Texture analysis of breast tumors on sonograms

Stavors, 1995, Solid breast nodules: use of sonography to distinguish between benign and malignant lesions, Radiology, 196, 123, 10.1148/radiology.196.1.7784555 Skaane, 1998, Analysis of sonographic features in the differentiation of fibroadenoma and invasive ductal carcinoma, AJR Am J Roentgenol, 170, 109, 10.2214/ajr.170.1.9423610 Gisvold, 1984, Prebiopsy localization of nonpalpable breast lesions, AJR Am J Roentgenol, 143, 477, 10.2214/ajr.143.3.477 Rosenberg, 1987, Clinical occult breast lesions: localization and significance, Radiology, 162, 167, 10.1148/radiology.162.1.3024209 Bassett, 1992, The prevalence of carcinoma in palpable vs impalpable, mammographically detected lesions (comment), AJR Am J Roentgenol, 158, 688 Jackson, 1995, Management of solid breast nodules: what is the role of sonography?, Radiology, 196, 14, 10.1148/radiology.196.1.7784557 Gurney, 1994, Neural networks at the crossroads: caution ahead, Radiology, 193, 27, 10.1148/radiology.193.1.8090906 Boone, 1993, Neural networks at the crossroads, Radiology, 189, 357, 10.1148/radiology.189.2.8210359 Astion, 1992, The application of backpropagation neural networks to problems in pathology and laboratory medicine, Arch Pathol Lab Med, 116, 995 Wu, 1993, Artificial neural networks in mammography: application to decision making in the diagnosis of breast cancer, Radiology, 187, 81, 10.1148/radiology.187.1.8451441 Piraino, 1991, Application of an artificial neural network in radiographic diagnosis, J Digit Imaging, 4, 226, 10.1007/BF03173904 Buller, 1996, Determining and classifying the region of interest in ultrasonic images of the breast using neural networks, Artif Intell Med, 8, 53, 10.1016/0933-3657(95)00020-8 Gross, 1995, Pediatric skeletal age: determination with neural networks, Radiology, 195, 689, 10.1148/radiology.195.3.7753995 Rumelhart, 1986, Learning representation by back-propagation errors, Nature, 323, 533, 10.1038/323533a0 Hirose, 1991, Back-propagation algorithm which varies the number of hidden units, Neural Networks, 4, 61, 10.1016/0893-6080(91)90032-Z Sahiner, 1996, Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images, IEEE Trans Med Imaging, 15, 598, 10.1109/42.538937 Garra, 1993, Improving the distinction between benign and malignant breast lesions: the value of sonographic texture analysis, J Ultrasound Med, 13, 267 Gonzalez, 1992, Image compression, 312 Fu, 1994 Weiss, 1989, An empirical comparison of pattern recognition neural nets and machine learning classification methods, 234 Sickles, 1991, Periodic mammographic follow-up of probably benign lesions: results of 3,184 consecutive cases, Radiology, 179, 63, 10.1148/radiology.179.2.2014293 Tersegno, 1993, Mammography: positive predictive value and true positive biopsy rate (letter), AJR Am J Roentgenol, 160, 660, 10.2214/ajr.160.3.8430576 Bassett, 1991, The prevalence of carcinoma in palpable versus impalpable-palpable, mammographically detected lesions, AJR Am J Roentgenol, 157, 21, 10.2214/ajr.157.1.1646562 Hall, 1988, Nonpalpable breast lesions: recommendations for biopsy based on suspicion of carcinoma at mammography, Radiology, 167, 353, 10.1148/radiology.167.2.3282256 Ciatto, 1987, Nonpalpable lesions detected with mammography: review of 512 consecutive cases, Radiology, 165, 99, 10.1148/radiology.165.1.3628796 Raza, 1997, Solid breast lesions: evaluation with power doppler US, Radiology, 203, 164, 10.1148/radiology.203.1.9122386 Naguib, 1997, Prediction of nodal metastasis and prognosis in breast cancer: a neural model, Anticancer Res, 4, 2735 Baker, 1995, Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon, Radiology, 196, 817, 10.1148/radiology.196.3.7644649 Chen, 1999, Computer-aided diagnosis applied to US of solid breast nodules by using neural networks, Radiology, 213, 407, 10.1148/radiology.213.2.r99nv13407