In a conventional ICG fluorescence observation system, the flow of ICG is observed using an IR camera and displayed on a monitor. However, it can be difficult to clearly understand the correspondence between the area of fluorescence on the body and that displayed on the monitor. We therefore propose a novel system that projects the area of ICG fluorescence directly onto the body surface. The system is composed of a commercially available IR camera, a laser projector, and an IR LED. The system excites the ICG by irradiation from the IR LED and detects the area of fluorescence by subtracting a non-excited image from an excited image and applying threshold processing. The subtracted image is transformed to correct distortion using a space-coding method and projected onto the body. The results of accuracy evaluation showed that the average transformation error was less than 0.5 mm. ICG fluorescence in a biological phantom could be observed to a depth of about 12 mm. The feasibility of employing this system in clinical applications was also assessed by conducting animal experiments.

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In dentistry, the milling operation is one of the most difficult tasks to master and is dependent on the surgeon's experience and tactile sensitivity. Dental education currently employs simple milling training using dental casts to help students acquire the delicate manipulative skills that are known as a "feather touch". Therefore, qualitative navigation of the milling operation is required. The objective of the present study is to develop a navigation system for dental milling training using an electrotactile display, which is a small device that provides unconstrained manipulation. For navigation of the amount of milling, the milling error from the predetermined desired surface is superimposed as artificial touch sensation. In this research, we propose a voxel-based stimulus design using the surface data of the dental cast. Assistance in the basic milling task is provided by the newly developed system. The results show that the desired milling operation could be achieved using the proposed system.

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Accurate segmentation of lesions is an essential process in CAD systems for differential diagnosis. However, segmentation of ground glass opacity (GGO) nodules, most of which are likely to be malignant, is a difficult task due to their poorly defined margins. We have developed a new segmentation algorithm for GGO nodules that enhances lesions by applying a boosting algorithm based on CT value features and extracts GGO nodules by graph cuts. Experiments to validate the proposed algorithm were conducted using data for 100 GGO nodules acquired at Kyoto University Hospital, and the Jaccard index between the extracted region and the true region was computed by a 10-fold cross-validation test. The Jaccard index of conventional graph cuts using CT data only was 40.7%, and the binarization results for lesions enhanced by a boosting algorithm showed a Jaccard index of 67.3%. In contrast, the proposed method, which combines enhancement processing with graph cuts, achieved a Jaccard index of 72.2%, which is significantly higher than the above performance indices.

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For the software used in 3-D X-ray CT such as dental CT or micro CT, it is desirable to integrate conebeam tomographic image reconstruction, volume visualization, and image measurement, but such integrated software is currently rare and expensive. As described in this report, by implementing several previously known or newly developed image processing algorithms using a GPU, we have developed software called TomoShop which integrates all of the above-mentioned functions. Furthermore, based on evaluation of its application to dental CT imaging, we have implemented specific image processing algorithms for panoramic display, nerve extraction, and distance measurement. Consequently, we have achieved the main goal of integrating the above-mentioned functions into a single software package and have realized high speed, high image quality, and high generality by adopting GPU implementation and scientifically novel image reconstruction, compensation, and processing algorithms. We have confirmed the high performance of this software by conducting various experimental studies and look forward to making it available to CT manufacturers at a reasonable price.

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This paper deals with the metal artifact problem in X-ray computed tomography (CT). If an X-ray opaque structure (metal object) is present in the region to be examined, metal streak artifacts may appear in the reconstructed image, resulting in a non-diagnostic image. In traditional analytical metal artifact reduction (MAR) methods, the part of the projection data affected by the metal object is removed from the original projection data, and the removed part is filled in by interpolation. Then, an image is reconstructed from the interpolated projection data using the filtered back-projection (FBP) algorithm. These methods can considerably reduce metal steak artifacts, but a satisfactory image still may not be reconstructed due to interpolation errors. It is known that the interpolation errors which arise during the interpolation step lead to DC-shift and shading artifacts in the reconstructed images. In the FBP-type MAR algorithm, the interpolated projection data is filtered using a non-local ramp filter before back-projection, which propagates the interpolation errors to the whole projection data. In this paper, we propose a differentiated back-projection (DBP)-type MAR method to reduce the effect of interpolation errors and consequently reduce DC-shift and shading artifacts. We expect image quality to be improved by the proposed method because the DBP reconstruction algorithm is able to apply non-local filtering after back-projection along the preferred Hilbert filter direction. This property helps to reduce the propagation of interpolation errors. A simulation study was performed to evaluate the proposed method.

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3D structure recovery techniques have intensively been studied as a fundamental technology in the computer vision research field. The application area of computer vision has also been extended into various topics, such as visual media contents creation, virtual reality interface, etc. This article focuses on the 3D structure recovery techniques. First, an overview of the technology of 3D structure recovery is given. Then, two example application topics of the 3D structure recovery are presented with the author's recent researches. One is free-viewpoint video synthesis techniques, and another is augmented reality techniques.

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