Fukai Toyofuku

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The purpose of this study was to develop a computerized method for detection of multiple sclerosis (MS) lesions in brain magnetic resonance (MR) images. We have proposed a new false positive reduction scheme, which consisted of a rule-based method, a level set method, and a support vector machine. We applied the proposed method to 49 slices selected from 6(More)
It has been reported that the severity of subcortical vascular dementia (VaD) correlated with an area ratio of white matter hyperintensity (WMH) regions to the brain parenchyma (WMH area ratio). The purpose of this study was to develop a computer-aided evaluation method of WMH regions for diagnosis of subcortical VaD based on magnetic resonance (MR) images.(More)
RATIONALE AND OBJECTIVES An automated method for identification of patients with cerebral atrophy due to Alzheimer's disease (AD) was developed based on three-dimensional (3D) T1-weighted magnetic resonance (MR) images. MATERIALS AND METHODS Our proposed method consisted of determination of atrophic image features and identification of AD patients. The(More)
Our purpose in this study was to develop an automated segmentation scheme for multiple sclerosis (MS) lesions in magnetic resonance images using an artificial neural network (ANN)-controlled level-set method. Forty-nine slices with T1-weighted, T2-weighted, and fluid-attenuated inversion recovery images were selected from six examinations of three MS(More)
PURPOSE Brain tissue segmentation based on diffusion tensor magnetic resonance imaging (DT-MRI) data has been attempted by previous researchers. Due to inherent low spatial resolution of DT-MRI data, conventional methods suffered from partial volume averaging among the different types of tissues, which may result in inaccurate segmentation results. The(More)
The purpose of this study was to develop a computer-aided method for determination of beam arrangements based on similar cases in a radiotherapy treatment-planning database for stereotactic lung radiation therapy. Similar-case-based beam arrangements were automatically determined based on the following two steps. First, the five most similar cases were(More)
Our purpose in this study was to develop an automated method for segmentation of white matter (WM) and gray matter (GM) regions with multiple sclerosis (MS) lesions in magnetic resonance (MR) images. The brain parenchymal (BP) region was derived from a histogram analysis for a T1-weighted image. The WM regions were segmented by addition of MS candidate(More)
We have proposed an automated method for three-dimensional (3D) measurement of cerebral cortical thicknesses based on fuzzy membership maps derived from magnetic resonance (MR) images for evaluation of Alzheimer's disease (AD). The cerebral cortical thickness was three-dimensionally measured on each cortical surface voxel by using a localized gradient(More)
To improve evaluations of cortical and subcortical diffusivity in neurological diseases, it is necessary to improve the accuracy of brain diffusion tensor imaging (DTI) data segmentation. The conventional partial volume segmentation method fails to classify voxels with multiple white matter (WM) fiber orientations such as fiber-crossing regions. Our purpose(More)
We have developed a computerized method for estimating patient setup errors in portal images based on localized pelvic templates for prostate cancer radiotherapy. The patient setup errors were estimated based on a template-matching technique that compared the portal image and a localized pelvic template image with a clinical target volume produced from a(More)