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EN
The segmentation and classification of brain magnetic resonance (MR) images are the crucial and challenging task for radiologists. The conventional methods for analyzing brain images are time-consuming and ineffective in decision-making. Thus, to overcome these limita-tions, this work proposes an automated and robust computer-aided diagnosis (CAD) system for accurate classification of normal and abnormal brain MR images. The proposed CAD system has the ability to assist the radiologists for diagnosis of brain MR images at an early stage of abnormality. Here, to improve the quality of images before their segmentation, contrast limited adaptive histogram equalization (CLAHE) is employed. The segmentation of the region of interest is obtained using the multilevel Otsu's thresholding algorithm. In addition, the proposed system selects the most significant and relevant features from the texture and multiresolution features. The multiresolution features are extracted using discrete wavelet transform (DWT), stationary wavelet transform (SWT), and fast discrete curvelet transform (FDCT). Moreover, the Tamura and local binary pattern (LBP) are used to extract the texture features from the images. These features are used to classify the brain MR images using feedforward neural network (FNN) classifier, where different meta-heuristic optimization algorithms, e.g., genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), and gbest-guided gravitational search algorithm (GG-GSA) are employed for optimizing the weights and biases of FNN. The extensive experimen-tal results on DS-195, DS-180, and three standard datasets show that the classification accuracy of GG-GSA based FNN classifier outperforms all mentioned meta-heuristic-based classifiers and several state-of-the-art methods.
EN
Ultrasound is the most widely used imaging modality for screening of breast tumors. However, due to the presence of speckle noise in an ultrasound image, the diagnostic information gets masked and the interpretation of the breast abnormalities becomes difficult for the radiologist. The texture of the tumor region and the shape/margin characteristics are considered to be important parameters for the analysis of the breast tumors. In the present work, exhaustive experimentation has been carried out for the design of CAD systems for classification of breast tumors by considering (a) original images only, (b) despeckled images only and (c) both original and despeckled images together (hybrid approach). Total 100 breast ultrasound images (40 benign and 60 malignant) have been used for the analysis. Initially, these images have been despeckled using six filters namely Lee sigma, BayesShrink, DPAD, FI, FB and HFB filters. Total 162 features (149 texture and 13 morphological features) have been computed from both original and despeckled breast ultrasound images and SVM classifier has been used extensively for the classification. The results of the study indicate that the hybrid approach of CAD system design using texture features computed from original images combined with morphological features computed from images despeckled by DPAD filter yield optimal performance for classifica-tion of benign and malignant breast tumors with a classification accuracy of 96.0%. From the promising results of the study it can be concluded that the proposed hybrid CAD system design could be used as a second opinion tool in clinical setting.
EN
The paper presents possibilities of X-ray computed tomography (CT) application in view of representing selected features of carbonate rocks in a CT image. 72 sections of drill cores, approx. 1 m long each, were selected for tomographic examinations to obtain as reliable as possible results. The selected core material represents carbonate formations of various ages (from Palaeozoic to Upper Cretaceous), originating from boreholes situated in the Carpathian Foreland area. The interpretation of tomographic examinations was connected with a detailed sedimentological analysis of selected core sections, allowing to carry out direct comparisons, which of studied features and to what extent have disclosed in the CT images, and also whether this image can supplement or make the prepared descriptions more detailed. The presented information has a qualitative nature, i.e. referring mainly to descriptive features of the analysed carbonate rocks. Because of a limited size of the paper we have focused only on a few from numerous analysed features of carbonate rocks. The method of X-ray computed tomography (CT) can be very helpful at the analysis of various carbonate rocks features, such as structural and textural features, biogenic structures, porosity, and fracturing. It should be emphasised that this is a non-invasive method, providing a possibility to reproduce the CT image in various directions, without the necessity of mechanical interference in the rock material, resulting in the core destruction. Mummified siliceous sponges were examples of biogenic structures, which were best reflected in formations, which have been subjected to processes of selective dolomitization. In such type of carbonate rocks the sponge mummies were not dolomitized, while the basic material of the background was dolomitized. A very good representation of the structure in CT images was obtained for colonial hexacorals from the Scleractinia group, because many details of their skeleton structure are noticeable. Contrary to siliceous sponges the structure of corals is preserved much worse in the case, when the studied deposits were subject to diagenetic processes (such as dissolution, recrystallisation, or dolomitization). In addition, the analysis of various bioclasts, preserved in carbonate rocks, has shown a significant role both of the original mineral component building the skeletal elements of organisms (aragonite, high-magnesium calcite, lowmagnesium calcite), and of diagenetic processes history, directly affecting the condition of those components preservation. Based on the analysed materials it was found that porosity and fracturing are among best reflected features of carbonate rocks in the CT image. Open fractures, fractures filled with anhydrite and fractures filled with clay-marly material are generally well reflected in the CT image. Instead, fractures filled with calcite are variously recognisable, depending on the mineral composition of the rock background.
