Computer-aided diagnosis of breast lesions in medical images
暂无分享,去创建一个
[1] E. Gose,et al. Breast lesion classification by computer and xeroradiograph , 1972, Cancer.
[2] H. Sittek,et al. Computer-aided diagnosis in mammography , 1997, Der Radiologe.
[3] M D Schnall,et al. Breast MR imaging: interpretation model. , 1997, Radiology.
[4] M. Giger,et al. Computerized analysis of lesions in US images of the breast. , 1999, Academic radiology.
[5] R Holland,et al. So‐called interval cancers of the breast: Pathologic and radiologic analysis of sixty‐four cases , 1982, Cancer.
[6] M D Schnall,et al. Discrimination of MR images of breast masses with fractal-interpolation function models. , 1999, Academic radiology.
[7] M. Giger,et al. Malignant and benign clustered microcalcifications: automated feature analysis and classification. , 1996, Radiology.
[8] Matthew A. Kupinski,et al. Investigation of regularized neural networks for the computerized detection of mass lesions in digital mammograms , 1997, Proceedings of the 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 'Magnificent Milestones and Emerging Opportunities in Medical Engineering' (Cat. No.97CH36136).
[9] M D Fox,et al. Application of expert systems to mammographic image analysis. , 1989, American journal of physiologic imaging.
[10] Jun-ichiro Toriwaki,et al. Pattern recognition of chest X-ray images , 1973, Comput. Graph. Image Process..
[11] C. M. Logan,et al. Automated analysis for microcalcifications in high resolution digital mammograms , 1994 .
[12] M L Giger,et al. Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules. , 1992, Investigative radiology.
[13] Kunio Doi,et al. Investigation of methods for the computerized detection and analysis of mammographic masses , 1990, Medical Imaging: Image Processing.
[14] Noboru Niki,et al. Computer Assisted Lung Cancer Diagnosis Based on Helical Images , 1995, ICSC.
[15] Maryellen L. Giger,et al. Computerized scheme for the detection of pulmonary nodules. A nonlinear filtering technique. , 1992 .
[16] M Moskowitz,et al. Occult breast cancer: prevalence and radiographic detectability. , 1987, Radiology.
[17] L. Tabár,et al. Teaching atlas of mammography. , 1983, Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin. Erganzungsband.
[18] William R. Brody,et al. Automated recognition of microcalcification clusters in mammograms , 1993, Electronic Imaging.
[19] M. Giger,et al. Analysis of spiculation in the computerized classification of mammographic masses. , 1995, Medical physics.
[20] Robert M. Nishikawa,et al. Computer-Aided Diagnosis of Digital Mammography and Ultrasound Images of Breast Mass Lesions , 1998, Digital Mammography / IWDM.
[21] I Andersson. What can we learn from interval carcinomas? , 1984, Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer.
[22] M. Giger,et al. Computerized Detection of Pulmonary Nodules in Computed Tomography Images , 1994, Investigative radiology.
[23] Y. Chiou,et al. Hybrid lung nodule detection (HLND) system. , 1994, Cancer letters.
[24] M. Giger,et al. Computerized detection of pulmonary nodules in digital chest images: use of morphological filters in reducing false-positive detections. , 1990, Medical physics.
[25] J. Sklansky,et al. Tumor detection in radiographs. , 1973, Computers and biomedical research, an international journal.
[26] E. Thurfjell,et al. Benefit of independent double reading in a population-based mammography screening program. , 1994, Radiology.
[27] N Segnan,et al. Inter-observer and intra-observer variability of mammogram interpretation: a field study. , 1992, European journal of cancer.
[28] M. Giger,et al. Computer vision and artificial intelligence in mammography. , 1994, AJR. American journal of roentgenology.
[29] K Doi,et al. Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms. , 1998, Medical physics.
[30] I S Simor,et al. Sensitivity and specificity of first screen mammography in the Canadian National Breast Screening Study: a preliminary report from five centers. , 1986, Radiology.
[31] M. Giger,et al. Development of an improved CAD scheme for automated detection of lung nodules in digital chest images. , 1997, Medical physics.
[32] J A Swets,et al. Enhancing and Evaluating Diagnostic Accuracy , 1991, Medical decision making : an international journal of the Society for Medical Decision Making.
[33] Kunio Doi,et al. Three-dimensional approach to lung nodule detection in helical CT , 1999, Medical Imaging.
[34] Wei Zhang,et al. Clinical Results with R2 Imagechecker System , 1998, Digital Mammography / IWDM.
[35] N. Petrick,et al. Design of a high-sensitivity classifier based on a genetic algorithm: application to computer-aided diagnosis , 1998, Physics in medicine and biology.
[36] B. Garra,et al. Improving the Distinction between Benign and Malignant Breast Lesions: The Value of Sonographic Texture Analysis , 1993 .
[37] M L Giger,et al. Computerized analysis of breast lesions in three dimensions using dynamic magnetic-resonance imaging. , 1998, Medical physics.
