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A Computer-aided diagnosis (CAD) system aims to facilitate characterization and quantification of abnormalities as well as minimize interpretation errors caused by tedious tasks of image screening and radiologic diagnosis. The system usually consists of segmentation, feature extraction and diagnosis, and segmentation significantly affects the diagnostic performance. In this paper, we propose an automatic...
Automatic or semi-automatic segmentation and tracking of artery trees from computed tomography angiography (CTA) is an important step to improve the diagnosis and treatment of artery diseases, but it still remains a significant challenging problem. In this paper, we present an artery extraction method to address the challenge. The proposed method consists of two steps: (1) a geometric moments based...
Automated image detection of white matter changes of the brain is essentially helpful in providing a quantitative measure for studying the association of white matter lesions with other types of biomedical data. Such study allows the possibility of several medical hypothesis validations which lead to therapeutic treatment and prevention. This paper presents a new clustering-based segmentation approach...
The paper describes a set of approaches and routines designed to improve results in CT based 3D subtractive angiography of lower extremities via better global locally defined image data registration. Starting from the generic concept of 3D disparity-based flexible registration, modifications of this idea are made founded on prior anatomical knowledge, as segmentation into individual bone areas, their...
In X-ray guided bronchoscopy of peripheral pulmonary lesions, airways and nodules are hardly visible in X-ray images. Transbronchial biopsy of peripheral lesions is often carried out blindly, resulting in degraded diagnostic yield. One solution of this problem is to superimpose the lesions and airways segmented from preoperative 3D CT images onto 2D X-ray images. A feature-based 2D/3D registration...
This paper presents a method to detect 128 EEG electrodes in image study and to merge with the Nuclear Magnetic Resonance volume for better diagnosis. First we propose three hypotheses to define a specific acquisition protocol in order to recognize the electrodes and to avoid distortions in the image. In the second instance we describe a method for segmenting the electrodes. Finally, registration...
Our recent adaptation to PET of the method of Fitchard et al., for rigid body registration of CT sinograms enables motion between two temporal frames of PET data to be estimated and corrected prior to reconstruction. This avoids both the computation required by multiple reconstructions and the need to make choices regarding reconstruction methods that influence the images produced, and potentially...
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