메뉴 건너뛰기




Volumn 25, Issue 1, 2015, Pages 33-40

Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor

Author keywords

artificial neural network; classification; medical images; statistical analysis; wavelets

Indexed keywords

BACKPROPAGATION; BRAIN MAPPING; CLASSIFICATION (OF INFORMATION); COMPUTERIZED TOMOGRAPHY; DISCRETE WAVELET TRANSFORMS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; MAGNETIC RESONANCE IMAGING; MAMMOGRAPHY; MEDICAL IMAGING; NEURAL NETWORKS; RADIAL BASIS FUNCTION NETWORKS; STATISTICAL METHODS; ULTRASONICS; X RAY SCREENS;

EID: 84922461060     PISSN: 08999457     EISSN: 10981098     Source Type: Journal    
DOI: 10.1002/ima.22118     Document Type: Review
Times cited : (45)

References (30)
  • 2
    • 0026870427 scopus 로고
    • Optimization neural networks for the segmentation of magnetic resonance images
    • S.C. Amartur, D. Piraino, and, Y. Takefuji, Optimization neural networks for the segmentation of magnetic resonance images, IEEE Trans Med Imaging 11 (1992), 215-220.
    • (1992) IEEE Trans Med Imaging , vol.11 , pp. 215-220
    • Amartur, S.C.1    Piraino, D.2    Takefuji, Y.3
  • 3
    • 0036464835 scopus 로고    scopus 로고
    • Fuzzy Hopfield neural network with fixed weight for medical image segmentation
    • C.L. Chang, and, Y.T. Ching, Fuzzy Hopfield neural network with fixed weight for medical image segmentation, Opt Eng 41 (2002), 351-358.
    • (2002) Opt Eng , vol.41 , pp. 351-358
    • Chang, C.L.1    Ching, Y.T.2
  • 4
    • 0033734154 scopus 로고    scopus 로고
    • Two-layer competitive based Hopfield neural network for medical image edge detection
    • C.Y. Chang, and, P.C. Chung, Two-layer competitive based Hopfield neural network for medical image edge detection, Opt Eng 39 (2000), 695-703.
    • (2000) Opt Eng , vol.39 , pp. 695-703
    • Chang, C.Y.1    Chung, P.C.2
  • 5
    • 77952577535 scopus 로고    scopus 로고
    • Thyroid segmentation and estimation in ultrasound images
    • Y.C. Chuan, F.L. Yue, H.T. Chin, and, R.S. Shyang, Thyroid segmentation and estimation in ultrasound images, IEEE Trans Biomed Eng, 57 (2010), 1348-1357.
    • (2010) IEEE Trans Biomed Eng , vol.57 , pp. 1348-1357
    • Chuan, Y.C.1    Yue, F.L.2    Chin, H.T.3    Shyang, R.S.4
  • 6
    • 84990623513 scopus 로고
    • Biorthogonal basis of compactly supported vectors
    • A. Cohen, Biorthogonal basis of compactly supported vectors, Commun. Pure Appl. Math. 21 (1992), 485-560.
    • (1992) Commun. Pure Appl. Math. , vol.21 , pp. 485-560
    • Cohen, A.1
  • 7
    • 0025482241 scopus 로고
    • The wavelet transform, time-frequency localization and signal analysis
    • I. Daubechies, The wavelet transform, time-frequency localization and signal analysis, IEEE Trans Inform Theory 36 (1990), 961-1005.
    • (1990) IEEE Trans Inform Theory , vol.36 , pp. 961-1005
    • Daubechies, I.1
  • 9
    • 0036885188 scopus 로고    scopus 로고
    • Segmentation of ultrasound images by using a hybrid neural network
    • Z. Dokur, and, T. Olmez, Segmentation of ultrasound images by using a hybrid neural network, Pattern Recogn Lett 33 (2002), 1825-1836.
    • (2002) Pattern Recogn Lett , vol.33 , pp. 1825-1836
    • Dokur, Z.1    Olmez, T.2
  • 10
    • 0037983742 scopus 로고    scopus 로고
    • Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance
    • X. Fu, and, L. Wang, Data dimensionality reduction with application to simplifying RBF network structure and improving classification performance, Syst Man Cybernet Part B: Cybernet IEEE Trans 33 (2003), 399-409.
    • (2003) Syst Man Cybernet Part B: Cybernet IEEE Trans , vol.33 , pp. 399-409
    • Fu, X.1    Wang, L.2
  • 11
    • 33746746440 scopus 로고    scopus 로고
    • Computer aided detection of clusters of microcalcifications on full field digital mammograms
