150

REFERENCES

1. Abdel-

IEEE International Conference on Electro/Information Technology Indianapolis, pp.1 - 6.

2. Ahmad, A, Amira, A, Rabah, H, -based architectures of finite radon transform for medical image de-IEEE Asia Pacific Conference on Circuits and Systems, Kuala Lumpur, pp. 20-23.

3.

Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no.12, pp. 2037 2041.

4.

Conference on Electrical and Computer Engineering, Toronto, vol.1, pp.289-293.

5. Allender, S, Scarborough, P, Peto, V, Rayner, M, Leal, J, Luengo-cardiovascular herzstiftung.ch/uploads /media/ European_cardiovascular_disease_ statistics_2008.pdf.[1 October 2008].

6.

Computer Networks and Wireless Communications, vol.2, no.2, pp. 187-190.

7. Amaral, JLM, Faria, ACD, Lopes, AJ. Jansen, JM, & Melo, PL 2010,

Based on forced oscillation measurements and artificial neural

Engineering in Medicine and Biology Society, Buenos Aires, pp.1394-1397.

151

8.

International Journal of Computer Applications, vol. 4, no. 7, pp. 10-15.

9. evaluation of independent component analysis in medical image

Technology, Chennai, pp.770-774.

10. Ar

11.

The International Journal of Medical Physics Research and Practice, vol. 28, no. 8, pp. 1552 1561.

12. Ashburner, J, Csernansky, JG, Davatzikos, C, Fox, NC, Frisoni, GB. -assisted imaging to assess brain

vol. 2, no. 2, pp. 79 88.

13.

14.

no. 2, pp. 4-7.

15. a Decision-Support Architecture for Management of remotely

in Biomedicine, vol. 14, no. 5, pp. 1216-1226.

16. Bellos, C, Papadopoulos, A, Rosso, R & Fotiadis, DI 2012

of the IEEE on Engineering in Medicine and Biology Society, San Deigo, pp. 61-64.

17. -based architecture for

vol. 6, no. 2, pp. 267-292.

152

18. fuzzy controlInternational Conference on Fuzzy Systems, San Francisco, vol. 1, pp. 345-350.

19. image-based diagnosis of Alzheimer's disease: Bringing medical

Biomedical Imaging, Barcelona, pp. 134-137.

20. Bingyuan, C, Tai-Fu, L & Cheng-Yi,

Springer Books. [1 October 2009].

21.

Artificial Intelligence in Medicine (Elsevier), vol. 45, no. 2-3, pp. 185-196.

22. Chan, RH, Chung-Wa, -and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-

vol. 14, no. 10, pp. 1479-1485.

23. n filters for the

on Circuits and Systems II: Analog and Digital Signal processing, vol. 48, no. 8, pp. 784-789.

24. Cordero-Grande, L, Vegas-Sánchez-Ferrero, G, Casaseca-de-la-Higuera, P, San-Román Calvar, JA, Revilla-Orodea, A, Martín-Fernández, M & Alberola-myocardium segmentation with a Markov Random Field based

no. 3, pp. 283 301.

25. Curry

26. cardiac cavities using hierarchically search in 2D grayscale ultrasound

International Conference on Systems, Signals and Image Processing, Bratislava, pp. 225-228.

153

27.

pp. 1341-1351.

28. Dinesen, B, Grann, O, Nielsen, C, Hejlesen, O & Toft, E 2011

obstructive pulmonary disease (COPD) patients and healthcare

Vehicular Technology, Information Theory and Aerospace & Electronic Systems Technology, Chennai, pp.1-4.

29. mobile-health system to manage Chronic Obstructive Pulmonary

ce of the IEEE on Engineering in Medicine and Biology Society, San Diego, pp. 2178-2181.

30. Image analysis in medical imaging: recent

Journal, vol. 6, no. 3, pp. 1-10.

31. Dun

Analysis and Machine Intelligence, vol. 22, no. 1, pp. 85-106.

32. Importanpp. 920-929.

33. Fukuchi Y, Nishimura M, Ichinose M, Adachi, M, Nagai, A, Kuriyama, T, Takahashi, K, Nishimura, K, Ishioka, S, Aizawa, H &

-465.

34. Springfield.

35. Goldbaum, M, Moezzi, S , Taylor, A, Chatterjee, S, Boyd, J, Hunter, E & object extraction, object classification, and inferencing in retinal

IEEE International Conference on Image Processing, Lausame, vol. 3, pp. 695-698.

154

36. Prentice-Hall, India.

37. Obstructive Pulmonary Disease in the Emergency Department: A

no.11, pp.1-28.

38. Gupta, V, Vajinepalli, P, Venkatesan, S, Seth, S, Keswarpu, P,

35th Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, Osaka, pp.3020-3023.

