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1
Content available Fast edge detection approach based on global optimization convex model and Split Bregman algorithm
Jing Y., Liu J., Liu Z., Cao H.
Diagnostyka
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2018
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Vol. 19, No. 2
23--29
EN
Active contour model is a typical and effective closed edge detection algorithm, which has been widely applied in remote sensing image processing. Since the variety of the image data source, the complexity of the application background and the limitations of edge detection, the robustness and universality of active contour model are greatly reduced in the practical application of edge extraction. This study presented a fast edge detection approach based on global optimization convex model and Split Bregman algorithm. Firstly, the proposed approach defined a generalized convex function variational model which incorporated the RSF model’s principle and Chan’s global optimization idea and could get the global optimal solution. Secondly, a fast numerical minimization scheme based on split Bregman iterative algorithm is employed for overcoming drawbacks of noise and others. Finally, the curve evolves to the target boundaries quickly and accurately. The approach was applied in real special sea ice SAR images and synthetic images with noise, fuzzy boundaries and intensity inhomogeneity, and the experiment results showed that the proposed approach had a better performance than the edge detection methods based on the GMAC model and RSF model. The validity and robustness of the proposed approach were also verified.
2
Content available remote Automatic seed point selection in ultrasound echography images of breast using texture features
Selvan S., Shenbaga Devi S.
Biocybernetics and Biomedical Engineering
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2015
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Vol. 35, no. 3
157--168
EN
Automatic segmentation of breast lesions in 2D ultrasound B-scan images via active contours, require a seed point to be selected inside the breast lesion. The grey levels on an ultrasound image of the breast show intensity information. The fat tissue is hypo echoic relative to the surrounding glandular tissue. The glandular parenchyma tissue usually appears homogeneously echogenic as compared with fat lobules. Simple cysts are anechoic. Malignant solid masses are usually heterogeneous, hypo echoic and tend to look intensely black compared to surrounding isoechoic fat. Benign solid masses tend to appear on ultrasound with intense and uniform hyper echogenicity. Texture features represent changes in grey level intensities. This paper proposes a method that can automatically identify a seed point based on texture features and allow automatic contour initialization for level set segmentation. This seed point plotted on an US B-scan image is mapped on to its corresponding elastogram pair. The proposed approach is applied to 199 ultrasound B-scan images of which 52 are benign solid masses, 84 malignant solid masses and 63 simple and complex cysts. The seed point obtained using this approach is mapped to its corresponding elastogram pair in 62 US B-scan and US elastography image pairs. Quantitative experiment results show that our proposed approach can successfully find proper seed points based on texture values, in ultrasound B-scan images and therefore in elastography images, with an overall accuracy of 86.93%. This approach is effective and makes segmentation of breast lesions computationally easier, more accurate and fast.
3
Content available remote Monitoring combustion process using image classification
Kotyra A., Sawicki D.
Przegląd Elektrotechniczny
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2014
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R. 90, nr 11
130--132
EN
This paper presents comparison image classification method of co-firing biomass and pulverized coal. Defined two class of combustion: stable and unstable for three variants with different power value parameters and fixed amount biomass. Compared naïve Bayes classifier and support vector machine (SVM) with RBF kernel function. Experimental results show that achieved correct classification of images for the assumed variations.
PL
W pracy przedstawiono porównanie wybranych metod klasyfikacji obrazów dla współspalania pyłu węglowego i biomasy. Zdefiniowano dwie klasy spalania: stabilne i niestabilne dla trzech wariantów z różnymi parametrami mocy oraz stałą ilością biomasy. Porównano naiwny klasyfikator bayesowski oraz metodę wektorów nośnych z radialną funkcją jądrową (RBF). Wyniki badań pokazują, poprawną klasyfikację obrazów dla założonych wariantów.
4
Content available remote Semi-Automatic Segmentation of Ct/Mri Images Based on Active Contour Method for 3D Reconstruction of Abdominal Aortic Aneurysms
Drapikowski P., Domagała Z.
Image Processing & Communications
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2014
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Vol. 19, no. 1
13--19
EN
The paper presents a CT/MRI image based semi-automatic AAA (abdominal aortic aneurysm) segmentation method. Segmentation process can run automatically with the active contour method but results are controlled by the operator. If incorrect segmentation is noticed, the operator may introduce corrections. The proposed method makes possible the segmentation of dissected aneurysms, with which no automatic analysis works. Controlling the segmentation process by the operator serves to ensure correct geometric shape reproduction, which is crucial in deploying aneurysm models to help assess rupture risk.
