Advances in Intelligent Analysis of Medical Data and by Abdel-Badeeh M. Salem (auth.), Roumen Kountchev, Barna 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 as a result of the fruitful and vibrant discussions throughout the MedDecSup'2012 overseas Workshop bringing jointly a correct physique of data, and new advancements within the more and more vital box of clinical informatics. This conscientiously edited ebook offers new principles aimed toward the improvement of clever processing of assorted forms of scientific info and the perfection of the modern computers for clinical determination aid. The e-book offers advances of the clinical info platforms for clever archiving, processing, research and search-by-content on the way to increase the standard of the scientific prone for each sufferer and of the worldwide healthcare method. The booklet combines in a synergistic means theoretical advancements with the practicability of the ways constructed and provides the final advancements and achievements in scientific informatics to a large variety of readers: engineers, mathematicians, physicians, and PhD scholars.

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Power distribution for Set 3, level 1: a - not arranged, b - arranged a b Fig. 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.

If the distance from this point to the segment is less then the threshold value ε then all points on this segment are rejected; otherwise we remember this point, and the segment from the previous step is divided into two parts. Step 4. We recursively repeat Step 3 for a new polyline building. As a result, the curve containing only the saved points will be received. The last stage of tracking of anchor points is executed for each frame: Step 1. The initial object image f0(x, y) is received. Step 2.

Group of 9 consecutive CT images in Set 3 Decorrelation of Sequences of Medical CT Images 49 On Fig. 4 are shown the corresponding eigen images, obtained in result of applying the 2-levels HAKLT algorithm on the group of images (Set 3). Eigen Image 1 Eigen Image 2 Eigen Image 4 Eigen Image 5 Eigen Image 7 Eigen Image 8 Eigen Image 3 Eigen Image 6 Eigen Image 9 Fig. 4. Еigen images, obtained for Set 3 after performing 2-levels HAKLT As it could be seen from the results on Fig. 4, on the first eigen image is concentrated the main part of the energy of all 9 images, and the energy of each next eigen image decreases quickly.

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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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