Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers.
暂无分享,去创建一个
M. Giger | L. Lan | G. Newstead | Hui Li | N. Bhooshan | S. Jansen
[1] H. Bloom,et al. Histological Grading and Prognosis in Breast Cancer , 1957, British Journal of Cancer.
[2] R. Blamey,et al. A prognostic index in primary breast cancer. , 1982, British Journal of Cancer.
[3] I. O. Ellis,et al. Confirmation of a prognostic index in primary breast cancer. , 1987, British Journal of Cancer.
[4] C E Metz,et al. Some practical issues of experimental design and data analysis in radiological ROC studies. , 1989, Investigative radiology.
[5] L. Tabár,et al. Breast screening, prognostic factors and survival--results from the Swedish two county study. , 1991, British Journal of Cancer.
[6] J O Barentsz,et al. Breast tumors: comparative accuracy of MR imaging relative to mammography and US for demonstrating extent. , 1995, Radiology.
[7] E. Feuer,et al. The impact of stage and histology on the long‐term clinical course of 163,808 patients with breast carcinoma , 1996, Cancer.
[8] U. Fischer,et al. Das duktale In-situ-Karzinom in der dynamischen MR-Mammographie bei 1,5 T , 1996 .
[9] D. Wartenberg,et al. The importance of histologic type on breast cancer survival. , 1997, Journal of clinical epidemiology.
[10] Martin P. DeSimio,et al. Computer-aided breast cancer detection and diagnosis of masses using difference of Gaussians and derivative-based feature saliency , 1997, IEEE Transactions on Medical Imaging.
[11] C A Roe,et al. Statistical Comparison of Two ROC-curve Estimates Obtained from Partially-paired Datasets , 1998, Medical decision making : an international journal of the Society for Medical Decision Making.
[12] M L Giger,et al. Computerized analysis of breast lesions in three dimensions using dynamic magnetic-resonance imaging. , 1998, Medical physics.
[13] R. Mansel,et al. The fourth EORTC DCIS Consensus meeting (Château Marquette, Heemskerk, The Netherlands, 23-24 January 1998)--conference report. , 1998, European journal of cancer.
[14] C. Kuhl,et al. Dynamic breast MR imaging: are signal intensity time course data useful for differential diagnosis of enhancing lesions? , 1999, Radiology.
[15] M. Giger,et al. Improving breast cancer diagnosis with computer-aided diagnosis. , 1999, Academic radiology.
[16] C K Kuhl,et al. Dynamic image interpretation of MRI of the breast , 2000, Journal of magnetic resonance imaging : JMRI.
[17] E A Sickles,et al. Dynamic high-spatial-resolution MR imaging of suspicious breast lesions: diagnostic criteria and interobserver variability. , 2000, AJR. American journal of roentgenology.
[18] S G Orel. MR imaging of the breast. , 2000, Radiologic clinics of North America.
[19] L. Tabár,et al. Potential contribution of computer-aided detection to the sensitivity of screening mammography. , 2000, Radiology.
[20] D. Chen,et al. Breast cancer diagnosis using self-organizing map for sonography. , 2000, Ultrasound in medicine & biology.
[21] Maryellen L. Giger,et al. Ideal observer approximation using Bayesian classification neural networks , 2001, IEEE Transactions on Medical Imaging.
[22] U. Fischer,et al. International investigation of breast MRI: results of a multicentre study (11 sites) concerning diagnostic parameters for contrast-enhanced MRI based on 519 histopathologically correlated lesions , 2001, European Radiology.
[23] Maryellen L. Giger,et al. Computerized analysis of multiple-mammographic views: potential usefulness of special view mammograms in computer-aided diagnosis , 2001, IEEE Transactions on Medical Imaging.
[24] B Fisher,et al. Fifteen‐year prognostic discriminants for invasive breast carcinoma , 2001, Cancer.
[25] L. Liberman,et al. Observer variability and applicability of BI-RADS terminology for breast MR imaging: invasive carcinomas as focal masses. , 2001, AJR. American journal of roentgenology.