PL
W artykule przedstawiono możliwości wykorzystania rentgenowskiej tomografii komputerowej (CT) pod kątem odzwierciedlenia wybranych cech skał węglanowych w obrazie CT. Do badań tomograficznych wytypowano 72 odcinki rdzeni wiertniczych o długości ok. 1 m każdy w celu uzyskania możliwie najbardziej wiarygodnych wyników. Wytypowany materiał rdzeniowy reprezentuje utwory węglanowe różnego wieku (od paleozoiku po górną kredę), pochodzące z otworów wiertniczych, zlokalizowanych na obszarze przedgórza i w podłożu Karpat. Interpretację badań tomograficznych powiązano ze szczegółową analizą sedymentologiczną wybranych odcinków rdzeni, co pozwoliło na bezpośrednie porównanie, które z badanych cech i w jakim stopniu ujawniły się w obrazie tomograficznym, a także czy obraz ten jest w stanie uzupełnić lub uszczegółowić wykonane opisy. Przedstawione informacje mają charakter jakościowy, tj. odnoszący się głównie do cech opisowych analizowanych skał węglanowych. W związku z ograniczoną objętością artykułu skoncentrowano się jedynie na kilku spośród wielu przeanalizowanych cech skał węglanowych. Metoda rentgenowskiej tomografii komputerowej (CT) może być bardzo pomocna przy analizie różnego typu ich cech, takich jak: cechy strukturalne i teksturalne, struktury biogeniczne, porowatość, szczelinowatość. Należy podkreślić, że jest to metoda nieinwazyjna, dająca możliwość odtwarzania obrazu tomograficznego w różnych kierunkach, bez konieczności mechanicznej ingerencji w materiał skalny, prowadzącej do niszczenia rdzenia. Spośród przeanalizowanych struktur biogenicznych uwagę zwrócono na zmumifikowane gąbki krzemionkowe, które w najlepszym stopniu odwzorowane zostały w zapisie CT w utworach, które w trakcie diagenezy poddane zostały procesom selektywnej dolomityzacji. W tego typu utworach mumie gąbek nie uległy dolomityzacji, podczas gdy masa podstawowa otaczającego osadu została zdolomityzowana. Bardzo dobre odzwierciedlenie struktury w zapisie CT uzyskano dla kolonijnych koralowców sześciopromiennych z grupy Scleractinia, gdyż w obrazie tomograficznym dostrzegalnych jest wiele detali budowy ich szkieletu. W przeciwieństwie do gąbek krzemionkowych, struktura koralowców zachowana jest znacznie gorzej w przypadku, gdy badane utwory poddane zostały w większym stopniu procesom diagenetycznym (takim jak rozpuszczanie, rekrystalizacja czy też dolomityzacja). Ponadto analiza różnego typu bioklastów, zachowanych w skałach węglanowych, wykazała istotną rolę, zarówno pierwotnego składnika mineralnego budującego elementy szkieletowe organizmów (aragonit, kalcyt wysokomagnezowy, kalcyt niskomagnezowy), jak również historii procesów diagenetycznych, mających bezpośredni wpływ na stan zachowania tych elementów. Na podstawie przeanalizowanych materiałów stwierdzono, że porowatość i szczelinowatość są jednymi z najlepiej odwzorowanych w zapisie tomograficznym cech skał węglanowych. W obrazie CT na ogół w bardzo dobrym stopniu czytelne są szczeliny otwarte, szczeliny wypełnione anhydrytem oraz szczeliny wypełnione materiałem ilasto-marglistym. Natomiast szczeliny zabliźnione kalcytem rozpoznawalne są w różnym stopniu, w zależności od składu mineralnego tła skalnego.
