A. Rey

University of A Coruña, A Coruña, Galicia, Spain

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Publications (2)0 Total impact

  • A. Rey, B. Arcay, A. Castro
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    ABSTRACT: The detection of pulmonary nodules is one of the most studied areas and challenging task in the field of medical image analysis, due the current relevance of the lung carcinoma. The difficulty and complexity of this task has led to the development of CAD systems for the automated detection of lung nodules in CT scans, which provides valuable assistance for radiologists and could improve the detection rate. A common phase of these systems is the detection of regions of interest (ROIs) that could be marked as nodules, in order to reduce the searching space problem. In this paper, we evaluate and compare the combination of various approaches of supervised vector machines (SVMs) with different kinds of fuzzy clustering algorithms, so as to improve the detection and segmentation of ROIs that could represent lung nodules in high resolution CT scans. These images are provided by the LIDC database (Lung Internet Database Consortium).
    Fuzzy Systems (FUZZ), 2011 IEEE International Conference on; 07/2011
  • A. Rey, A. Castro, B. Arcay
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    ABSTRACT: The complexity of detecting pulmonary nodules has led to the development of Computer Aided Systems (CAD) that automate and reduce the cost of this task. The first phase of such systems usually consists in preprocessing the Computer Tomography (CT) scans, with the aim of segmenting the lungs and eliminating the elements that might interfere with the process. This paper presents an automatic method for the segmentation of lungs into three-dimensional pulmonary high resolution CT images. The proposed method has three main steps, that combine both 3D and 2D techniques. Firstly the trachea and the main airways are removed from the volume; then the lung region is segmented by grey-level thresholding, separating the right and left lungs if a junction is visible in the image, and the lung contour is smoothed; finally, a ”region growing” is applied using two seeds from each identified lung, avoiding as such the incorporation of other elements that do not belong to the lungs.
    Biomedical Engineering, 2011 10th International Workshop on; 01/2011