[26] M. Giger,et al. Breast cancer: effectiveness of computer-aided diagnosis observer study with independent database of mammograms. , 2002, Radiology.
[27] Berkman Sahiner,et al. Breast cancer detection: evaluation of a mass-detection algorithm for computer-aided diagnosis -- experience in 263 patients. , 2002, Radiology.
[28] Elizabeth A Morris,et al. Breast cancer imaging with MRI. , 2002, Radiologic clinics of North America.
[29] L. Turnbull,et al. Textural analysis of contrast‐enhanced MR images of the breast , 2003, Magnetic resonance in medicine.
[30] W. Kaiser,et al. High grade and non-high grade ductal carcinoma in situ on dynamic MR mammography: characteristic findings for signal increase and morphological pattern of enhancement. , 2003, The British journal of radiology.
[31] Mitchell D Schnall,et al. Breast MR imaging. , 2003, Radiologic clinics of North America.
[32] Maryellen L Giger,et al. Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography. , 2004, Academic radiology.
[33] Jane Warwick,et al. Time‐dependent effects on survival in breast carcinoma , 2004, Cancer.
[34] M. Giger,et al. Computerized detection and classification of cancer on breast ultrasound. , 2004, Academic radiology.
[35] M. Giger,et al. Computerized interpretation of breast MRI: investigation of enhancement-variance dynamics. , 2004, Medical physics.
[36] Elizabeth A Morris,et al. Determination of the Presence and Extent of Pure Ductal Carcinoma in Situ by Mammography and Magnetic Resonance Imaging , 2005, The breast journal.
[37] Murray H. Loew,et al. Estimating the uncertainty in the estimated mean area under the ROC curve of a classifier , 2005, Pattern Recognit. Lett..
[38] Fiona J Gilbert,et al. Reading protocol for dynamic contrast-enhanced MR images of the breast: sensitivity and specificity analysis. , 2005, Radiology.
[39] P. Parizel,et al. Comparison of MRI features of different grades of DCIS and invasive carcinoma of the breast. , 2006, JBR-BTR : organe de la Societe royale belge de radiologie (SRBR) = orgaan van de Koninklijke Belgische Vereniging voor Radiologie.
[40] N. Obuchowski,et al. Assessment of suspected breast cancer by MRI: a prospective clinical trial using a combined kinetic and morphologic analysis. , 2005, AJR. American journal of roentgenology.
[41] Li Lan,et al. Classification of breast lesions with multimodality computer-aided diagnosis: observer study results on an independent clinical data set. , 2006, Radiology.
[42] Maryellen L. Giger,et al. A Fuzzy C-Means (FCM)-Based Approach for Computerized Segmentation of Breast Lesions in Dynamic Contrast-Enhanced MR Images1 , 2006 .
[43] L. Liberman,et al. Determination of the Presence and Extent of Pure Ductal Carcinoma in Situ by Mammography and Magnetic Resonance Imaging , 2005, The breast journal.
[44] M. Giger,et al. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI. , 2006, Medical physics.
[45] Murray H. Loew,et al. Assessing Classifiers from Two Independent Data Sets Using ROC Analysis: A Nonparametric Approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] R. Arriagada,et al. Twenty‐five years of follow‐up in patients with operable breast carcinoma , 2006, Cancer.
[47] Lina Arbash Meinel,et al. Breast MRI lesion classification: Improved performance of human readers with a backpropagation neural network computer‐aided diagnosis (CAD) system , 2007, Journal of magnetic resonance imaging : JMRI.
[48] M. Giger,et al. Volumetric texture analysis of breast lesions on contrast‐enhanced magnetic resonance images , 2007, Magnetic resonance in medicine.
[49] J. Coebergh,et al. An overview of prognostic factors for long-term survivors of breast cancer , 2007, Breast Cancer Research and Treatment.
[50] R. Schmidt,et al. Pure ductal carcinoma in situ: kinetic and morphologic MR characteristics compared with mammographic appearance and nuclear grade. , 2007, Radiology.
[51] L. Liberman,et al. Imaging breast cancer. , 2007, Radiologic clinics of North America.