Noriyuki Tomiyama

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PURPOSE To evaluate the usefulness of a commercially available computer-aided diagnosis (CAD) system that incorporates temporal subtraction for the detection of solitary pulmonary nodules on chest radiographs by readers with different levels of experience. MATERIALS AND METHODS Sixty pairs of chest radiographs in 30 patients with newly detected solitary(More)
The paper addresses the automated segmentation of multiple organs in upper abdominal CT data. We propose a framework of multi-organ segmentation which is adaptable to any imaging conditions without using intensity information in manually traced training data. The features of the framework are as follows: (1) the organ correlation graph (OCG) is introduced,(More)
OBJECTIVE To assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D) for image quality improvement and dose reduction for chest computed tomography (CT). METHODS Institutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions(More)
OBJECTIVE The objective of this study was to determine whether the various chronic cystic lung diseases can be differentiated on the basis of the pattern and distribution of abnormalities on high-resolution CT. MATERIALS AND METHODS High-resolution CT scans in 92 patients with chronic cystic lung diseases (18 with pulmonary Langerhans cell histiocytosis,(More)
Segmentation of the femur and pelvis is a prerequisite for patient-specific planning and simulation for hip surgery. Accurate boundary determination of the femoral head and acetabulum is the primary challenge in diseased hip joints because of deformed shapes and extreme narrowness of the joint space. To overcome this difficulty, we investigated a(More)
We describe a method to capture disease-specific components in organ shapes. A statistical shape model, constructed by the principal component analysis (PCA) of organ shapes, is used to define the subspace representing inter-subject shape variability. The first PCA is applied to the datasets of healthy organ shapes to define the subspace of normal(More)
This paper addresses the automated segmentation of multiple organs in upper abdominal computed tomography (CT) data. The aim of our study is to develop methods to effectively construct the conditional priors and use their prediction power for more accurate segmentation as well as easy adaptation to various imaging conditions in CT images, as observed in(More)
SUMMARY In this paper, we present an algorithm to segment the liver in low-contrast CT images. As the first step of our algorithm, we define a search range for the liver boundary. Then, the EM algorithm is utilized to estimate parameters of a 'Gaussian Mixture' model that conforms to the intensity distribution of the liver. Using the statistical parameters(More)