-enhanced MRI. Radiology. 2023 04; 307(1):e220984.
Score: 0.085
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Computerized analysis of lesions in US images of the breast. Acad Radiol. 1999 Nov; 6(11):665-74.
Score: 0.068
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Radiogenomics of breast cancer using dynamic contrast enhanced MRI and gene expression profiling. Cancer Imaging. 2019 Jul 15; 19(1):48.
Score: 0.067
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Relationships Between Human-Extracted MRI Tumor Phenotypes of Breast Cancer and Clinical Prognostic Indicators Including Receptor Status and Molecular Subtype. Curr Probl Diagn Radiol. 2019 Sep - Oct; 48(5):467-472.
Score: 0.063
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Automated seeded lesion segmentation on digital mammograms. IEEE Trans Med Imaging. 1998 Aug; 17(4):510-7.
Score: 0.063
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Fast bilateral breast coverage with high spectral and spatial resolution (HiSS) MRI at 3T. J Magn Reson Imaging. 2017 11; 46(5):1341-1348.
Score: 0.057
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Computer-aided methods help cancer diagnoses. Diagn Imaging (San Franc). 1996 Nov; Suppl Digital X:D17-20.
Score: 0.055
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Clinical significance of noncalcified lung nodules in patients with breast cancer. Breast Cancer Res Treat. 2016 Sep; 159(2):265-71.
Score: 0.055
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Deciphering Genomic Underpinnings of Quantitative MRI-based Radiomic Phenotypes of Invasive Breast Carcinoma. Sci Rep. 2015 Dec 07; 5:17787.
Score: 0.052
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Computerized characterization of mammographic masses: analysis of spiculation. Cancer Lett. 1994 Mar 15; 77(2-3):201-11.
Score: 0.046
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Mammographic quantitative image analysis and biologic image composition for breast lesion characterization and classification. Med Phys. 2014 Mar; 41(3):031915.
Score: 0.046
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Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers. Med Phys. 2014 Mar; 41(3):031917.
Score: 0.046
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Potential of computer-aided diagnosis of high spectral and spatial resolution (HiSS) MRI in the classification of breast lesions. J Magn Reson Imaging. 2014 Jan; 39(1):59-67.
Score: 0.045
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Computers aid diagnosis of breast abnormalities. Diagn Imaging (San Franc). 1993 Jun; 15(6):98-102, 113.
Score: 0.044
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Quantitative ultrasound image analysis of axillary lymph node status in breast cancer patients. Int J Comput Assist Radiol Surg. 2013 Nov; 8(6):895-903.
Score: 0.043
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Computerized analysis of mammographic parenchymal patterns on a large clinical dataset of full-field digital mammograms: robustness study with two high-risk datasets. J Digit Imaging. 2012 Oct; 25(5):591-8.
Score: 0.042
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A scaling transformation for classifier output based on likelihood ratio: applications to a CAD workstation for diagnosis of breast cancer. Med Phys. 2012 May; 39(5):2787-804.
Score: 0.041
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Re: effectiveness of computer-aided detection in community mammography practice. J Natl Cancer Inst. 2012 Jan 04; 104(1):77; author reply 78-9.
Score: 0.040
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Computerized three-class classification of MRI-based prognostic markers for breast cancer. Phys Med Biol. 2011 Sep 21; 56(18):5995-6008.
Score: 0.039
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Combined use of T2-weighted MRI and T1-weighted dynamic contrast-enhanced MRI in the automated analysis of breast lesions. Magn Reson Med. 2011 Aug; 66(2):555-64.
Score: 0.038
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Evaluation of clinical breast MR imaging performed with prototype computer-aided diagnosis breast MR imaging workstation: reader study. Radiology. 2011 Mar; 258(3):696-704.
Score: 0.037
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Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI. Acad Radiol. 2010 Sep; 17(9):1158-67.
Score: 0.036
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Enhancement of breast CADx with unlabeled data. Med Phys. 2010 Aug; 37(8):4155-72.
Score: 0.036
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Computerized assessment of breast lesion malignancy using DCE-MRI robustness study on two independent clinical datasets from two manufacturers. Acad Radiol. 2010 Jul; 17(7):822-9.
