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In a lung auscultatory sounds diagnosis , the diagnosis result would be affected by the skill of the doctor, that is, the doctor should discriminate a lung sounds by own subjective, since standard diagnosis procedure with objectivity has not been established yet. In many cases of the lung sounds diagnosis, the existence of features, which are called(More)
Visual inspection of diffuse lung disease (DLD) patterns on high-resolution computed tomography (HRCT) is difficult because of their high complexity. We proposed a bag of words based method on the classification of these textural patters in order to improve the detection and diagnosis of DLD for radiologists. Six kinds of typical pulmonary patterns were(More)
The purpose of this work is to present some technical approaches of our computer-aided detection (CAD) system for chest radiograms and helical CT scans, and also evaluate that by using three databases. The CAD includes some methods to detect lesions and to eliminate false-positive findings. The detective methods consist of template matching and artificial(More)
We evaluated the usefulness of a computerized analysis system in the detection of interstitial lung abnormalities in digitized chest radiography. This system uses the processes of four-directional Laplacian-Gaussian filtering, linear opacity judgment, and linear opacity subtraction. For qualitative analysis, we employed a combined radiographic index, which(More)
SUMMARY Computer-aided diagnosis (CAD) systems on diffuse lung diseases (DLD) were required to facilitate radiologists to read high-resolution computed tomography (HRCT) scans. An important task on developing such CAD systems was to make computers automatically recognize typical pulmonary textures of DLD on HRCT. In this work, we proposed a bag-of-features(More)
Minimum description length (MDL) based group-wise registration was a state-of-the-art method to determine the corresponding points of 3D shapes for the construction of statistical shape models (SSMs). However, it suffered from the problem that determined corresponding points did not uniformly spread on original shapes, since corresponding points were(More)
PURPOSE For realizing computer-aided diagnosis (CAD) of computed tomography (CT) images, many pattern recognition methods have been applied to automatic classification of normal and abnormal opacities; however, for the learning of accurate classifier, a large number of images with correct labels are necessary. It is a very time-consuming and impractical(More)
To analyze diffuse lung diseases based on chest region computed tomography (CT) imaging by using a computer-aided diagnosis (CAD) system, it is necessary to first determine the lung regions subject to analysis. The lung regions can be selected relatively easily for healthy individuals, by applying a threshold. Selecting an area by using a threshold-based(More)
We applied and optimized the sparse representation (SR) approaches in the computer-aided diagnosis (CAD) to classify normal tissues and five kinds of diffuse lung disease (DLD) patterns: consolidation, ground-glass opacity, honeycombing, emphysema, and nodule. By using the K-SVD which is based on the singular value decomposition (SVD) and orthogonal(More)