Wyniki wyszukiwania - BazTech

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Grafowe techniki sztucznej inteligencji w percepcyjnej analizie przestrzennych zobrazowań tętnic wieńcowych

Ogiela M., Tadeusiewicz R., Trzupek M.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2005

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Vol. 11, nr 3-4

10-13

PL

W pracy omówiono sposoby wykorzystania technik inteligencji obliczeniowej, a zwłaszcza grafowych formalizmów lingwistycznych do tworzenia syntaktycznego opisu znaczeniowego przestrzennych wizualizacji naczyń wieńcowych serca. Opisy takie mogą być wykorzystywane w inteligentnych systemach wspomagania diagnostyki medycznej, ukierunkowanych na dokonywanie komputerowej interpretacji semantycznej poszczególnych części drzewa naczyń wieńcowych. Interpretacja taka pozwoli na szybką I w znacznym stopniu automatyczną detekcję miejsc istotnych przewężeń światła naczyń. W tym też celu wykorzystane zostały grafowe formalizmy obrazowe, oparte na gramatykach generujących IE grafy, które pozwalają na wykrywanie nieprawidłowości uwidocznionych na obrazach otrzymywanych w trakcie badań diagnostycznych mięśnia sercowego, z użyciem spiralnej tomografii komputerowej. Zaletą omawianych formalizmów obrazowych jest możliwość dokonywania automatycznej Identyfikacji miejsc zmian chorobowych, a także znaczeniowego opisu badanych rekonstrukcji przestrzennych naczyń wieńcowych.

EN

In this paper there will be described the way of application of computational intelligence techniques, and especially graph linguistic formalisms for creation syntactic meaning description of spatial coronary arteries structure. Such descriptions may be than used in intelligent medical diagnosis support systems, which will allow to make essentially steered semantic interpretation of sections coronary arteries morphology as well as fast Identification and automatisation of lumen stricture detection. In order to state a correct diagnosis and define the degree of pathological changes has been used graph image languages based on the expansive graph grammars of IE type. These kinds of grammars enable effective detection of abnormalities in diagnostic images obtained using spiral computerized tomography. An advantage of these Image languages Is automatic identification of changes essential from diagnostic point of view, and the introduction of semantic relations and description In reconstruction of analyzed coronary vessels.

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Artificial intelligence methods in shape feature analysis of selected organs in medical images

Ogiela M., Tadeusiewicz R.

Image Processing & Communications

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2000

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Vol. 6, no 1-2

3-11

EN

The goal of this paper is a presentation of the possibilities of the application of syntactic methods of computer image analysis to the recognition of the local stenoses of the lumen of coronary arteries, and to the detection of pathological signs in upper parts of ureter ducts and renal calyxes. An analysis of the correct morphology of these structures is possible thanks to the application of sequence and tree methods from the group of syntactic methods of pattern recognition. In the case of the analysis of coronary artery images, the main objective is a computer-aided early diagnosis of the different forms of cardiac ischemic diseases. Such diseases may show themselves in the form of stable or unstable disturbances of heart rhythm or infarction. In the analysis of kidney radiograms the main goal is the recognition of local irregularities in ureter lumens, and an examination of the morphology of renal pelvis and calyxes.

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Computer techniques of image enhancement and their application in visualization of anatomic structures during preliminary analysis of medical images

Ogiela M.

Image Processing & Communications

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1999

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Vol. 5, no 1

33-44

EN

The article presents the group of transformations which medical pictures can be subjected to, in the aim of enhancing of their contrast and better distinguishing and diagnosis of organs shown in this pictures. In this work, the analysis was based on images acquired by various techniques, such as roentgenography (RTG), magnetic resonance imaging (MRI), classic computer tomography (CT) and ultrasonography (USG). Contrast expansion in these images was performed using the histogram method of balancing of gray levels and the method based on the modification of tonal curve. Such transformations were necessary during preliminary processing of these images, especially to adjust their quality to next steps of the analysis in case of automatic medical diagnosis, and also to enable their visual evaluation by specialists and diagnostic interpretation of images of organs and their structural features. The studies show that the method based on the modification of tonal curve yields better results in case of images acquired by roentgenography and magnetic resonance imaging. On the other hand, histogram method is more suitable for contrast expansion in CT and USG images.

4

Geometric transformations in the shape analysis of selected biomedical structures

Ogiela M.

Image Processing & Communications

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1998

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Vol. 4, no 3-4

27-36

EN

The article presents an algorithm of the transformation straightening outer contours of objects, allowing to transform bilogical structures of interest, visible in medical images, from two-dimensional space of the image into two-dimensional graph, representing contours of the straightened object with its possible outer morphological changes, indicating the progress of pathological processes. The developed method is based on a sequence of geometric transformations of the analyzed objects in the image, and its operation was described in detail and illustrated by examples of transformation of main pancreatic ducts, appearing in X-ray images acquired by ERCP, as well as by graphs showing outer morphology of blood vessels in the fundus of the eye and morphology of renal sinuses from kidneys roengenograms. The proposed method is universal, and due to the fact that the transformation preserves and exposes pathologic morphological changes, such as abnormal lateral branches, local dilatations or projections it can also be used in the recognition and analysis of other structure images acquired by various techniques of computer tomography, e.g. celebral vessels, bile ducts, coronary vessels of fragments of gastroin-testinal tract. The graphs of the structures of interest obtained as a result of the transformation straightening outer contours of objects are a starting point for the recognition of morphological changes, important for diagnosis, using syntactic methods of pattern recognition.