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1

Automated detection of optic disc contours in fundus images using decision tree classifier

Pathan Sumaiya, Kumar Preetham, Pai Radhika, Bhandary Sulatha V.

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

52--64

EN

Automated segmentation of optic disc in fundus images plays a vital role in computer aided diagnosis (CAD) of eye pathologies. In this paper, a novel method is proposed which detects and excludes the blood vessel for accurate optic disc segmentation. This is achieved in two steps. First, an effective blood vessel detection and exclusion algorithm is developed using directional filter. In the second step, a decision tree classifier is used to obtain an adaptive threshold in order to detect the contour of optic disc. The proposed method aids in computationally robust segmentation of optic disc even in fundus images having illuminations, reflections and exudates. The proposed method is tested on two different datasets which includes 300 fundus images collected from Kasturba Medical College (KMC) Manipal and also the publically available RIM-ONE database. The average values of Jaccard index, dice coefficient, sensitivity, specificity and accuracy obtained for KMC images is 91.28 %, 94.17 %, 92.71 %, 99.89 % and 99.61 % respectively. For RIM-ONE database the obtained average values of Jaccard index, dice coefficient, sensitivity, specificity and accuracy are 85.30 %, 90.69 %, 93.90 %, 99.39 % and 99.15 % respectively. The obtained segmentation results proves the efficiency of the algorithm to be incorporated in CAD of eye diseases.

2

Retinal blood vessel segmentation employing image processing and data mining techniques for computerized retinal image analysis

GeethaRamani R., Balasubramanian L.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 1

102--118

EN

Most of the retinal diseases namely retinopathy, occlusion etc., can be identified through changes exhibited in retinal vasculature of fundus images. Thus, segmentation of retinal blood vessels aids in detecting the alterations and hence the disease. Manual segmentation of vessels requires expertise. It is a very tedious and time consuming task as vessels are only a few pixels wide and extend almost throughout entire span of the fundus image. Employing computational approaches for this purpose would help in efficient retinal analysis. The methodology proposed in this work involves sequential application of image pre-processing, supervised and unsupervised learning and image post-processing techniques. Image cropping, color transformation and color channel extraction, contrast enhancement, Gabor filtering and halfwave rectification are sequentially applied during pre-processing stage. A feature vector is formed from the pre-processed images. Principal component analysis is performed on the feature vector. K-means clustering is executed on this outcome to group pixels as either vessel or non-vessel cluster. Out of the two groups, the identified non-vessel group undergoes an ensemble classification process employing root guided decision tree with bagging, while vessel group is left unprocessed as further processing might increase misclassifications of vessels as non-vessels. The resultant segmented image is formed through combining the results of clustering and ensemble classification process. The vessel segmented output from previous phase is post-processed through morphological techniques. The proposed technique is validated on images from publicly available DRIVE database. The proposed methodology achieves an accuracy of 95.36%, which is comparable with the existing blood vessel segmentation techniques.

3

Ocena możliwości automatyzacji układu do rozciągania próbek na użytek spektroskopii Ramana

Wilk J., Klonecki-Olech K., Kobielarz M.

Aktualne Problemy Biomechaniki

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2010

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z. 4

275--278

PL

Badania ścian naczyń krwionośnych metodą spektroskopii Ramana, pozwalają na badanie zależności między obciążeniem jakiemu poddawana jest tkanka, a jej strukturą. W celu zwiększenia efektywności pomiarów podjęta została próba zautomatyzowania układu służącego do rozciągania próbek poddawanych badaniu.

EN

Study of vessels walls by means of Raman Spectroscopy allows to analyze the relation between load placed upon the tissue and it’s structure. To maximize the effectiveness of measurement, the goal of automation of the tensile tool used in the procedure was undertaken.

4

Fast Skeletonization of Blood Vessels

Chang S., Croasmun A.