EN
Melanoma and dysplastic lesions are pigmented skin lesions whose accurate classification is of great importance. In this paper, we have proposed a computer-aided diagnosis (CAD) system to improve the diagnostic ability of the conventional ABCD (asymmetry, border irregularity, color, and diameter) analysis. We introduced features extracted by local analysis of range of intensity variations within the lesion that describe pigment distribution and texture (PDT) features. The statistical distribution of pigmentation at a specified direction and distance was analyzed through grey level co-occurrence matrix (GLCM). Some other quantitative features were also extracted by computing neighborhood grey-tone difference matrix. These were correlated with human perception of texture. A hybrid classifier was designed for classification of melanoma, dysplastic, and benign lesions. Log-linearized Gaussian mixture neural network (LLGMNN), K-nearest neighborhood (KNN), linear discriminant analysis (LDA), and support vector machine (SVM) construct the hybrid classifier. The proposed system was evaluated on a set of 792 dermoscopy images and the diagnostic accuracies of 96.8%, 97.3%, and 98.8% for melanoma, dysplastic, and benign lesions were achieved, respectively. The results indicate that PDT features are promising features which in combination with the conventional ABCD features are capable of enhancing the classification performance of the pigmented skin lesions.
EN
Fatty liver is a prevalent disease and is the major cause for the dysfunction of the liver. If fatty liver is untreated, it may progress into chronic diseases like cirrhosis, hepatocellular carcinoma, liver cancer, etc. Early and accurate detection of fatty liver is crucial to prevent the fatty liver progressing into chronic diseases. Based on the severity of fat, the liver is categorized into four classes, namely Normal, Grade I, Grade II and Grade III respectively. Ultrasound scanning is the widely used imaging modality for diagnosing the fatty liver. The ultrasonic texture of liver parenchyma is specific to the severity of fat present in the liver and hence we formulated the quantification of fatty liver as a texture discrimination problem. In this paper, we propose a novel algorithm to discriminate the texture of fatty liver based on curvelet transform and SVD. Initially, the texture image is decomposed into sub-band images with curvelet transform enhancing gradients and curves in the texture, then an absolute mean of the singular values are extracted from each curvelet decomposed image, and used it as a feature representation for the texture. Finally, a cubic SVM classifier is used to classify the texture based on the extracted features. Tested on a database of 1000 image textures with 250 image textures belonging to each class, the proposed algorithm gave an accuracy of 96.9% in classifying the four grades of fat in the liver.
EN
Hematological malignancies i.e. acute lymphoid leukemia and acute myeloid leukemia are the types of blood cancer that can affect blood, bone marrow, lymphatic system and are the major contributors to cancer deaths. In present work, an attempt has been made to design a CAC (computer aided classification system) for diagnosis of myeloid and lymphoid cells and their FAB (French, American, and British) characterization. The proposed technique improves the AML and ALL diagnostic accuracy by analyzing color, morphological and textural features from the blood image using image processing and to assist in the development of a computer-aided screening of AML and ALL. This paper endeavors at proposing a quantitative microscopic approach toward the discrimination of malignant from normal in stained blood smear. The proposed technique firstly segments the nucleus from the leukocyte cell background and then computes features for each segmented nucleus. A total of 331 geometrical, chromatic and texture features are computed. A genetic algorithm using support vector machine (SVM) classifier is used to optimize the feature space. Based on optimized feature space, an SVM classifier with various kernel functions is used to eradicate noisy objects like overlapped cells, stain fragments, and other kinds of background noises. The significance of the proposed method is tested using 331 features on 420 microscopic blood images acquired from the online repository provided by the American society of hematology. The results confirmed the viability or potential of using a computer aided classification method to reinstate the monotonous and the reader-dependent diagnostic methods.