39. Hai, J, Aobing, S, Qin, Z, Ran, Z & Ruhan,

Asian Conference on Intelligent Information and Database Systems, Dong Hoi, pp. 98-103.

40. Hara, T, Fujita, H, Lee, Y, Yoshimura, H & Kido, S 1999, X-ray

Venice, pp. 768-773.

41. rasound as a screening tool for thyroid 880.

42.

Press (Springer), New York, Available from: Springer Books. [1 March 2009].

43. Hounsfield, The International Journal of Medical Physics Research and Practice, vol. 7, no. 4, pp. 277-283.

44. Automation, Robotics and Vision

Conference, China, vol.2, pp. 1029-1036.

45.

Technology, vol. 11, no. 1, pp. 16-24.

155

46. Hussein, AS, Om

EMBS Conference on Biomedical Engineering and Sciences, Langkawi, pp.209-214.

47. algorithms vol. 4, no. 4, pp. 499-502.

48. Fuzzy Rule-Fuzzy Systems, vol. 13, no. 4, pp. 428 435.

49.

Approaches to Linguistic Data Mining, Academic Press (Springer), New York, Available from: Springer Books. [1 April 2004].

50. Jagtap, P & P -ANFIS and

Advance Computing Conference, Gurgaon, pp. 1190-1194.

51. ransactions on Pattern Analysis and

-37.

52. -network-based fuzzy inference

vol. 23, no. 3, pp. 665 685.

53. Jayaraj, VPepper Noise Removal in Images using Improved Adaptive Statistics

Network Security, vol. 9, no.11, pp. 170-176.

54. plication of image segmentation in inspection of welding of Boras.

55. of chronic obstructive pulmonary disease & peak expiratory flow

-26.

156

56. Jirawanitcharoen, K, Kiattisin, S, Leelasantitham, A & Chaiprapa, P

nal Conference on Computer Science and Information Technology, Beijing, pp. 125-128.

57.

Electronic Computer Technology, Kuala Lumpur, pp. 112-116.

58. Control and Management Systems, vol. 1, no. 2, pp. 51-56.

59. Karpagachelvi, S, Arthanari, M & Sivakumar, M 2011, h Extreme Learning

Computer Science Issues, vol. 8, no. 1, pp. 338-345.

60. Similarity Measure in Independent PCA based ClassificaInternational Journal of Computers & Technology, vol. 9, no. 2, pp. 1099-1109.

61. selection and classification of breast MRI lesions based on multi

um on Artificial Intelligence and Signal Processing, Tehran, pp. 54 58.

62. Kollorz, ENK., Hahn, DA, Linke, R, Goecke, TW, Hornegger, J -D

ging, vol. 27, no. 4, pp. 457-466.

63. th

German Workshop on Color Image Processing, Report University of Erlangen-Nurnberg, vol.34, no. 15, pp. 69-79.

64. Kulkarni, RK, Rohit A, Priti C, Priyanka P & Bhoomika R 2012, -Free Pixel Based Video De-

Journal of Engineering Research and Applications, vol. 2, no. 3, pp. 2454-2462.

157

65. Diagnosis of Parkinson's Disease Employing Virtual-Workshop on Database and Expert Systems Applications, Bilbao, pp.132-136.

66. Lado, MJ, Mendez, A.J, Vila, XA, Rodriguez-Linares, L & Felix, P

Information Systems and Technologies, Madrid, pp. 1-4.

67.

vol. 20, no. 2, pp. 404-418.

68. Proceedings of the IEEE

-511.

69. -Fuzzy

70. Lin, JS, Ligomenides, PA, Lo, SCB, Freedman, MT & Mun, SK 1994, -digital computer-aided diagnosis system for lung

IEEE Seventh Symposium on Computer-Based Medical Systems, Winston-Salem, pp. 207-212.

71. Lindberg A, Jonsson AC, Ronmark E, Larsson LG & Lundback B

according to BTS, ERS, GOLD and ATS Criteria in relation to

Respiration Journal, vol. 72, no. 5, pp. 471-479.

72. Lovell, NH, Redmond, S.J, Basilakis, J, Shany, T & Celler, BG 2010, - experiences

IEEE on Engineering in Medicine and Biology Society, Buenos Aires, pp. 5267-5269.

73.

Neural Networks, vol. 10, no. 5, pp. 1142-1152.

158

74. Mag Computer Aided Diagnosis System For the Identification And Classification of

Technology, vol. 1, no. 2, pp. 12-22.

75. re Extraction of Bone Scintigraphy for

Systems and Network Technologies, Rajkot, pp. 179-183.

76. Journal of Physics C: Solid State Physics, vol. 6, no. 22, pp. 422-426.

77. --Part II: Their relations to median, order-Transactions on Acoustics, Speech and Signal Processing, vol. 35, no. 8, pp. 1170 1184.

