Read e-book online Advances in Intelligent Analysis of Medical Data and PDF

By Abdel-Badeeh M. Salem (auth.), Roumen Kountchev, Barna Iantovics (eds.)

ISBN-10: 3319000284

ISBN-13: 9783319000282

ISBN-10: 3319000292

ISBN-13: 9783319000299

This quantity is because of the the fruitful and bright discussions through the MedDecSup'2012 overseas Workshop bringing jointly a proper physique of information, and new advancements within the more and more vital box of scientific informatics. This conscientiously edited e-book provides new rules aimed toward the advance of clever processing of assorted sorts of scientific details and the perfection of the modern computers for scientific determination aid. The publication offers advances of the clinical details platforms for clever archiving, processing, research and search-by-content so one can enhance the standard of the scientific providers for each sufferer and of the worldwide healthcare procedure. The e-book combines in a synergistic approach theoretical advancements with the practicability of the methods built and offers the final advancements and achievements in scientific informatics to a wide diversity of readers: engineers, mathematicians, physicians, and PhD scholars.

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Extra info for Advances in Intelligent Analysis of Medical Data and Decision Support Systems

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6. Power distibution for Set 3, level 2: a - not arranged, b - arranged Decorrelation of Sequences of Medical CT Images 51 Fig. 7. , Set 7 (R=7), and on Fig. 8 a, b - their corresponding graphic distributions. The data in the last column of Table 2 show, that in the first 3 eigen images are concentrated 95,7 % of the total mean power of all 9 images in GMI. Table 2. 0 a. 0 b. Fig. 8. a. Mean Power Distribution; b. Relative Mean Power Distribution for all sets of eigen images 52 R. Kountchev and P.

Model-based Segmentation and Recognition of Dynamic Gestures in Continuous video streams. Pattern Recognition 44, 1614–1628 (2011) Visual System of Sign Alphabet Learning for Poorly-Hearing Children 39 4. : Segmentation and Recognition of Continuous Gestures. In: Int. Conf. , vol. 1, pp. I365–I368 (2007) 5. : Large-vocabulary Continuous Sign Language Recognition Based on Transition-movement Models. IEEE Trans. Syst. Man. Cybern. Part A: Syst. Humans 37(1), 1–9 (2007) 6. : Simultaneous Gesture Segmentation and Recognition Based on Forward Spotting Accumulative HMMs.

Anal. of Med. , SCI 473, pp. 41–55. 1007/978-3-319-00029-9_4 © Springer-Verlag Berlin Heidelberg 2013 42 R. Kountchev and P. Ivanov spatial positions of the Computer Tomography (CT) scanner. Because of the large volume of the visual medical information, various algorithms are used for its compression. For still MRI are usually used algorithms based on the DCT, wavelet decomposition for prediction or zero-tree/block coding [5, 6, 7], etc. For compression of CT images sequences are used: interframe decorrelation based on hierarchical interpolation (HINT) [8, 9], spatial active appearance model [10], JPEG-LS and JPEG2000 with interframe motion compensated prediction [11, 12] and distributed representation of image sets based on Slepian-Wolf coding [13].

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Advances in Intelligent Analysis of Medical Data and Decision Support Systems by Abdel-Badeeh M. Salem (auth.), Roumen Kountchev, Barna Iantovics (eds.)

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