7
Content available remote Quick texture generation for multiobject image analysis in brain pathology
EN
The paper presents two methods of texture features generation for recognition between neoplasm and non-neoplasm cells in cancer diagnosis. There are few problems which need to be solved to achieve the best results: differentiable images, extraction of the individual cell image, selection of the most important features. We propose two models solving all of these problems. We compare the consequences of implementation Unser’s selected texture features and Markov Random Field model. The results of numerical experiments have shown in both methods quite good accuracy in recognizing cells. The proposed methods have proved to be useful in practical application at the diagnosis of cancer.
PL
Referat przedstawia zastosowanie generacji cech teksturalnych w rozpoznawaniu komórek nowotworowych. Proces rozróżniania komórek jest dość złożony ze względu naturalną złożoność obrazów, konieczność ekstrakcji pojedynczej komórki obrazu oraz trudności w wyborze odpowiednio różnicującej cechy. W pracy porównane zostały efekty zastosowania dwóch rodzajów modeli – opartego na cechach Unsera oraz modelu Markova. Główny nacisk pracy położony jest na praktyczne zastosowanie obu metod w diagnozie nowotworowej.
EN
Analysis of the texture of sediments from the Glinojeck borehole (sheet Sochocin) allowed to better understand conditions of their accumulation environment. Sandy sediments were divided into fluvioglacial, fluvioperiglacial and fluvial units. Rate and duration of the accumulation processes were determined. The analysis also allowed to distinguish between thick units of glacial till. No sediments representing climatic optimum of any interglacial were found in the borehole since the sediments must have been accumulated in harsh environmental conditions (sparse vegetation and intensive aeolian processes during the Małopolanian and Great Interglacials).
EN
The sediment texture data (grain size, quartz grain abrasion, and roundness) from a range of different glacial environments at Hansbreen in southern Spitsbergen are presented. The six main sediment groups were distinguished: subglacial till, supraglacial debris cover, debris flow deposits, supra- and englacial meltwater stream deposits, dirt cone and proglacial glaciofluvial deposits. The division is supported by grain size statistics (presented in form of 3D diagrams), and is also legible in quartz grain abrasion differences. The latter one reveals strong changeability depending on the grain size class. No correlation between clay ratio and standard deviation vs. quartz grain abrasion was found. Lithology has limited impact on clast roundness (analysed for > 2.8 mm fraction), although restricted by short distance and time of transportation. A comparison with similar data set from Werenskioldbreen shows the deposits of Hansbreen as more mature, which is probably caused by reworking of older deposits and longer transport.
PL
Wybrane cechy teksturalne osadów (rozkład uziarnienia, abrazja ziarna kwarcowego - grainformametria mechaniczna i obtoczenie) zostały określone dla prób z różnych środowisk glacjalnych lodowca Hansa (Hansbreen), południowy Spitsbergen. Wyróżniono 6 podstawowych grup osadów: osady subglacjalane, pokryw supraglacjalnych, osady spływów błotnych, stożków ablacyjnych, supra- i inglacjalnych potoków wód roztopowych oraz proglacjalnych osadów fluwioglacjalnych. Podział ten znalazł swoje odzwierciedlenie w analizie statystycznych wskaźników uziarnienia (prezentowanych w postaci diagramów 3D) i jest również czytelny w zróżnicowaniu abrazji ziarna kwarcowego. Ta ostatnia wykazuje zróżnicowanie w zależności od wielkości frakcji. Nie wykryto wyraźnej relacji pomiędzy wskaźnikiem ilastości oraz odchyleniem standardowym a wskaźnikami obtoczenia. Litologia ma ograniczony wpływ na obtoczenie (analizowana frakcja > 2,8 mm). Porównanie z podobnym zestawem danych dla lodowca Werenskiolda (Werenskioldbreen) wskazuje na większą dojrzałość osadów lodowca Hansa, prawdopodobnie można to wiązać z redepozycją starszych osadów i dłuższym transportem.
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