Wyniki wyszukiwania - BazTech

1

Zastosowanie algorytmów przeszukiwania grafów do analizy obrazów medycznych

Dimitrova-Grekow T., Dąbkowski A.

Pomiary Automatyka Kontrola

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2012

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R. 58, nr 7

578-580

PL

W artykule przedstawiono wyniki testów niekonwencjonalnego zastosowania metod do przeszukiwania grafów w celu analizy obrazów powstałych z rezonansu magnetycznego głowy. Zaprezentowano GUI do automatycznej obróbki serii obrazów. Zbudowane klasyfikatory wykazały, że metoda BFS analizy plików DICOM, po odpowiednej selekcji cech, pozwala na 100% rozpoznawanie chorych na wodogłowie i ponad 90% zdrowych, co zachęca do dalszych badań i obserwacji, np. czy osoby sklasyfikowane błędnie jako chorzy, po czasie rzeczywiście nie rozwinęli tej choroby.

EN

There are many methods for image segmentation [1, 2]: threshold, area, edge and hybrid methods. Area methods indicate groups of similar pixels form local regions [3, 4]. Edge methods detect boundaries between homogeneous segments [5, 6, 7]. In this paper we present the results of tests of unconventional implementation of graph search methods for the analysis of images generated from magnetic resonance imaging [8]. We explored the effectiveness of different approaches for dividing areas within a similar gray scale, using adapted graph search algorithms (DFS, BFS) after appropriate modification (Fig. 1). For this purpose, the Weka package (a tool for pre-processing, classification, regression, clustering and data visualization) was used [9]. A training set was generated after analyzing all the series of images from the database. First, we evaluated models created using certain algorithms and compared their efficacy (Tab. 1). This was followed by a selection of attributes (Tab. 2) and a re-evaluation of the models (Tab. 3). Comparison of the results of both evaluations showed that after selection of the relevant product attributes, you can achieve up to 100% detection of patients with hydrocephalus and over 90% proper recognition of healthy persons. This encourages further research and observation, such as whether persons wrongly classified as sick actually developed the disease in time. We designed a web application for the study, written in Windows Azure, as well as a GUI for automatic processing of a series of images (Fig. 2).

2

A computer aided dignostic system for survival analysis after EVAR treatment of EVAR

Maiora J., Grańa M.

Journal of Medical Informatics & Technologies

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2011

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Vol. 18

51--58

EN

Abdominal Aortic Aneurysm (AAA) is a local dilation of the Aorta that occurs between the renal and iliac arteries. Recently developed treatment involves the insertion of a endovascular prosthetic (EVAR), which has the advantage of being a minimally invasive procedure but also requires monitoring to analyze postoperative patient outcomes. The most widespread method for monitoring is computerized axial tomography (CAT) imaging, which allows 3D reconstructions and segmentations of the aorta's lumen of the patient under study. Previously published methods measure the deformation of the aorta between two studies of the same patient using image registration techniques. This paper applies neural network and statistical classifiers to build a predictor of patient survival. The features used for classification are the volume registration quality measures after each of the image registration steps. This system provides the medical team an additional decision support tool.

3

Komputerowe wspomaganie diagnostyki obrazowej w medycynie

Piętka E.

Pomiary Automatyka Kontrola

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2005

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R. 51, nr 9 bis

16--18

PL

Komputerowe wspomaganie diagnostyki (CAD) medycznej w zakresie analizy i oceny zmian patologicznych widocznych w obrazach klinicznych staje się niezbędne w codziennej praktyce radiologicznej. Ilość danych oraz tryb dostępu do nich zwiększają zapotrzebowanie na komputerowe wsparcie procesu diagnostycznego. Różnorodność procesów diagnostycznych wyznacza różne konfiguracje, w których wykorzystywane są aplikacje analizy obrazu i klasyfikacji wzorca. Autonomiczna stacja CAD jest rozbudowana do systemu CAD, w którym dane oraz aplikacja analizy obrazów dostępne są lokalnie lub zdalnie. Integracja z systemem archiwizacji i transmisji obrazów oraz ze szpitalnym systemem informacyjnym umożliwia wykorzystanie zgromadzonych w nim danych oraz. infrastruktury informatycznej do transmisji informacji.

EN

Computer aided diagnosis (CAD) in an analysis and assessment of pathological abnormalities in medical imaging is a common procedure in clinical environment. The amount of data and the access mode increase the needs for a computer support at the diagnostic procedure. The variability of diagnostic procedures sets the requirements for the informatics infrastructure in which the application program, responsible for the image analysis and pattern recognition, are implemented. A plug-in CAD work-station is extended to a CAD system in which the database as well as the application software are accessed locally or remotely. The integration with clinical Picture Archiving and Communication System (PACS) lakes the advantages of a large image database for testing and evaluation of the application software and the informatics infrastructure is employed for data communication. Implementation of Web technology permits a CAD server to be connected with clinical workstations used by physicians and accessed remotely.