78. Researcher) Ordered: New Applications for Medical Imaging

-17.

79. Ming-Feng, W, Chao-Ling, C, Chih-Yu, W & Jeng-Yuan, H 2013, ve Rehabilitation Monitoring for Chronic

no. 11, pp. 4413-4422.

80. Mizotin, M, Benois-Pineau, J, Allard, M & Catheline, G 2012, -based brain MRI retrieval for Alzheimer disease diagn

IEEE International Conference on Image Processing, Orlando, pp. 1241-1244.

81. Extraction and X-ray Sciences, vol. 78, no. 8, pp. 1224-1229.

82. Murand disability by cause 1990The Lancet, vol. 349, no. 9064, pp. 1498-1504.

83. Myoung, HK, Yu-Bu, L & Yoo-Joo, image visualization and analysis systems for diagnosis and treatment

Signal Processing and Communication Systems, pp. 244-249.

159

84. O'Clock, GD, Yong Wan Lee, Jongwong Lee & Warwick, WJ 2012, -Frequency and Low-Frequency Chest Compression: Effects on

Lung Water Secretion, Mucus Transport, Heart Rate, and Blood

Transactions on Biomedical Engineering, vol. 59, no. 1, pp.106-114.

85. Oguro, S, Tuncali, K, Elhawary, H, Morrison, PR, Hata, N & -procedural MRI and

intra-procedural CT images to aid CT-guided percutaneous omputer

Assisted Radiology and Surgery (Springer), vol. 6, no. 1, pp. 111-117.

86. Oliver, A, Freixenet, J, Martí, J, Pérez, E, Pont, J, Denton, ERE &

Image Analysis (Elsevier), vol. 14, no. 2, pp. 87-110.

87.

Conference on Computational Intelligence, Modelling and Simulation, Bali, pp. 355-359.

88.

no. 9434, pp. 613-620.

89. Pauwels, RA, Buist, AS, Calverley, PM, Jenkins, CR & Hurd, SS iagnosis, Management, and

NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) workshop summary, American Journal of Respiratory Critical Care Medicine, vol. 163, no. 5, pp. 1256-1276.

90. Phooi Yee, -based analysis for classifying multimodal brain images in the Image-guided Medical

on Engineering in Medicine and Biology Society, vol. 2, pp. 3400-3403.

91.

International Conference of the IEEE Engineering on Medicine and Biology Society, Buenos Aires, pp. 6058-6061.

160

92.

in Computer Science, vol. 4, no. 4, pp. 166-171.

93. Rabe, KF, Hurd, S, Anzueto, A, Barnes, PJ, Buist, SA, Calverley, P, Fukuchi, Y, Jenkins, C, Rodriguez-Roisin, R, Weel, C & Zielinski, J 2007, Prevention of Chronic Obstructive Pulmonary Disease: GOLD

American Journal Respiratory and Critical Care Medicine, vol. 176, no. 6, pp. 532-555.

94. bronchitis in an urban locality of New Delhi-an epidemiological

pp. 273-285.

95.

Imaging, vol. 5, no. 4, pp. 170-176.

96. Ratika P, Pradhan, MP, Ashish B, Ronak, KP & Ghose, MK 2010, -cover Classification and Mapping for Eastern Himalayan State

ng, vol. 2, no. 3, pp. 166-170.

97. -year prospective epidemiological study of chronic obstructive pulmonary diseases in rural south in -44.

98. Rennard, S, Decramer, M, Calverley, PM, Pride, NB, Soriano, JB,

Internapp. 799 805.

99. Rosso, R, Munaro, G, Salvetti, O, Colantonio, S & Ciancitto, F 2010,

management platform for Chronic Obstructive Pulmonary Disease

Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, Buenos Aires, pp. 6850-6853.

161

100. Rui, -Guided Detection Technique for Screening of Infectious Pulmonary

Biomedical Engineering, vol. 57, no. 11, pp. 2646-2656.

101. Recognition UsiJournal of Electrical and Computer Engineering, vol. 2, no. 3, pp. 345-352

102. Sarlabous, L, Torres, A, Fiz, JA, Gea, J, Martinez-Llorens, JM, muscles

International Conference of the IEEE on Engineering in Medicine and Biology Society, Boston, pp. 3820-3823.

103. Selvaraj, H, Thamarai Selvi, S, Selvathi, D & MRI Slices Classification using Least Squares Support Vector

Sciences & Image Processing, vol. 1, no. 1, pp. 21-33.

104. tool for modeling and simulation of mechanically ventilated

Annual International Conference of the IEEE on Engineering in Medicine and Biology Society, Buenos Aires, pp. 569-572.

105. Shamsul Arifin, M, Golam Kibria, M, Firoze, A, Ashraful Amini, M & Hong Yan 2012, -

International Conference on Machine Learning and Cybernetics, Xian, vol. 5, pp. 1675-1680.