    • J Ge, B Sahiner, LM Hadjiiski, HP Chan, J Wei, MA Helvie, and, C Zhou, Computer aided detection of clusters of microcalcifications on full field digital mammograms, Med Phys 33 (2006), 2975-2988.
    • (2006) Med Phys , vol.33 , pp. 2975-2988
    • Ge, J.1    Sahiner, B.2    Hadjiiski, L.M.3    Chan, H.P.4    Wei, J.5    Helvie, M.A.6    Zhou, C.7
  • 12
    • 0038802299 scopus 로고    scopus 로고
    • Harvard Whole brain atlas
    • D. Summers, Harvard Whole brain atlas: www.med.harvard.edu/AANLIB/home.html, J Neurol Neurosurg Psychiatry 74 (2003), 288.
    • (2003) J Neurol Neurosurg Psychiatry , vol.74 , pp. 288
    • Summers, D.1
  • 13
    • 33847782793 scopus 로고    scopus 로고
    • Statistical comparison of a probabilistic neural network approach in hepatic cancer diagnosis, Computer as a Tool
    • F. Gorunescu, M. Gorunescu, E. El-Darzi, M. Ene, and, S. Gorunescu, Statistical comparison of a probabilistic neural network approach in hepatic cancer diagnosis, Computer as a Tool, IEEE Eurocon 1 (2005), 237-240.
    • (2005) IEEE Eurocon , vol.1 , pp. 237-240
    • Gorunescu, F.1    Gorunescu, M.2    El-Darzi, E.3    Ene, M.4    Gorunescu, S.5
  • 14
    • 84858722591 scopus 로고    scopus 로고
    • Application of neuro-fuzzy model for MR brain tumor image classification
    • D.J. Hemanth, C. Kezi Selva Vijila, and, J. Anitha, Application of neuro-fuzzy model for MR brain tumor image classification, Biomed Soft Comput Hum Sci 16 (2010), 95-102.
    • (2010) Biomed Soft Comput Hum Sci , vol.16 , pp. 95-102
    • Hemanth, D.J.1    Kezi Selva Vijila, C.2    Anitha, J.3
  • 15
    • 77957910572 scopus 로고    scopus 로고
    • Medical image analysis with artificial neural networks
    • J. Jiang, P. Trundle, and, J. Ren, Medical image analysis with artificial neural networks, Comput Med Imag Graph 34 (2010), 617-631.
    • (2010) Comput Med Imag Graph , vol.34 , pp. 617-631
    • Jiang, J.1    Trundle, P.2    Ren, J.3
  • 16
    • 72449184466 scopus 로고    scopus 로고
    • Comparing the performance of different neural networks for binary classification problems
    • SNLP'09 Eighth International Symposium, 2009
    • P. Jeatrakul, and, K. Wong, Comparing the performance of different neural networks for binary classification problems. Natural Language Processing, 2009, SNLP'09 Eighth International Symposium, 2009.
    • (2009) Natural Language Processing
    • Jeatrakul, P.1    Wong, K.2
  • 17
    • 0021136434 scopus 로고
    • The structure of images
    • J. Koenderink, The structure of images, Biol Cybern 50 (1984), 363-370.
    • (1984) Biol Cybern , vol.50 , pp. 363-370
    • Koenderink, J.1
  • 18
    • 36749047332 scopus 로고    scopus 로고
    • Supervised machine learning: A review of classification techniques
    • S. Kotsiantis, I. Zaharakis, and, P. Pintelas, Supervised machine learning: A review of classification techniques, Inform J 31 (2007), 249-268.
    • (2007) Inform J , vol.31 , pp. 249-268
    • Kotsiantis, S.1    Zaharakis, I.2    Pintelas, P.3
  • 19
    • 70349647885 scopus 로고    scopus 로고
    • A comparison of RBF neural network training algorithms for inertial sensor based terrain classification
    • T. Kurban, and, E. Beşdok, A comparison of RBF neural network training algorithms for inertial sensor based terrain classification, Sensors 9 (2009), 6312-6329.
    • (2009) Sensors , vol.9 , pp. 6312-6329
    • Kurban, T.1    Beşdok, E.2
  • 20
    • 33746901239 scopus 로고    scopus 로고
    • The use of artificial neural networks in decision support in cancer: A systematic review
    • PJ Lisboa, and, AFG. Taktak, The use of artificial neural networks in decision support in cancer: A systematic review, Neural Networks 19 (2006), 408-415.
