Medical doctors identify benign or malignant colon polyps by their size and shape. Since this identification is related to whether or not resection surgery is necessary, a technology for estimating absolute size and shape from endoscopic images is required. In previous research, the method for recovering the size and shape of polyps using a blood vessel region as a reference object has been proposed. This paper proposes a method to recover the size and shape of polyps by using a cylindrical endoscopic hood as a reference object. The experimental results confirm that the proposed method can estimate reflectance factor without using blood vessel information.

The presence or absence of cancer metastasis in the lymph-nodes using an AI-based approach has been important these days in the medical field of gastroenterological surgery. The medical field needs the introduction of machine learning to help the knowledge and skill of surgery of medical doctors who are taking operations by checking CT scans or MRI images for cancer disease. Recent machine learning based researches on lymph-node are mainly either detection of the location of lymph-nodes or classification of cancer metastasis. This paper proposes a method to perform both tasks at the same time with a single U-Net model. Obtained results in the experiments show that the classification accuracy is further improved compared with the previous approach while keeping the detection ratio as almost the same level as that of the related paper.

It is important to estimate the size and shape of the polyp from endoscope images in the medical diagnosis. Ref.[1] was proposed as a method to estimate the absolute size of the polyp, where movement of endoscope in depth direction was estimated from two endoscope images. Ref.[1] introduced template matching using blood vessel to determine the correspondence between two images. However, it is not appropriate for actual endoscope environment since actual motion includes not only the camera transition but also the camera rotation. Further object motion is non-rigid motion and it is difficult to determine correct correspondence points between two images. So, this paper proposes a new approach to extract a blood vessel structure based on the blood vessel region using a graph structure, where the graph is matched between two images. Here, a matching method of blood vessels is described, where camera rotation and non-rigid motion of the target object are under consideration. Effectiveness of the proposed approach is confirmed in the experiments.

The experience to see oneself from behind in real-time, that is like out-of-body experience, is refreshing, it is also expected as a trigger to improve oneself. However selfie-stick, drone, or something is necessary to take a bird's-eye view. We propose the method to make virtual self bird's-eye view using an omnidirectional camera on an HMD.

Cytology is one of the decisive factors for the early detection of cancer. It is necessary to have a certain number of years of experience to be able to screen tumor cells for cytodiagnosis. However, this diagnosis has poor objectivity because there are so many parts that the judge’s experience and skill is responsible for. In this paper, we present a new method to extract cell nuclei from HE stained images generally used cell staining for Creation of digitized objective indicators in cytology. Our method extracts cell nuclei using combining the input image and the image previously prepared by SVM. Features used in SVM are automatically generated from CNN. Results are demonstrated by experiments using the real images and its ground truths.

A new approach to recover 3-D shape from a Scanning Electron Microscope (SEM) image is described. With an ideal SEM image, 3-D shape can be recovered using the Fast Marching Method (FMM) applied to the Eikonal equation. However, when the light source direction is oblique, the correct shape cannot be obtained by the usual one-pass FMM. The new approach modifies the intensities in the original SEM image using an additional SEM image of a sphere and Neural Network (NN) training. Image modification is a two degree-of-freedom (DOF) rotation. No assumption is made about the specific functional form for intensity in an SEM image. The correct 3-D shape can be obtained using the FMM and NN learning, without iteration. The approach is demonstrated through computer simulation and validated through real experiment.

In this study, the authors forecast students’ future academic records using past attendance recording data and grade data. We use a Bayesian network as forecasting method. During construction of the Bayesian network forecasting model, unnecessary variables become noise and so lower the forecasting accuracy. Therefore, to improve the forecasting accuracy, we used information gain to reduce the number of variables in the model. As a result, accuracy improved.

The objective of this study is to utilize students' data to forecast their future grades, and to identify the students who would benefit from educational counseling. To achieve these purposes, we propose a Bayesian network model as a forecasting method. A Bayesian network is a graphical model that presents the dependence relationship among some variables in a graph structure. By calculating the probability value using the model, it is possible to make forecasts. Moreover, in this study, to facilitate the construction of a Bayesian network model, data mining is introduced.

Data glove is widely used interface device which measures hand posture (finger joint angles) and inputs it into a computer in virtual reality field. But it dose not spread throughout home because of expensive interface. On the other hand, researches to recognize a hand posture from photo/video images are performed, which are a kind of hand posture measurement system and called Vision Based Data Glove (VBDG) in recent years. In this paper, we propose a new VBDG system. It estimates hand motion using detected fingertip positions with monocular camera and inverse kinematics. However it cannot estimate hand motion when a fingertip is undetectable with self-occlusion. So our system estimates hidden finger motion, then estimates hand motion. Our experimental results show that the proposed method can estimate it with sufficient accuracy in real-time. Since camera base system is inexpensive, it fits personal use.

One of our main goal is to provide a VR chemical laboratory system as a VR-learning system for the people, i.e., who have to stay in the hospital. Therefore we have already proposed an interactive model of virtual liquid like water which focus on user impression and real-time processing rather than exact behavior simulation. However free fall water was simulated and rendered with particles simply. In this paper, we propose an efficient and effective method of free fall water with key particles instead of conventional particles. The envelope surface is rendered around the key particles as a surface of the water.

The touchable online shopping system we propose enables users can touch a virtual commodity with their own hands. One purpose of our proposal is to evaluate whether it is easy to measure the size and weight of the commodity intuitively only with small-scale size and low-price elements. Another is to make a general-purpose system only with them for general applications. With such virtual reality, we used a data-glove with vibrators and a simple force feedback device to cover any impressions such as interface interference during use. We evaluated whether users can measure the size and weight of a virtual commodity. Using this system, we found that users could measure them similar to the use of real ones.

Describes a method to realize the interactive manipulation of a virtual liquid using virtual vessels which are expressed by a general convex-shape polyhedron. We propose a liquid manipulation model which has some functions to treat the relation between the volume of liquid in a vessel and the height level of the liquid surface in it while it is being tilted. For a general-shape vessel, a lookup table is implemented to calculate the above functions. Our system with this proposed model makes it possible to catch the liquid using the virtual vessel, to hold the liquid in it, then to spill the liquid by tilting it. Also, the system realizes a manipulation method to skim the liquid from another liquid vessel.