Score: 0.036
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Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. Radiology. 2010 Mar; 254(3):680-90.
Score: 0.035
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Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE. Med Phys. 2010 Jan; 37(1):339-51.
Score: 0.034
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Breast US computer-aided diagnosis system: robustness across urban populations in South Korea and the United States. Radiology. 2009 Dec; 253(3):661-71.
Score: 0.034
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Correlative feature analysis on FFDM. Med Phys. 2008 Dec; 35(12):5490-500.
Score: 0.032
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Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM. Med Phys. 2008 Dec; 35(12):5799-820.
Score: 0.032
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Evaluation of computer-aided diagnosis on a large clinical full-field digital mammographic dataset. Acad Radiol. 2008 Nov; 15(11):1437-45.
Score: 0.032
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Prevalence scaling: applications to an intelligent workstation for the diagnosis of breast cancer. Acad Radiol. 2008 Nov; 15(11):1446-57.
Score: 0.032
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Performance of breast ultrasound computer-aided diagnosis: dependence on image selection. Acad Radiol. 2008 Oct; 15(10):1234-45.
Score: 0.032
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DCEMRI of breast lesions: is kinetic analysis equally effective for both mass and nonmass-like enhancement? Med Phys. 2008 Jul; 35(7):3102-9.
Score: 0.031
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Potential effect of different radiologist reporting methods on studies showing benefit of CAD. Acad Radiol. 2008 Feb; 15(2):139-52.
Score: 0.030
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Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment. J Digit Imaging. 2008 Jun; 21(2):145-52.
Score: 0.030
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A dual-stage method for lesion segmentation on digital mammograms. Med Phys. 2007 Nov; 34(11):4180-93.
Score: 0.030
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Volumetric texture analysis of breast lesions on contrast-enhanced magnetic resonance images. Magn Reson Med. 2007 Sep; 58(3):562-71.
Score: 0.029
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Fractal analysis of mammographic parenchymal patterns in breast cancer risk assessment. Acad Radiol. 2007 May; 14(5):513-21.
Score: 0.029
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Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI. Med Phys. 2006 Aug; 33(8):2878-87.
Score: 0.027
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Computerized mass detection for digital breast tomosynthesis directly from the projection images. Med Phys. 2006 Feb; 33(2):482-91.
Score: 0.026
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A fuzzy c-means (FCM)-based approach for computerized segmentation of breast lesions in dynamic contrast-enhanced MR images. Acad Radiol. 2006 Jan; 13(1):63-72.
Score: 0.026
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Computerized texture analysis of mammographic parenchymal patterns of digitized mammograms. Acad Radiol. 2005 Jul; 12(7):863-73.
Score: 0.025
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Computerized detection of mass lesions in digital breast tomosynthesis images using two- and three dimensional radial gradient index segmentation. Technol Cancer Res Treat. 2004 Oct; 3(5):437-41.
Score: 0.024
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Computerized detection and classification of cancer on breast ultrasound. Acad Radiol. 2004 May; 11(5):526-35.
Score: 0.023
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Computerized interpretation of breast MRI: investigation of enhancement-variance dynamics. Med Phys. 2004 May; 31(5):1076-82.
Score: 0.023
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Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography. Acad Radiol. 2004 Mar; 11(3):272-80.
Score: 0.023
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Computerized analysis of mammographic parenchymal patterns for assessing breast cancer risk: effect of ROI size and location. Med Phys. 2004 Mar; 31(3):549-55.
Score: 0.023
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Estimating three-class ideal observer decision variables for computerized detection and classification of mammographic mass lesions. Med Phys. 2004 Jan; 31(1):81-90.
Score: 0.023
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Computerized analysis of shadowing on breast ultrasound for improved lesion detection. Med Phys. 2003 Jul; 30(7):1833-42.
Score: 0.022
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Computerized analysis of digitized mammograms of BRCA1 and BRCA2 gene mutation carriers. Radiology. 2002 Nov; 225(2):519-26.
Score: 0.021
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Breast cancer: effectiveness of computer-aided diagnosis observer study with independent database of mammograms. Radiology. 2002 Aug; 224(2):560-8.
