The Atlas of Heart Disease and Stroke. World Health Organization, 2004
Google Scholar
Ministry of Public Health (2002) Burden of disease and injuries in Thailand Priority setting for policy, pp A14–A16
Google Scholar
Jalivand M, Li X, Zwick T, Wiesbeck W, Pancera, E (2011) Hemorrhagic stroke detection via UWB medical imaging. In: Antennas and propagation (EUCAP), proceeding of the 5th European conference on, pp 2911–2914, April (2011)
Google Scholar
Neethu S, Venkataraman D (2015) Stroke detection in brain using CT images. J Artif Intell Evol Algorithms Eng Syst 324:379–386 (Springer, 2015)
Google Scholar
Roy S, Chatterjee K, Bandyopadhyay SK (2014) Segmentation of acute brain stroke from MRI of brain image using power law transformation with accuracy estimation. J Adv Comput, Netw Inf 27, 453–461 (Springer International Publishing)
Google Scholar
Wysoki MG et al (1998) Head trauma: CT scan interpretation by radiology residents versus Staff Radiologists. Radiology 208(1):8–125
CrossRef
Google Scholar
Erickson BJ, Bartholmai B (2002) Computer aided detection and diagnosis at the start of the third millennium. J Digit Imag 15(2):59–68
CrossRef
Google Scholar
Sharma N, Aggarwal LM (2010) Automated medical image segmentation techniques. J Med Phys, Assoc Med Physicists India 3, 35(1)
Google Scholar
Vymazal J, Rulseh AM, Keller J, Janouskova L (2012) Comparison of CT and MR imaging in Ischemic Stroke. In: Insight into imaging 3(6), 619–627
Google Scholar
Praveen R Mirajakar, Arun Vikas Singh, Dr. Kishan Asok Bhagwat, Ashalatha M E.: Acute ischemic stroke detection using wavelet based fusion of CT and MRI images. In: International conference on advances in computing, communication and informatics, IEEE (2015)
Google Scholar
Doi K (2007) Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph 31(4–5):198–211
CrossRef
Google Scholar
Yoshida H, Nappi J (2001) Three dimensional computer-aided diagnosis scheme for detection of colonic polyps. IEEE Trans Med Imaging 20(12):1261–1274
CrossRef
Google Scholar
Yoshida H, Nappi J, MacEneaney P, Rubin DT, Dachman AH (2000) Computer aided diagnosis scheme for detection of polyps at CT colonography. Radiographics 22(4):963–979
CrossRef
Google Scholar
Schlachetzki F, Herzberg M, Hlscher T, Ertl M, Zimmermann M, Ittner KP et al (2012) Transcranial ultrasound from diagnosis to early stroke treatment: part 2: prehospital neurosonography in patients with acute stroke: the Regensburg stoke mobile project. Cerebrovasc Dis 33:262–271
CrossRef
Google Scholar
Perez N, Valdes J,Guevara M, Silva A (2009) Spontaneous intracerebral hemorrhage image analysis methods: a survey. In: Advances in computational vision and medical image processing (2009)
Google Scholar
Liu Y, Rothfus WE, Kanade T (1997) Content based 3D neuoradiologic image retrieval: preliminary results. In: IEEE content-based video and image retrieval workshop associated with CVPR97
Google Scholar
Dhawan AP, Loncaric S, Hitt K, Broderick J, Brott T (1993) Image analysis and 3D visualization of intracerebral brain hemorrhage. In: IEEE Symposium on Computer Based Medical Systems, pp 140–145
Google Scholar
Cosic D, Loncaric S (1997) Computer system for quantitative analysis of ischemic from ct head images. In: 19th Annual international conference of the IEEE (1997)
Google Scholar
Chan T (2007) Computer aided detection of small acute intracranial hemorrhage on computer tomography of brain. Compute Med Imaging Graph 31(4), 285–298
Google Scholar
Zhang WL, Wang XZ (2007) Feature extraction and classification for human brain CT images. Proc IEEE Int Conf Mach Learn Cybern 2:19–22
Google Scholar
Fallahi AR, Pooyan M, Khotanlou H A new approach for classification of human brain CT images based on morphological operations. J Biomed Sci Eng 3, 78–82
Google Scholar
Chawla M, Sharma S, Sivaswamy J, Kishore L (2009) A method for automatic detection and classification of stroke from brain CT images. In: Proceedings of the Annual International conference IEEE Engineering in Medicine and Biology Society (EMBC 09)
Google Scholar
Liu R, Tan CL, Leong TY, Lee CK, Pang BC, Lim CT, Tian Q, Tang S, Zhang Z (2008) Hemorrhage slices detection in brain ct images. In: International conference on pattern recognition, pp 1–4
Google Scholar
Hara T, Matoba N, Zhou X, Yokoi S, Aizawa H, Fujita H, Sakashita K, Matsuoka T (2007) Automated detection of extradural and subdural hematoma for content-enhanced CT images in emergency medical care. In: Proceeding of SPIE (2007)
Google Scholar
