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Independent component analysis (ICA) is widely used for signal separation in various fields. However, low signal to noise ratio (SNR) of data sometimes causes failures in component estimation. We have proposed a spatial ICA-based method for extracting a blood-related component from medical images measured with positron emission tomography (PET) to omit arterial blood sampling, in which a cost function was designed in consideration of statistical properties of components. In this study, spatial ICA with the proposed cost function or kurtosis, a conventional cost function, was applied to real PET images measured with three kinds of radiopharmaceuticals, and the estimation results were compared. The proposed cost function fails to estimate components from the PET data with low SNR because it is sensitive to outliers. Experimental results suggest that a cost function should be selected depending on SNR of data.

In this study, maximize a posterior approach (MAP) was applied for detailed imaging of the glucose metabolism in the brain using PET and 18 F-FDG. FDG is a glucose analog and it can investigate a glucose metabolism. In PET studies, glucose metabolism can be measured to estimate a compartment model which describes the behavior of glucose in the brain. We applied the MAP approach to a voxel-by-voxel compartment model estimation in order to visualize a net amount of glucose, glucose transportation, and glucose phosphorylation because a MAP approach is advantageous for robust model estimation against noise existence. When the algorithm was applied to Alzheimer patients, the images had different patterns depending on severity of the disease. We conclude that the proposed MAP-based algorithm is useful for detail imaging of glucose metabolism in the brain.

Three-dimensional (3D) visualization or 3D monitoring of patients or infected animals is useful in actual clinical environment. We propose a 3D imaging system with a single camera and multiple mirrors. The camera is located directly above the object and the multiple mirrors are placed surrounding the object. The single captured image includes multiple viewpoint images: the object captured directly and the same objects reflected by the mirrors. After a simple calibration of the measurement, the 3D volume data are reconstructed with the visual hull based method. Texture mapping is also performed to enhance the reality. A living object was observed in usual environment using this system. The results have demonstrated effectiveness of the system.