Read e-book online Medical Image Understanding Technology: Artificial PDF

By Professor Ryszard Tadeusiewicz (auth.), Professor Ryszard Tadeusiewicz, Professor Marek R. Ogiela (eds.)

ISBN-10: 3540409971

ISBN-13: 9783540409977

ISBN-10: 364253578X

ISBN-13: 9783642535789

A unique description of a brand new method of perceptual research and processing of scientific photos is given. rather than conventional development reputation a brand new approach to photo research is gifted, in response to a syntactic description of the shapes chosen at the photo and graph-grammar parsing algorithms. this system of "Image realizing" are available as a version of mans’ cognitive photo realizing strategies. The usefulness for the automated realizing of the benefit of scientific pictures is confirmed in addition to the power for giving invaluable diagnostic descriptions of the health problems. As an program, the construction of a content-based, instantly generated index for arranging and for looking out clinical photos in multimedia clinical databases is presented.

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Extra info for Medical Image Understanding Technology: Artificial Intelligence and Soft-Computing for Image Understanding

Sample text

Heart sounds and murmurs), and especially, various Images. A characteristic feature of these signals (registration of various information is semantically not reducible to a text or a set of digits, especially medical images) is, among others, that in general their ontologies have not been weil developed yet; therefore in semantic networks they are very difficult from the point of view of intelligent servicing. However, as has already been said, multimedia resources of medical information collected in the numerical form keep growing and this growth will continue to accelerate if we take into consideration the planned development of telemedicine.

This is iIIustrated in Fig. 33 showing the same medical problem in the form of two completely dissimilar images registered in two different patients but leading to the same diagnosis. Fig. a-b. Both ERCPs show pancreatic cancer but the images are not that similar to each other Since the form of an image is not identical to its content, we need tools which will allow us to 'extract' the content (semantic sense) ofthe image trapped in its more complicated form. Automatie image understanding postulated by the authors both in this book and in other publications consist of automatie extraction of some significant sense, which is contained in the image but trapped in its form.

As a result, the searching process applied later (to be discussed in a while) will find in the data base primarily such 'obvious' cases; in view of the search purpose this cannot be considered as a defect. Let us remind ourselves that the objective of a semantic search for medical images in a data base usually means finding images that can be used as didactie examples or as reference objects in the process of finding the optimal diagnosis. Here the usefulness of 'good' images subject to unambiguous classification seems to be indisputable.

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Medical Image Understanding Technology: Artificial Intelligence and Soft-Computing for Image Understanding by Professor Ryszard Tadeusiewicz (auth.), Professor Ryszard Tadeusiewicz, Professor Marek R. Ogiela (eds.)

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