    • (2006) Neural Networks , vol.19 , pp. 408-415
    • Lisboa, P.J.1    Taktak, A.F.G.2
  • 21
    • 0029569057 scopus 로고
    • Artificial convolution neural network for medical image pattern recognition
    • SCB Lo, HP Chan, JS Lin, H Li, MT Freedman, and, SK Mun, Artificial convolution neural network for medical image pattern recognition, Neural Networks 8 (1995), 1201-1214.
    • (1995) Neural Networks , vol.8 , pp. 1201-1214
    • Lo, S.C.B.1    Chan, H.P.2    Lin, J.S.3    Li, H.4    Freedman, M.T.5    Mun, S.K.6
  • 22
    • 0344009664 scopus 로고    scopus 로고
    • Segmentation of magnetic resonance images using a combination of neural networks and active contour models
    • I Middleton, and, RI Damper, Segmentation of magnetic resonance images using a combination of neural networks and active contour models, Med Eng Phys 26 (2004), 71-86.
    • (2004) Med Eng Phys , vol.26 , pp. 71-86
    • Middleton, I.1    Damper, R.I.2
  • 23
    • 85008907036 scopus 로고    scopus 로고
    • Comparing performance of different neural networks for early detection of cancer from benign hyperplasia of prostate
    • G. Mustafa, F. Rebecca, and, S Arran, Comparing performance of different neural networks for early detection of cancer from benign hyperplasia of prostate, Appl Med Inform 33 (2013), 45-54.
    • (2013) Appl Med Inform , vol.33 , pp. 45-54
    • Mustafa, G.1    Rebecca, F.2    Arran, S.3
  • 24
    • 0031814618 scopus 로고    scopus 로고
    • Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms
    • RH Nagel, RM Nishikawa, J Papaioannou, and, K Doi, Analysis of methods for reducing false positives in the automated detection of clustered microcalcifications in mammograms, Med Phys 25 (1998), 1502-1506.
    • (1998) Med Phys , vol.25 , pp. 1502-1506
    • Nagel, R.H.1    Nishikawa, R.M.2    Papaioannou, J.3    Doi, K.4
  • 25
    • 0036106379 scopus 로고    scopus 로고
    • An automatic microcalcification detection system based on a hybrid neural network classifier
    • A Papadopoulossa, DI Fotiadis, and, A Likas, An automatic microcalcification detection system based on a hybrid neural network classifier, Artif Intell Med 25 (2002), 149-167.
    • (2002) Artif Intell Med , vol.25 , pp. 149-167
    • Papadopoulossa, A.1    Fotiadis, D.I.2    Likas, A.3
  • 26
    • 33745255698 scopus 로고    scopus 로고
    • Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network
    • C Sandeep, LM Patnaik, and, NR Jangnnathan, Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network, Biomed Signal Process Control 1 (2006), 86-92.
    • (2006) Biomed Signal Process Control , vol.1 , pp. 86-92
    • Sandeep, C.1    Patnaik, L.M.2    Jangnnathan, N.R.3
  • 27
    • 0030087643 scopus 로고    scopus 로고
    • Extracting rules from pruned neural networks for breast cancer diagnosis
    • R. Setiono, Extracting rules from pruned neural networks for breast cancer diagnosis, Artif Intell Med 8 (1996), 37-51.
    • (1996) Artif Intell Med , vol.8 , pp. 37-51
    • Setiono, R.1
  • 29
    • 0025399335 scopus 로고
    • Probabilistic neural networks and the polynomial adaline as complementary techniques for classification
    • DF Specht, Probabilistic neural networks and the polynomial adaline as complementary techniques for classification, IEEE Trans Neural Networks 1 (1990), 111-121.
    • (1990) IEEE Trans Neural Networks , vol.1 , pp. 111-121
    • Specht, D.F.1
  • 30
    • 0030127507 scopus 로고    scopus 로고
    • A review of wavelets in biomedical applications
    • M Unser, and, A Aldroubi, A review of wavelets in biomedical applications, Proc IEEE 84 (1996), 626-638.
    • (1996) Proc IEEE , vol.84 , pp. 626-638
    • Unser, M.1    Aldroubi, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.