106. -fuzzy Fuzzy Sets and Systems

(Elsevier), vol. 112, no. 1, pp. 99 116.

107. neuro-Sets and Systems (Elsevier), vol. 112, no. 1, pp. 51-63.

108. Shufu, X, Shiguang, S, Xilin, C & Jie, IEEE

Transactions on Image Processing, vol. 19, no. 5, pp. 1349-1361.

162

109. SegmentatElectronics and Communication Engineering, vol. 2, no. 6, pp. 22-26.

110.

Communication & Instrumentation, Kerala, vol. 2, pp. 34-38.

111. Sobradillo-Pena, V, Miravitlles, M, Gabriel, R, Carlos, AJ, Villasante, C, Masa, JF, Viejo, JL & Fernandez-Fau, L, 2000,

Results of Chest Journal, vol. 118, no. 4, pp. 981 989.

112. Sorensen, L, Nielsen, M, Pechin Lo, Ashraf, H, Pedersen, JH & -Based Analysis of COPD: A Data-

Transactions on Medical Imaging, vol. 31, no. 1, pp. 70-78.

113. Saunders (Elsevier), Philadelphia.

114. Souad Guessoum, Tayeb Laskri, M, Hayet djellali & Tarek Khadir, M e Based Reasoning for the Diagnosis

International Journal of Hybrid Information Technology, vol. 5, no. 3, pp. 145-159.

115. Stang P, Lydick, E, Silberman, C, Kempel, A & Keating, ET 2000, f COPD: Using Smoking Rates to Estimate Disease

no. 5_suppl_2, pp. 354S 359S.

116. System to Assist Interpretation of Medical Images - Application to

and Measurement, vol. 55, no. 6, pp. 1944-1952.

117. International Conference

on Control Automation and Systems, Gyeonggi-do, pp. 2448-2451.

163

118. -International Journal of Approximate Reasoning (Elsevier), vol. 5, no. 3, pp. 191-212.

119. Thiruvengadam, KV, Raghava, TP &

obstructive lung disease. Asthma and Bronchitis Foundation of India, pp. 59-69.

120. Tobin, KW, Chaum, E, Govindasamy, VP & Karnowski, TP 2007,

Transactions on Medical Imaging, vol. 26, no.12, pp.1729-1739.

121. Torres, A, Sarlabous, L, Fiz, JA, Gea, J, Martinez-Llorens, JM,

muscle performance by means of diaphragm muscle mechanomyographic signals in COPD patients during an incremental

Engineering in Medicine and Biology Society, Buenos Aires, pp. 2493-2496.

122. Vere, K, Richens, J, Somekh, M, Bajaj, N, Morgan, K & O'Shea, P -array-based biosensors for the diagnosis of

Functional Optical Imaging, Ningbo, p. 1.

123. agnosis, Management, and Prevention of Chronic Obstructive Pulmonary

Available from: http://www.goldcopd.org/uploads/users/files/ GOLD_At A Glance_2013_Feb20.pdf. [20 February 2013].

124. Viegi, G, Scognamigli,o A, Baldacci, S, Pistelli, F & Carrozzi, L

19.

125. Morbidity Survey in PaResearch, vol. 54, no. 1, pp. 105-111.

126. Publishing, Adam Hilger, Bristol and Philadelphia.

164

127. onic Respiratory Disease Journal, vol. 6, no. 3, pp.177 185.

128. Wu, Y, Lo, Y, Cheng, S & Lin, C Matching for Automatic Liver Disease Diagnosis Using Generalized

Information Hiding and Multimedia Signal Processing, Darmstadt, pp. 627-630.

129.

Transactions on Medical Imaging, vol. 24, no. 1, pp. 45-57.

130. Yamomoto, S, Jiang, H, Matsumoto, R, Tateno, Y, Iinuma, T & -aided diagnosis

on Applications of Computer Vision, Sarsota, pp. 236 241.

131. Yang, X, Redmond, SJ, Mohktar, MS, Shany, T, Basilakis, J, Hession, M &

International Conference of the IEEE EMBS, Osaka, pp. 3-7.

132. Yeny, Y, Helen, H & Yeong Gil, in chest CT images for computer-International Workshop on Enterprise Networking and Computing in Healthcare Industry, pp. 378 383.

133. You, S, Bas, E, Erdogmus, D & Kalpathy-Curved Based Retinal Vessel Segmentation towards Diagnosis of

Informatics, Imaging and Systems Biology, San Jose, pp. 331-337.

134. Zadeh, LA 196(Elsevier), vol. 8, no. 3, pp. 338-353.

135. Zhang, X, Guo, Y & Du, P th IEEE International

Conference on Bioinformatics and Biomedical Engineering, Wuhan, pp.1-4.