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Data reduction is an important step in knowledge discovery from data. The high dimensionality of databases can be reduced using suitable techniques, depending on the requirements of the data mining processes. In this work, Rough set theory (RST) has been used as such a tool with much success. RST enables the discovery of data dependencies and the reduction of the number of attributes contained in...
For the purpose of taking good use of the diagnosis obtained from medical experts and improving the accuracy of chest X-ray images retrieval, the lung fields are segmented and interested regions are marked off on the basis of chest X-ray images having been processed previously; the Gray Difference Statistics is used to indicate the texture feature of each region. Using the K-nearest neighbor classifier,...
Diabetic retinopathy is the commonest cause of blindness. Diabetes causes cataracts, Glaucoma and diabetic retinopathy. The Optic Disc is the exit point of retinal nerve fibers from the eye and the entrance and exit point for retinal blood vessels. The detection of Optic Disc is very essential to locate the various anatomical features in the retinal images. We describe a new filtering approach in...
Attribute filters allow enhancement and extraction of features without distorting their borders, and never introduce new image features. These are highly desirable properties in biomedical imaging, where accurate shape analysis is paramount. However, setting the attribute-threshold parameters has to date only been done manually. This paper explores simple, fast and automated methods of computing attribute...
Doppler imaging allows evaluation of blood flow patterns, direction, and velocity. The color (red, blue, and mosaic) signify the direction of the blood flow. By analyzing this color Doppler, it is possible to detect heart diseases like mitral and aortic stenosis, mitral, tricuspid, and aortic regurgitation, and Left Ventricle (LV) hypertrophy. We present 3 methods to extract low level features namely...
The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult...
In this paper, we present an intelligent approach to analysing prostrate ultrasound images in order to diagnose prostate cancer. Algorithms based on fuzzy image processing are applied first to enhance the contrast of the original image, to extract the region of interest and to enhance the edges surrounding that region. Then, we extract features characterising the underlying texture of the regions...
The `fuzzy co-clustering algorithm for images (FCCI)' technique has been successfully applied to colour segmentation of medical images. The goal of this work is to extend this technique by the inclusion of texture features as a clustering parameter for detecting blotches in skin lesions based on colour information. The objective function is optimized using the bacterial foraging algorithm which gives...
The clinical interpretation of breast MRI remains largely subjective, and the reported findings qualitative. Although the sensitivity of the method for detecting breast cancer is high, its specificity is poor. Computerised interpretation offers the possibility of improving specificity through objective quantitative measurement. This paper reviews the plethora of such features that have been proposed...
The main objective of this research is to develop a prototype system for diagnosing paddy diseases, which are blast disease (BD), brown-spot disease (BSD), and narrow brown-spot disease (NBSD). This paper concentrates on extracting paddy features through off-line image. The methodology involves image acquisition, converting the RGB images into a binary image using automatic thresholding based on local...
In this study texture differentiation associated to bone regeneration properties, around loaded oral implants immersed to Platelets Rich Plasma (PRP), was investigated in panoramic radiographs. The bone-to-implant contact region was analyzed in a follow up clinical sample of 30 digitized panoramic radiographs, 15 corresponding to implant loading (Class I) and 15 after an 8 month period (Class II)...
The presence of microcalcifications clusters, which appear as small bright spots in mammographic images, can be considered as a very important sign for breast cancer diagnosis. They can, however, be hard to detect due to their size and low contrast from surrounding normal tissue. In this paper, a new fuzzy-based method is presented to provide an appropriate segmentation of microcalcifications. This...
Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. Firstly, we construct 6 different Gaussian templates that are used to enhance the coronary angiograms. Then the transition region is extracted by using local entropy-based on transition region extraction...
This paper proposes a new segmentation approach by considering the non extensive property of mammograms. The novel thresholding technique is performed by Tsallis entropy characterized by one more parameter q, which depends on the nonextensiveness of mammogram. Mammograms are typical examples of image with fractal-type structures (nonextensiveness). The proposed approach has been tested on various...
We present a registration method for medical images based on shape information and voxel intensities. First, we segment volume images using the Markov random field and the Gibbs distribution. We extract the 3D feature points of the shape from the surface of the segmented object. Then, we conduct first registration using ordinary Procrustes analysis for two sets of 3D feature points. For the second...
Meniscal myxoid degeneration (MMD) represents a type of degenerative lesion, characterized by histological alterations of the meniscus. In the context of magnetic resonance (MR) imaging evaluation of MMD, the incidence of the condition is indicated by the presence of high intensity signal within the meniscus, while normal menisci are depicted as of homogeneously low intensity. In the present study,...
This paper describes our ongoing efforts to provide efficient and accurate classification of microcalcification clusters in mammogram images. In this paper, a study of the characteristics of true microcalcifications compared to falsely detected microcalcifications is carried out using first and second order statistical texture analysis techniques. These features are generated in order to reduce the...
Classification of breast lesions is clinically most relevant for breast radiologists and pathologists for early breast cancer detection. This task is not easy due to poor ultrasound resolution and large amount of patient data size. This paper proposes a five step novel and automatic methodology for breast lesion classification in 3-D ultrasound images. The first three steps yield an accurate segmentation...
Classification of breast lesions is clinically most relevant for breast radiologists and pathologists for early breast cancer detection. This task is not easy due to poor ultrasound resolution and large amount of patient data size. This paper proposes a five step novel and automatic methodology for breast lesion classification in 3-D ultrasound images. The first three steps yield an accurate segmentation...
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