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Content Based Image Retrieval (CBIR) systems that search similar images in a large database are attracting more and more research interests recently, and have been applied to medical image characterization for expert's experience sharing. One challenging task in CBIR is how to extract features for effective image representation. Therein sparse coding technique has been proven to be an effective way...
Computer-aided diagnosis (CAD) systems have been verified to have the potential to assist radiologists in clinical diagnosis to detect and characterize focal liver lesions (FLLs) based on single- or multiphase contrast-enhanced computed tomography (CT) images. Features extracted from multiphase contrast-enhanced CT images carry more important diagnostic information i.e. enhancement pattern and demonstrate...
Content-based image retrieval (CBIR) technique for digital image searching has been applied in medical images which are called content-based medical image retrieval (CBMIR). In this paper, we combine texture, density and shape features for CBMIR based on 3D multi-phase contrast enhanced CT images according to radiologists' clinical experience. And a database of 132 focal liver lesions (FLLs) with...
Locoregional therapy (LT) is a popular method to cure hepatocellular carcinoma (HCC) of liver in the last few years. Evaluating the treated margin is a critical factor for predicting local recurrence after locoregional treatment is done. In this paper, we proposed a non-rigid registration method with constraint of anatomic landmarks for assessing treated margin of locoregional therapy. Compared with...
Recently a growing interest has been seen in minimally invasive treatments with open configuration magnetic resonance (Open-MR) scanners. Because of the lower magnetic field (0.5T) and various different surgical conditions, sometimes tumors can not be visualized clearly on Open-MR volumes. Combining of CT volumes acquired before surgery, it is possible to identify the tumor's location by application...
Automatic tumor detection and segmentation is essential for the computer-aided diagnosis of live tumors in CT images. However, it is a challenging task in low-contrast images as the low-level images are too weak to detect. In this paper, we propose a new method for the automatic detection of liver tumors. We first adaptively enhance the intensity contrast of CT images by probability density function...
Successful liver surgery requires a clear understanding of the differences in liver shapes and vessel distribution in different individuals. Furthermore, in clinical medicine, there is a high demand for surgical assistance systems for individual patients. Therefore, we aim to segment the liver on the basis of the CT volume data, semi-automatically extract the vessels from the segmented livers and...
Catheterization is the treatment insert tube which name is catheter from thigh's or wrist's artery and discharge fluid, give medicine to affected area directly etc. Recently this treatment is commonly performed because make only a small hole to the patient body thus patient bears little risks. At the catheterization, expert surgeon's experience and knowledge are needed for making optimal shape of...
Two major cross-sectional imaging modalities used in the medical field for the diagnosis of abdominal conditions are X-ray computed tomography and Magnetic resonance imaging. Dramatic technological advances have been achieved in the both imaging modalities in recent years, it has become possible to obtain images with quite high spatial, temporal and contrast resolution. In this article, recent development...
In this paper, we report our current progress results on computer assisted diagnostic (CAD) system, which consists of three units: database unit (statistical atlas of human anatomy), image processing unit (image enhancement, image segmentation, image registration), and visualization unit (volume rendering). In the database unit, we proposed a new method called generalized N-dimensional principal component...
In this paper, we propose a new method to detect liver tumors in CT images automatically. The proposed method is composed of two steps. In the first step, tumor candidates are extracted by EM/MPM algorithm; which is used to cluster liver tissue. To cluster a dataset, EM/MPM algorithm exploits both intensity of voxels and labels of the neighboring voxels. It increases the accuracy of detection, with...
Segmentation of liver in CT images is regarded as a challenge in image processing due to low-contrast of datasets, variety of liver shape, and its non-uniform texture; especially for abnormal cases. In this paper, we deal with normal and abnormal datasets as images containing two or more Gaussian components. We threshold a slice in a narrow band of each mode, find liver pixels based on a priori knowledge,...
Recently a growing interest has been seen in minimally invasive treatments with open configuration magnetic resonance (Open-MR) scanners. In this paper, we proposed a semi-automatic non-rigid 3D MR-CT image registration technique for MR-Guided Liver Cancer Surgery in which cancer tissues are coagulated by microwave ablation. Because of the lower magnetic field (0.5 T) and various different surgical...
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