Physiological morphometry is a critical factor in the flow dynamics in small airways. In this study, we visualized and analyzed the three-dimensional structure of the small airways without dehydration and fixation. We...
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Physiological morphometry is a critical factor in the flow dynamics in small airways. In this study, we visualized and analyzed the three-dimensional structure of the small airways without dehydration and fixation. We developed a two-step method to visualize small airways in detail by staining the lung tissue with a radiopaque solution and then visualizing the tissue with a cone-beam microfocal X-ray computed tomographic (CT) system. To verify the applicability of this staining and CT imaging (SCT) method, we used the method to visualize small airways in excised rat lungs. By using the SCT method to obtain continuous CT images, three-dimensional branching and merging bronchi ranging from 500 to 150 mum (the airway generation = 8-16) were successfully reconstructed. The morphometry of the small airways (diameter, length, branching angle and gravity angle between the gravity direction and airway vector) was analyzed using the three-dimensional thinning algorithm. The diameter and length exponentially decreased with the airway generation. The asymmetry of the bifurcation decreased with generation and one branching angle decided the other pair branching angle. The SCT method is the first reported method that yields faithful high-resolution images of soft tissue geometry without fixation and the three-dimensional morphometry of small airways is useful for studying the biomechanical dynamics in small airways. (C) 2003 Elsevier Science Ltd. All rights reserved.
Tumor vascularity is an important factor that has been shown to correlate with tumor malignancy and was demonstrated as a prognostic indicator for a wide range of cancers. three-dimensional (3-D) power Doppler ultraso...
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Tumor vascularity is an important factor that has been shown to correlate with tumor malignancy and was demonstrated as a prognostic indicator for a wide range of cancers. three-dimensional (3-D) power Doppler ultrasound (PDUS) offers a convenient tool for investigators to inspect the signals of blood flow and vascular structures in breast cancer. In this paper, a new computer-aided diagnosis (CAD) system for quantifying Doppler ultrasound images based on 3-D thinningalgorithm and neural network is proposed. We extracted the skeleton of blood vessels from 3-D PDUS data to facilitate the capturing of morphological changes. Nine features including vessel-to-volume ratio, number of vascular trees, length of vessels, number of branching, mean of radius, number of cycles, and three tortuosity measures, were extracted from the thinning result. Benign and malignant tumors can therefore be differentiated by a score computed by a multilayered perceptron (MLP) neural network using these features as parameters. The proposed system was tested on 221 breast tumors, including 110 benign and Ill malignant lesions. The accuracy, sensitivity, specificity, and positive and negative predictive values were 88.69% (196/221), 91.89% (102/111), 85.45% (94/110), 86.44% (102/118), and 91.26% (94/103), respectively. The Az value of the ROC curve was 0.94. The results demonstrate a correlation between the morphology of blood vessels and tumor malignancy, indicating that the newly proposed method can retrieves a high accuracy in the classification of benign and malignant breast tumors.
In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method...
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In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method for the threedimensional skeletal graph generation of liver vessels using 3D thinningalgorithm and graph theory. First of all, the principal methods for skeletonization are introduced, followed by their comparative analysis. Secondly, the 3D thinning-based skeletonization method together with a filling hole pre-processing on liver vessel image are employed to form the liver skeleton. A graph-based technique is then employed on the skeleton image to efficiently form the liver vascular graph. The thinning-based liver vessel skeletonization method was evaluated on liver vessel images with other two kinds of skeletonization approaches to show its effectiveness and efficiency.
In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method...
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In the clinical practice of diagnosis and treatment of liver disease, how to effectively represent and analyze the vascular structure has been a widely studied topic for a long time. In this paper, we propose a method for the three- dimensional skeletal graph generation of liver vessels using 3D thinningalgorithm and graph theory. First of all, the principal methods for skeletonization are introduced, followed by their comparative analysis. Secondly, the 3D thinning-based skeletonization method together with a filling hole pre-processing on liver vessel image are employed to form the liver skeleton. A graph-based technique is then employed on the skeleton image to efficiently form the liver vascular graph. The thinning-based liver vessel skeletonization method was evaluated on liver vessel images with other two kinds of skeletonization approaches to show its effectiveness and efficiency.
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