Medical image segmentation with transform and moment based features and incremental supervised neural network
Tóm tắt
Từ khóa
Tài liệu tham khảo
Z. Dokur, T. Ölmez, Classification of magnetic resonance images using a novel neural network, in: IEEE-EMBS Asia Pacific Conf. on Bio. Eng., China, 2000
Shitong, 2007, Advanced fuzzy cellular neural network: Application to CT liver images, Artif. Intell. Med., 39, 65, 10.1016/j.artmed.2006.08.001
Middleton, 2004, Segmentation of magnetic resonance images using a combination of neural networks and active contour models, Med. Eng. Phys., 26, 71, 10.1016/S1350-4533(03)00137-1
Iscan, 2006, Ultrasound image segmentation by using wavelet transform and self-organizing neural network, Neural Inform. Process.—Lett. Rev., 10, 183
Qian, 1999, Image feature extraction for mass detection in digital mammography-influence of wavelet analysis, Med. Phys., 26, 402, 10.1118/1.598531
Haering, 1999, Features and classification methods to locate deciduous trees in images, Comput. Vis. Image Und., 75, 133, 10.1006/cviu.1999.0769
Kim, 1998, Ultrasound image texture analysis for characterizing intramuscular fat-content of live beef-cattle, Ultrasound Imag., 20, 191, 10.1177/016173469802000304
Ogawa, 1998, Computer-aided diagnostic system for diffuse liver-diseases with ultrasonography by neural networks, IEEE Trans. Nucl. Sci., 45, 3069, 10.1109/23.737666
Feleppa, 1996, Typing of prostate tissue by ultrasonic spectrum analysis, IEEE Trans. Ultr. Ferr. Freq. Cont., 3, 609, 10.1109/58.503779
Dasarathy, 1991, Image characterization based on joint gray level run length distributions, Pattern Recogn. Lett., 12, 497, 10.1016/0167-8655(91)80014-2
Llobet, 2007, Computer-aided detection of prostate cancer, Int. J. Med. Inform., 76, 547, 10.1016/j.ijmedinf.2006.03.001
Hsiang, 2006, Segmentation of kidney from ultrasound B-mode images with texture-based classification, Comp. Methods Prog. Biol., 84, 114
Zhang, 1998, Optimally weighted wavelet transform based on supervised training for detection of microcalcifications in digital mammograms, Med. Phys., 25, 949, 10.1118/1.598273
Lefebvre, 1998, Automatic detection of the boundary of the calcaneus from ultrasound parametric images using an active contour model-clinical assessment, IEEE Trans. Med. Imag., 17, 45, 10.1109/42.668693
Parkkinen, 1990, Detecting texture periodicity from co-occurrence matrix, Pattern Recogn. Lett., 11, 43, 10.1016/0167-8655(90)90054-6
Retico, 2006, An automatic system to discriminate malignant from benign massive lesions on mammograms, Nuclear Instrum. Methods Phys. Res. A, 569, 596, 10.1016/j.nima.2006.08.093
Petersen, 2002, Image processing with neural networks—A review, Pattern Recogn., 35, 2279, 10.1016/S0031-3203(01)00178-9
Yang, 2007, Magnetic resonance imaging segmentation techniques using batch-type learning vector quantization algorithms, Magn. Reson. Imag., 25, 265, 10.1016/j.mri.2006.09.043
Dokur, 2006, Segmentation of medical images by using wavelet transform and incremental self-organizing pap, Lect. Notes Artif. Intell., LNAI 4293, 800
Sheshadri, 2007, Experiment investigation on breast tissue classification based on statistical feature extraction of mammograms, Comp. Med. Imag. Grap., 31, 46, 10.1016/j.compmedimag.2006.09.015
Polikar
E. Alpaydın, Neural models of incremental supervised and unsupervised learning, Ph.D. thesis, Ecole Polytechnique Federale de Lausanne, Switzerland, 1990
Dokur, 2003, Classification of respiratory sounds by using an artificial neural network, Int. J. Pattern Recogn. Artif. Intell., 17, 567, 10.1142/S0218001403002526
Ölmez, 2003, Classification of heart sounds using an artificial neural network, Pattern Recogn. Lett., 24, 617, 10.1016/S0167-8655(02)00281-7
Cohen, 1986