Journal of Applied Computer Science

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2009

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Vol. 17, nr 2

17-39

EN

The study of the morphological and rheological behaviors of intramural vessels plays a critical role in various clinical applications such as surgical planning and radiotherapy. To better understand the rheological behavior of vascular structures in relation to the network morphology, we must obtain the quantitative measurements of the morphometric parameters of the vascular networks under various conditions. Morphometric parameters of the networks include vessel diameter, distance between branching points of vessels, and branching complexity. Because of the morphological complexity of blood vessels, however, it is difficult to obtain accurate measurements. In this paper, we present a novel and efficient method for skeletonization of curvilinear object. The proposed method automatically skeletonizes the vascular network in a given image and constructs a graph that represents the branching structures of the network. Since the method processes a given image as a whole, the multiple vascular networks present in the image are automatically detected and skeletonized simultaneously. Moreover, since the skeletons are represented as graph structures, various morphometric parameters are obtained automatically. We also present the very promising results of the method applied to the complex blood vessel networks in various retinal images.

5

Mineralizacja naczyń krwionośnych w świetle badań fizycznych

Gil A.

Prace Naukowe Akademii im. Jana Długosza w Częstochowie. Edukacja Techniczna i Informatyczna

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2007

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T. 2

115-126

6

Ocena kierunkowych właściwości mechanicznych ścian naczyń krwionośnych

Kobielarz M., Będziński R., Szotek S.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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2006

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z. 30

131-136

PL

Głównym celem tej pracy jest wyznaczenie właściwości mechanicznych ścian zdrowej aorty brzusznej oraz ścian tętniaka aorty brzusznej. W tym celu, przeprowadzono test jednoosiowego rozciągania próbek, które wycinano w dwóch kierunkach: wzdłużnym i obwodowym. Dla wszystkich przebadanych próbek wykreślano charakterystyki σ=f(ε) i wyznaczano dla nich umowny moduł Younga oraz wytrzymałość mechaniczną na rozciąganie. Zaobserwowano, że ściany tętniaka aorty brzusznej w porównaniu ze ścianami zdrowej aorty brzusznej są sztywniejsze.

EN

The maim aim of this research work is appointed mechanical properties of walls of normal abdominal aorta and walls of abdominal aortic aneurysms. In this end of view, the uniaxial tensile tests were performed for each specimen, which were cut out research material in two directions: longitudinal and circumferential. On the basis these tests the stress-strain characteristics were drawn for all specimens and the assumed Young's modules and the tensile strength were assigned. The results indicate that the walls of abdominal aortic aneurysms in comparison with walls of normal abdominal aortas are stiffer.

7

Models for 3D vascular image analysis

Orkisz M., Hernández Hoyos M.

Journal of Medical Informatics & Technologies

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2001

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Vol. 2, Part. 1

IP13--IP22

EN

In image processing, models are used to improve robustness of algorithms by introducing a priori knowledge. Deformable models, frequently used in the field of medical images, are described by means of energy functionals with data attachment terms and regularising terms. The regularising terms express constraints relating to the expected shapes. The expected shape of a blood vessel segment in 3D images obtained by Magnetic Resonance Imaging or by helicoidal Computed Tomography is often implicitly described by a generalised cylinder model, i.e. an association of an axis (vessel centreline) and a surface (vessel boundary). In this context, the data attachment terms involve, for candidate points, a measure of the likelihood of being located on the centreline or on the boundary. Such a measure can use models reflecting low-level local photometrical properties of the brightness patterns. This presentation will give an overview of the recently used models and will be illustrated by the authors' contribution.

8

Numerical solution of pennes bio-heat transfer equation with the blood vessels

Mochnacki B., Majchrzak E., Jasiński M.

Zeszyty Naukowe Katedry Mechaniki Stosowanej / Politechnika Śląska

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1999

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z. 10

233-236

EN

In the paper the heat transfer within the tissue in the presence of a pair of blood vessels is analyzed. Taking into account the of a blood vessel and inconsiderable change of blood temperature along the vessel one can consider the 2D problem. In order to solve the boundary element method is used. In the final part of the paper the example of computations is presented.

PL

W pracy rozważano przepływ ciepła w tkance biologicznej w obecności pary naczyń krwionośnych. Biorąc pod uwagę wymiary pojedynczego naczynia i niewielką zmianę temperatury krwi na jego długości, zadanie traktowano jako problem 2D. Do rozwiązania wykorzystano metodę elementów brzegowych. W końcowej części pracy przedstawiono przykład obliczeń numerycznych.