[38] Hirotsugu Takabatake,et al. Development of a computer-aided detection system for lung cancer diagnosis , 1992, Medical Imaging.
[39] R. Bird. Professional quality assurance for mammography screening programs. , 1990, Radiology.
[40] L. Bassett,et al. Breast Cancer Detection: Mammography and Other Methods in Breast Imaging , 1987 .
[41] L. Liberman,et al. Breast imaging reporting and data system (BI-RADS). , 2002, Radiologic clinics of North America.
[42] J. Swets,et al. Enhanced interpretation of diagnostic images. , 1988, Investigative radiology.
[43] Heng-Da Cheng,et al. A novel approach to microcalcification detection using fuzzy logic technique , 1998, IEEE Transactions on Medical Imaging.
[44] M. Giger,et al. Improving breast cancer diagnosis with computer-aided diagnosis. , 1999, Academic radiology.
[45] Noboru Niki,et al. Computer aided diagnosis system for lung cancer based on helical CT images , 1997, Medical Imaging.
[46] 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.
[47] J. Elmore,et al. Variability in radiologists' interpretations of mammograms. , 1994, The New England journal of medicine.
[48] C. Floyd,et al. Fractal texture analysis in computer-aided diagnosis of solitary pulmonary nodules. , 1997, Academic radiology.
[49] B L Kalman,et al. Prescreening entire mammograms for masses with artificial neural networks: preliminary results. , 1997, Academic radiology.
[50] W A Murphy,et al. Professional quality assurance for mammography screening programs. , 1990, Radiology.
[51] L. Clarke,et al. Fragmentary window filtering for multiscale lung nodule detection: preliminary study. , 1998, Academic radiology.
[52] Shinji Yamamoto,et al. Image processing for computer-aided diagnosis of lung cancer screening system by CT (LSCT) , 1998, Medical Imaging.
[53] J. Spratt,et al. Tumor growth, doubling times, and the inability of the radiologist to diagnose certain cancers. , 1983, Radiologic clinics of North America.
[54] M. Moskowitz,et al. Breast cancer missed by mammography. , 1979, AJR. American journal of roentgenology.
[55] Matthew T. Freedman,et al. Computer-assisted diagnosis of lung nodule detection using artificial convoultion neural network , 1993 .
[56] A. Stavros,et al. Solid breast nodules: use of sonography to distinguish between benign and malignant lesions. , 1995, Radiology.
[57] M L Giger,et al. Pulmonary nodules: computer-aided detection in digital chest images. , 1990, Radiographics : a review publication of the Radiological Society of North America, Inc.
[58] Yali Amit,et al. Wavelet-based deformable contour and its application to detection of pulmonary nodules on chest radiographs , 1997, Optics & Photonics.
[59] M. Giger,et al. Image feature analysis and computer-aided diagnosis in digital radiography. 3. Automated detection of nodules in peripheral lung fields. , 1988, Medical physics.
[60] Hiroyuki Yoshida,et al. Computer-aided diagnosis scheme for detecting pulmonary nodules using wavelet transform , 1995, Medical Imaging.
[61] F. Winsberg,et al. Detection of Radiographic Abnormalities in Mammograms by Means of Optical Scanning and Computer Analysis , 1967 .
[62] L. Tabár,et al. Update of the Swedish two-county program of mammographic screening for breast cancer. , 1992, Radiologic clinics of North America.
[63] Dana H. Ballard,et al. A Ladder-Structured Decision Tree for Recognizing Tumors in Chest Radiographs , 1976, IEEE Transactions on Computers.
[64] Y. Wu,et al. Artificial neural networks in mammography: application to decision making in the diagnosis of breast cancer. , 1993, Radiology.
[65] K Doi,et al. A genetic algorithm-based method for optimizing the performance of a computer-aided diagnosis scheme for detection of clustered microcalcifications in mammograms. , 1998, Medical physics.
[66] Matthew T. Freedman,et al. Application of artificial neural networks for reducing false positives in lung nodule detection on digital chest radiographs , 1995, Medical Imaging.
[67] M. Giger,et al. Automated computerized classification of malignant and benign masses on digitized mammograms. , 1998, Academic radiology.
[68] Rangaraj M. Rangayyan,et al. Automatic detection and classification system for calcifications in mammograms , 1993, Electronic Imaging.
[69] S. Armato,et al. Computerized detection of pulmonary nodules on CT scans. , 1999, Radiographics : a review publication of the Radiological Society of North America, Inc.
[70] M. Giger,et al. Computerized characterization of mammographic masses: analysis of spiculation. , 1994, Cancer letters.
[71] B S Worthington,et al. Computer aids to mammographic diagnosis. , 1987, The British journal of radiology.
[72] R J Brenner,et al. Medicolegal aspects of breast imaging: variable standards of care relating to different types of practice. , 1991, AJR. American journal of roentgenology.