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PET and CT image registration is an important tool of clinical diagnosis of diseases. For PET and CT images, a preprocessing algorithm of medical image registration is proposed in this paper. The algorithm process includes image normalization, CT image adaptive threshold adjustment and automatic extraction of tissues based on morphology, edge detection and statistical analysis theory, and improved...
This paper presented a novel application of Magneto encephalography (MEG) and diffusion tensor image (DTI) on word recognition, in which the spatiotemporal signature and the neural network of brain activation associated with word recognition were investigated. The word stimuli consisted of matched and mismatched words, which were visually and acoustically presented simultaneously. Twenty participants...
The computer-assisted methods for measuring and tracking nodule volumes have the potential to improve precision for indicating of malignancy for indeterminate nodules. In this paper, we propose a semi-automatic geometric solitary pulmonary nodule (SPN) volume measurement algorithm for calculating the precise volume of indeterminate SPNs with low-dose CT (LDCT) images. The algorithm divided the SPN...
In this paper, an interactive lung parenchyma segmentation algorithm is put forward with improved Live-Wire model, Snake model and contour interpolation, which takes full advantage of lung contours' slow change in adjacent CT image layers and operators' professional knowledge. Firstly, we manually select key slices of lung parenchyma in serial CT images, then draw the lung's contours in key slices...
Image contrast enhancement is a very critical step for automatic medical image processing and analyzing applications. In this paper, we described a novel image enhancement algorithm based on the single-scale Retinex (SSR) theory to enhance the tiny anatomical structures and other regions of interest on the low-dose CT (LDCT) images. This algorithm applies a three-stage approach: (a) separating the...
In this paper we present a method for developing a fully automated computer aided diagnosis (CAD) system to help radiologist in detecting and diagnosing micro-calcifications (MCCs) in digital format mammograms. One aim of the CAD system is to increase the effectiveness and efficiency of screening procedures by using computer. Another aim of the CAD is to extract and analyze the characteristics of...
As an important and necessary step in many medical image processing applications, contrast enhancement can amplify tiny anatomies, such as airways, vessels, lung nodules and pulmonary fissures in lung CT (computerized tomography) images. In this paper we describe a more useful contrast enhancement algorithm based on localized histogram equalization for low-dose CT images. This algorithm applies a...
The pulmonary fissures are the boundaries between the lobes in the lungs. They are useful for the analysis of pulmonary conformation and the diagnosis of lung disease on a lobar level. This paper introduces a technique for the semi-automatic extraction of lung lobar major fissures on HRCT images. First we get the direction and approximate bound of the fissure using Ridgelet transform, and then use...
The accurate segmentation of pulmonary nodules lays the foundation for distinguishing malignant from benign pulmonary nodules. In this paper, a robust and automatic algorithm is proposed to segment lung nodules slice-by-slice in three dimensional (3D) Computed Tomography (CT) images. A nonparametric estimation method called Mean-Shift (MS) algorithm was applied to segmenting lung nodules. It is critical...
Computer-aided detection (CAD) schemes can assist radiologists in the early detection of lung cancer which is crucial to the chance for curative treatment. Characterizing the pulmonary nodules in the multislice X-ray computed tomography (CT) images is notoriously difficult. This is due to the fact that the anatomical structures such as blood vessels, bronchi, and alveoli are subject to partial volume...
This paper presents a novel enhancement filter as a preprocessing step in the early detection of lung cancer. The identification and enhancement of the nodular structures is the initial stage in computer-aided diagnosis (CAD) for improving the sensitivity of nodule detection and reducing the number of false positives. Based on nodular texture feature and mathematical morphology, our proposed enhancement...
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