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In this paper, we introduce a hybrid image registration approach for diffusion weighted image (DWI) distortion correction. General intensity-based multimodal registration uses mutual information (MI) as the similarity metric, which can cause matching ambiguities due to the intensity correspondence uncertainty in some anatomical regions. We propose to overcome such limitations by enhancing the registration...
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...
This paper presents a wavelet-based texture analysis method for classification of melanoma. The method applies tree-structured wavelet transform on different color channels of red, green, blue and luminance of dermoscopy images, and employs various statistical measures and ratios on wavelet coefficients. Feature extraction and a two-stage feature selection method, based on entropy and correlation,...
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...
We present a novel methodological framework for leveraging multiple image sources, including different modalities, acquisition protocols or image features, in the registration of more than two images via information theoretic data fusion. The technique, referred to as multi-attribute combined mutual information (MACMI), adopts a multivariate application of mutual information (MI) to allow several...
Brain magnetic resonance (MR) images consist of different structures and features when they are observed at different scales and layers. Conventional non-rigid brain MR image registration methods mainly estimate the optimum transformation by relying on the information of a single layer and this can lead to the loss of information contained in other layers. In this paper, we propose a multi-layer framework...
This article presents a systematic analysis of focus functions in conventional sputum smear microscopy for tuberculosis. This is the first step in the development of automatic microscopy. Nine autofocus functions are analyzed in a set of 1200 images with varying degrees of content density. These functions were evaluated using quantitative procedures. The main accomplishment of this work was to show...
Recognition of prostate calculus is an important step to determine the source of pathological organ, and is of great importance for further diagnosis of prostate cancer. In this paper, due to some tissues are similar to calculus, and prostate calculus usually adheres to other tissues, a recognition algorithm for prostate calculus based on transition region and PCA-SVM is proposed. Firstly, local entropy,...
Understanding the kinematics of the knee joint as it undergoes normal physical activities is an important goal of the orthopaedic research community. The limitations of previous approaches to capturing knee kinematics include the requirement for tantalum beads to be implanted prior to imaging and the use of biplanar X-ray imaging which is not commonly available in hospital imaging departments. A recently...
Feature extraction and classification of EEG signals is core issues on EEG-based brain computer interface (BCI). Typically, such classification has been performed using signals from a set of selected EEG sensors. Because EEG sensor signals are mixtures of effective signals and noise, which has low signal-to-noise ratio, motor imagery EEG signals can be difficult to classification. Energy entropy was...
In the present work, a similarity metric based on image difference entropy has been investigated for myocardial contrast echocardiography non-rigid registration. The image histogram size has shown to influence registration accuracy, improving results for difference entropy, which has presented better results when compared to other two well known similarity metric in literature, namely, normalized...
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,...
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