Score: 0.021
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Computerized lesion detection on breast ultrasound. Med Phys. 2002 Jul; 29(7):1438-46.
Score: 0.021
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Computerized diagnosis of breast lesions on ultrasound. Med Phys. 2002 Feb; 29(2):157-64.
Score: 0.020
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Computer-aided diagnosis in radiology. Acad Radiol. 2002 Jan; 9(1):1-3.
Score: 0.020
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Computer-aided diagnosis in medical imaging. IEEE Trans Med Imaging. 2001 Dec; 20(12):1205-8.
Score: 0.020
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Computerized analysis of multiple-mammographic views: potential usefulness of special view mammograms in computer-aided diagnosis. IEEE Trans Med Imaging. 2001 Dec; 20(12):1285-92.
Score: 0.020
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Automatic segmentation of breast lesions on ultrasound. Med Phys. 2001 Aug; 28(8):1652-9.
Score: 0.019
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Computerized classification of benign and malignant masses on digitized mammograms: a study of robustness. Acad Radiol. 2000 Dec; 7(12):1077-84.
Score: 0.018
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Computer-aided detection and diagnosis of breast cancer. Radiol Clin North Am. 2000 Jul; 38(4):725-40.
Score: 0.018
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Computerized analysis of mammographic parenchymal patterns for breast cancer risk assessment: feature selection. Med Phys. 2000 Jan; 27(1):4-12.
Score: 0.017
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Effect of dominant features on neural network performance in the classification of mammographic lesions. Phys Med Biol. 1999 Oct; 44(10):2579-95.
Score: 0.017
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Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol. 1999 Jan; 6(1):22-33.
Score: 0.016
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Computerized analysis of breast lesions in three dimensions using dynamic magnetic-resonance imaging. Med Phys. 1998 Sep; 25(9):1647-54.
Score: 0.016
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Automated computerized classification of malignant and benign masses on digitized mammograms. Acad Radiol. 1998 Mar; 5(3):155-68.
Score: 0.015
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Malignant and benign clustered microcalcifications: automated feature analysis and classification. Radiology. 1996 Mar; 198(3):671-8.
Score: 0.013
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Analysis of spiculation in the computerized classification of mammographic masses. Med Phys. 1995 Oct; 22(10):1569-79.
Score: 0.013
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Automated segmentation of digitized mammograms. Acad Radiol. 1995 Jan; 2(1):1-9.
Score: 0.012
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Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network. Med Phys. 1994 Apr; 21(4):517-24.
Score: 0.012
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Computer vision and artificial intelligence in mammography. AJR Am J Roentgenol. 1994 Mar; 162(3):699-708.
Score: 0.012
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Computerized detection of masses in digital mammograms: automated alignment of breast images and its effect on bilateral-subtraction technique. Med Phys. 1994 Mar; 21(3):445-52.
Score: 0.012
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Computerized detection of masses in digital mammograms: investigation of feature-analysis techniques. J Digit Imaging. 1994 Feb; 7(1):18-26.
Score: 0.011
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Effect of case selection on the performance of computer-aided detection schemes. Med Phys. 1994 Feb; 21(2):265-9.
Score: 0.011
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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: 0.011
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Application of the EM algorithm to radiographic images. Med Phys. 1992 Sep-Oct; 19(5):1175-82.
Score: 0.010
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Computerized detection of masses in digital mammograms: analysis of bilateral subtraction images. Med Phys. 1991 Sep-Oct; 18(5):955-63.
Score: 0.010
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Normal parenchymal enhancement patterns in women undergoing MR screening of the breast. Eur Radiol. 2011 Jul; 21(7):1374-82.
Score: 0.009
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A novel hybrid linear/nonlinear classifier for two-class classification: theory, algorithm, and applications. IEEE Trans Med Imaging. 2010 Feb; 29(2):428-41.
Score: 0.008
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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: 0.003
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Computer-aided detection of clustered microcalcifications on digital mammograms. Med Biol Eng Comput. 1995 Mar; 33(2):174-8.
Score: 0.003
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Digital radiography. A useful clinical tool for computer-aided diagnosis by quantitative analysis of radiographic images. Acta Radiol. 1993 Sep; 34(5):426-39.
Score: 0.003