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This work presents a low-cost microcontrolled dosimeter based on CD4007 device, a popular off-the-shelf CMOS circuit. This dosimeter is aimed at in vivo radiotherapy applications and combines a simple and accurate readout with a small size, low-cost, and cable-free sensor. The response of this dosimeter to low-dose (10 cGy–1 Gy) and 40 Gy irradiations were tested using X-ray (6 MV).
This paper analyzes the performance of ensemble tree learning techniques for predicting the progression of Alzheimer's disease (AD) in a longitudinal dataset of 128 mild-cognitive impairment (MCI) subjects from the Alzheimer's disease Neuroimage Initiative (ADNI). The system is evaluated by means of tissue-segmented T1 magnetic resonance images (MRI) as well as Mini Mental State Examination (MMSE)...
This paper shows a machine learning approach based on Principal Component Analysis (PCA) and Support Vector Machine (SVM) to compare the diagnostic accuracy on very early Alzheimer's Disease (AD) patients with 18F FDG and Pittsburg Compound B (PiB) PET imaging. The Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset is used for testing, making use of the longitudinal character. Mild Cognitive...
This paper shows a new computer aided diagnosis (CAD) technique for the early Alzheimer's disease (AD) based on single photon emission computed tomography (SPECT) image feature selection and a statistical learning theory (SLT) classifier. Conventional evaluation of SPECT is time consuming, subjective and prone to error because images often rely on manual reorientation, visual reading of tomographic...
This paper presents a new method for automatic selection of Regions of Interest (ROIs) of functional brain images based on a Gaussian Mixture Model (GMM). This method allows avoiding the so-called small sample size problem in the construction of a CAD system that performs the automatic diagnosis of Alzheimers disease (AD). First we generate an image that holds the differences between normal and AD...
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