5
Content available Automatic segmentation of corneal endothelial cells using active contours
Charłampowicz K., Reska D., Bołdak C.
Advances in Computer Science Research
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2014
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Nr 11
47--60
EN
We present a new method for segmenting the corneal endothelial cells from microscopic images. It uses multiple active contours initialized by adaptive thresholding and limited with their growing to not overlap. Thanks to the inherent characteristics of the active contour both outcomes can be achieved: cell quantity and delimitation. The tool implementing this approach is built within the MESA framework - an environment for developing and evaluating segmentation techniques. The accuracy is estimated on the base of real microscopic cell images segmented manually.
PL
W artykule zaprezentowano autorską automatyczną metodę segmentacji komórek śródbłonka rogówki oka z obrazów mikroskopowych. Metoda używa wielu aktywnych konturów zainicjalizowanych wewnątrz komórek za pomocą adaptacyjnego progowania i ograniczonych w swoim rozroście tak, aby nie pokrywać się. Metoda został zaimplementowana w środowisku MESA przeznaczonym do rozwoju i ewaluacji technik segmentacji. Jakość segmentacji została oszacowana na rzeczywistych obrazach mikroskopowych w odniesieniu do ręcznie zaznaczonych konturów komórek.
6
Content available remote Real-Time Object Tracking using Gradient Vector Flow
Azadi S., Pourjam E., Nikkerdar A., Sharifi M.
Przegląd Elektrotechniczny
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2013
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R. 89, nr 1a
280--283
EN
In this paper an object tracking system with utilizing optical flow technique, and Gradient Vector Flow (GVF) active contours is presented. Optical flow technique is less sensitive to background structure and does not need to build a model for the background of image so it would need less time to process the image. GVF active snakes have good precision for image segmentation. However, due to the high computational cost, they are not usually applicable. Since precision is one of the important factors in the image segmentation, several methods have been developed to overcome the computational speed. In this paper, we, first, recognize the moving object. Then, the object fame with some pixels surrounding to it, was created. Then, this new frame is sent to the GVF filed calculation procedure. Contour initialization is obtained based on the selected pixels. This approach increases the calculation speed, and therefore makes it possible to use the contour for the tracking. The system was built, and tested with a microcomputer. The results show a speed of 10 to 12 frames per second which is considerably suitable for object tracking approaches.
PL
W artykule przedstawiono system śledzenia obiektu z wykorzystaniem techniki Optic Flow oraz Gradiend Vector Flow. Wykrywanie ruchomego obiektu stanowi pierwszy etap działania, następnie ramka zawierająca obiekt przesyłana jest do algorytmu GVF, gdzie określany jest zarys obiektu. Dzięki temu podejściu możliwe jest wykorzystanie, wymagającego obliczeniowo GVF w śledzeniu obiektów. Przedstawiono wyniki eksperymentalne.
7
Content available Porównanie wybranych metod wyznaczania obszaru płomienia w wizyjnym systemie diagnostycznym
Sawicki D., Kotyra A.
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
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2013
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nr 4
14--17
PL
W pracy przedstawiono porównanie wybranych metod wykrywania krawędzi dla obrazów spalania pyłu węglowego. Porównano metodę gradientową Canny’ego z metodą zbiorów poziomicowych oraz metodą opartą o model konturu aktywnego Chan-Vese. Wyniki badań pokazują, że metoda korzystająca z modelu Chan-Vese dobrze odwzorowała brzeg obszaru.
EN
This paper presents comparison edge detection method of combustion pulverized coal. Compared method are: Canny edge detection operator, level set method and Chan-Vese active contour method. Experimental results show that edges extracted with method based on Chan-Vese active contour model gives good result.
8
Wykorzystanie konturu aktywnego do określenia obszaru płomienia w wizyjnym systemie diagnostycznym
Kotyra A., Sawicki D., Gromaszek K., Smolarz A.
Elektronika : konstrukcje, technologie, zastosowania
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2012
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Vol. 53, nr 6
27-28
PL
W pracy przedstawiono porównanie wybranych metod wykrywania krawędzi dla obrazów spalania pyłu węglowego. Porównano metodę gradientową Canny'ego z metodą zbiorów poziomicowych oraz metodą opartą o model konturu aktywnego Chan-Vese. Wyniki badań pokazują, że metoda korzystająca z modelu Chan-Vese dobrze odwzorowała brzeg obszaru.