Das DS, Rani GU, Moorthy GS (2012) Analysis of PSNR for Different 3D DWT. J Int J Inf Technol Secur 1, ISSN 2279–008X
Google Scholar
Przelaskowski A et al (2007) Improved early stroke detection: wavelet based perception enhancement of computerized tomography exams. J Comput Biol Med 37, pp 524–533, Science Direct
Google Scholar
Seemann T (2012) Digital image processing using local segmentation book. Monash University, Australia
Google Scholar
Badioze Zaman H et al (2009) Automated segmentation and retrieval system for CT head images. In: IVIC 2009. LNCS, 5857, pp 97–109. Springer, Berlin
Google Scholar
Rajini NH, Bhavani R (2013) Computer aided detection of ischemic stroke using segmentation and texture features. J Meas 46, 1865–1874 (Science Direct)
Google Scholar
Nagalkar V, Agrawal S (2012) Ischemic stroke detection using digital image processing by fuzzy methods. J Int J Latest Res Sci Technol 1(4), 345–347
Google Scholar
Balasooriya U, Perera MUS (2012) Intelligent brain hemorrhage diagnosis using artificial neural networks. In: IEEE business, engineering & industrial applications colloquium (BEIAC)
Google Scholar
http://funnotes.net/tofpages/TopicOfFortnight.php?tofTpcFl=topicoffortnight2
Lee TH (2009) Segmentation of CT brain images using unsupervised clustering. J Vis 12(2), 131–138
Google Scholar
Ramos OE, Rezaei B Scene segmentation and interpretation image segmentation using region growing. M.Sc. thesis, Computer
Google Scholar
Gonzalez CR, Woods ER (2000) Digital image processing, 2nd edn. Prentice Hall, New Jersey
Google Scholar
Kaganami HG, Beij Z (2009) Region based detection versus edge detection. In: IEEE transaction on intelligent information hiding and multimedia signal processing, pp 1217–1221
Google Scholar
Kyaw MM (2013) Computer aided detection system for hemorrhage contained region. J Int J Comput Sci Inf Technol 1(1)
Google Scholar
Pauline J, Hitesh Sh (2012) Brain tumor classification using wavelet and texture based neural network. J Int J Sci Eng Res 3(10). ISSN 2229–5518
Google Scholar
Coifman R, Meyer Y, Quake S, Wickerhauser MV (1993) Signal processing and compression with wavelet packets. In: Progress in wavelet analysis and applications (Toulouse, 1992), pp 77–93, Frontiers, Gif
Google Scholar
Licciardi G, Pacifici F, Tuia D, Prasad S, West T, Giacco F, Thiel C, Inglada J, Christophe E, Chanussot J, Gamba P (2009) Decision fusion for the classification of hyper spectral data: outcome of the 2008 GRS-S data fusion contest. In: IEEE transaction on geo science and remote sensing, vol 47, no 11, pp 3857–3865
Google Scholar
Arivazhagan S, Ganesan L (2003) Texture segmentation using wavelet transform, Elsevier. Pattern Recog Lett 24:3197–3203
CrossRef
MATH
Google Scholar
Haralick RM, Shanmugam K, Dinstein I (1973) Textural features for image classification. IEEE Trans Syst, Man Cybern 3(6):610–621
CrossRef
Google Scholar
Hema Rajini N, Bhavani R (2013) Automatic classification of computed tomography brain images using ANN, k-NN and SVM. J. AI & Society 29, 97–102 (Springer)
Google Scholar
Sundararaj GK, Balamurugan V (2014) Robust classification of primary brain tumor in computer tomography images using K-NN and linear SVM. In: International conference on contemporary and informatics
Google Scholar
McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in nervous activity. Bull Math Biophys 5
Google Scholar
Cristianini N, Shawe T, Taylor J (2000) An introduction to support vector machines and other Kernel-based learning methods, 1st edn. Cambidge University Press, New York
Google Scholar
Suykens JAK, Vandewalle J (1999) Least squares support vector machines classifiers . Neural Process Lett 9(3), 293–300
Google Scholar
Olesen J, Gustavsson A, Svensson M, Wittchen HU, Jonsson B (2012) CDBE2010 study group: European brain council the economic cost of brain disorders in Europe. J Eur J Neurol 19:155–162
CrossRef
Google Scholar
Padma Nanthagopal A, Sukanesh Rajamony R (2012) Automatic classification of brain computed tomography images using wavelet based statistical texture features. J Vis Soc Jpn 1–10
Google Scholar
Amato F, López A, Peña-Méndez EM, Vaňhara P, Hampl A, Havel J (2013) Artificial neural network in medical diagnosis. J Appl Biomed 111, 47–58
Google Scholar
irtskhulava L, Wong J, Al-Majeed S, Pearce G (2015) Artificial neural network model in stroke diagnosis. In: UKSIM-AMSS International conference on modeling and simulation
Google Scholar
Li GZ, Yang J, Liu GP, Xue L (2004) Feature selection for multi-class problems using support vector machines. Image Process Pattern Recogn 109–111
Google Scholar