EN
This paper presents comparison edge detection method of combustion pulverized coal. Compared method are: Canny edge detection operator, level set method and Chan-Vese active contour method. Experimental results show that edges extracted with method based on Chan-Vese active contour model gives good result.
9
Content available HIST - an application for segmentation of hepatic images
Reska D., Krętowski M.
Zeszyty Naukowe Politechniki Białostockiej. Informatyka
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2011
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Z. 7
71-93
EN
HIST (Hepatic Image Segmentation Tool) is a Java-based application for segmentation and visualisation of medical images, specialised for hepatic image analysis. This paper contains an overview of the application features, a description of adapted segmentation algorithms and their experimental validation. The application provides two main segmentation methods, based on region growing and active contour model methods, adapted for the case of liver segmentation. HIST also offers data visualisation tools, including multiplanar reconstruction, volume rendering and isosurface extraction.
PL
HIST (ang. Hepatic Image Segmentation Tool – narzędzie do segmentacji obrazów wątroby) jest napisaną w języku Java aplikacją do segmentacji i wizualizacji obrazów medycznych, wyspecjalizowaną segmentacji w obrazów wątroby. Artykuł ten zawiera przegląd możliwości aplikacji, opis zaadaptowanych algorytmów segmentacji i wizualizacji oraz ich eksperymentalną walidację. Aplikacja oferuje dwie główne metody segmentacji, oparte o algorytmy rozrostu regionów i aktywnego konturu, dostosowane do segmentacji wątroby. Narzędzia wizualizacyjne aplikacji wykorzystają rekonstrukcję multiplanarną, rendering wolumetryczny oraz ekstrakcję izopowierzchni.
10
Content available remote Neural networks for medical image processing
Pieciak T., Jaworek J., Gorgon M.
Bio-Algorithms and Med-Systems
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2011
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Vol. 7, no. 4
101--110
EN
The proposed article presents the most common types of artificial neural networks used to be performed in the field of medical imaging. The first section describes the use of artificial neural networks in the preprocessing stage, restoration of noisy and distorted images and in conjunction with morphological operations. The second part presents the artificial neural networks in image segmentation problem, particularly in adaptive binarization threshold level selection and as a complement to the active contour method.
11
Content available remote Myocardial segmentation based on magnetic resonance sequences
Pieciak T.
Bio-Algorithms and Med-Systems
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2010
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Vol. 6, no. 12
85--90
EN
A strain analysis is a novel diagnostics method used in the cardiology. The advanced regional quantitive analysis of the myocardium during a systole and a diastole allows to diagnose a cardiac cycle. Realization of the analysis requires a myocardial segmentation algorithm. In this paper the myocardial segmentation method from the cardiovascular magnetic resonance sequences (CMR) has been presented. The endocardium areas are calculated using active contour algorithm with the gradient vector flow forces (GVF). Apart from that, the algorithm uses fuzzy logic approach to detect the edges. As a result, the curve matches to image contents. The epicardium boundaries are being designated and supplemented by the surrounding analysis and Fourier descriptors. Based on the endocardium and the epicardium boundaries which limit the myocardium it is possible to realize analysis a local stenosis detection and the directional strain during the cardiac cycle. The analysis is based on the CMR images of the left ventricle which were acquired in short axis of left ventricle and radial direction. The most important achievements presented in this paper are fuzzy logic application in the image processing, the active contour segmentation method improvements and the formal descriptions of the myocardium boundaries.
12
Content available remote Segmenting "flares" in ultrasound images using prior statistics
Stippel G., Duskunovic I., Philips W., Lemahieu I.
Image Processing & Communications
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2001
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Vol. 7, no 1-2
41-54
EN
The common method neonatologists use nowadays to determine White Matter Damage (leukomalacia) is by visual inspection of ultrasound images of the neonatal brain. A need for a (semi)-computerized computerized way of delineating the affected regions, in order to make quantitative measurements as an aid to the subjective diagnosis, is felt. The use of active contours for this purpose is a classical approach [5, 6]. The performance of active contours for this purpose, however, is heavily deteriorated by the presence of speckle noise. In this article a new filter, incorporating prior statistics concerning medical features in these images, is proposed, that removes a significant amount of speckle noise in the healthy parts, while it makes regions affected by WMD more uniform, thus severely improving the performance of the active contour. The results of the active contour after applying the proposed technique are compared with the manual delineation of an expert. Furthermore the proposed technique is compared with two other popular speckle suppression techniques, namely the ones proposed by Lee and Frost.
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