Yasuharu Mizutani

High-performance computing service over the Internet for intraoperative image processing

This paper presents a framework for a cluster system that is suited for high-resolution image processing over the Internet during surgery. The system realizes high-performance computing (HPC) assisted surgery, which allows surgeons to utilize HPC resources remote from the operating room. One application available in the system is an intraoperative estimator for the range of motion (ROM) adjustment in total hip replacement (THR) surgery. In order to perform this computation-intensive estimation during surgery, we parallelize the ROM estimator on a cluster of 64 PCs, each with two CPUs. Acceleration techniques such as dynamic load balancing and data compression methods are incorporated into the system. The system also provides a remote-access service over the Internet with a secure execution environment. We applied the system to an actual THR surgery performed at Osaka University Hospital and confirmed that it realizes intraoperative ROM estimation without degrading the resolution of images and limiting the area for estimations.

A high-performance computing service over the Internet for nonrigid image registration

Abstract This paper presents a novel high-performance computing (HPC) system for compute-intensive medical applications. Our system provides surgeons a framework for utilizing remote HPC resources with a secure execution environment by a public key cryptography and a high-speed data transmission by a real-time lossless data compression algorithm. Our implementation on a cluster of 64 off-the-shelf PCs with 128 processors has successfully demonstrated HPC benefits by reducing the turn-around time for the nonrigid registration of liver CT images of 512×512×159 voxels from about 17 h on a sequential system to about 12 min.

Grid Resource Monitoring and Selection for Rapid Turnaround Applications

In this paper, we present a resource monitoring and selection method for rapid turnaround grid applications (for example, within 10 seconds). The novelty of our method is the distributed evaluation of resources for rapidly selecting the appropriate idle resources. We integrate our method with a widely used resource management system, namely the Monitoring and Discovery System 2 (MDS2), and compare our method with the original MDS2 in terms of the performance and the scalability. The performance is measured using a 64-node cluster of PCs and the scalability is analyzed using a theoretical model and the measured performance. The experimental results show that our method reduces the resource selection time by 82%, as compared with the original MDS2. The scalability analysis also indicates that our method can keep the resource selection time within 1 second, up to 500 nodes in local-area-network (LAN) environments. In addition, some simulation results are presented to estimate the impact of our method for wide-area-network (WAN) environments.

A High Performance Computing System for Medical Imaging in the Remote Operating Room

This paper presents a novel cluster system, named MI-Cluster, for the purpose of developing a testbed for the cluster-assisted surgery. Our system provides a framework for utilizing high performance computing resources from the remote operating room. One current application is an accurate simulator for the range of motion (ROM) adjustment in total hip replacement (THR) surgery. To perform high-quality imaging during surgery, we have parallelized this compute-intensive ROM simulator on a cluster of PCs with 128 processors. Acceleration techniques such as dynamic load-balancing and data compression have been incorporated into our system. The system also provides a remote access service with a secure execution environment. We applied the system to an actual THR surgery performed at Osaka University Hospital and confirmed that the MI-Cluster system realizes intraoperative ROM simulation without degrading the accuracy of the simulation.

Verification of Stereoscopic Effect Induced Parameters of 3D Shape Monitor Using Reverse Perspective

In the field of optical illusion, reverse perspective is used to draw a scene that is opposite to the actual perspective. When the viewing position is changed, a farther object seems to be always coming toward and following the viewer instead of going away. Therefore, we considered whether the reverse perspective can be applied to a dynamic representation of computer animation using multiple combined monitors. In this research, we arranged three monitors in the shape of a corner cube and tried to determine whether the viewer can recognize the concave corner of the cube as the convex corner through the reverse perspective illusion. Furthermore, we developed a virtual environment that enabled us to simulate the reverse perspective illusion by changing the position, angle, and shape of the screen using a head-mounted display and controllers.

Generating Training Images Using a 3D City Model for Road Sign Detection

In order to prevent traffic accidents due to mistakes in checking road signs, a method for detecting road signs from an image shot by an in-vehicle camera has been developed. On the other hand, Deep Learning which is frequently used in recent years requires preparing a large amount of training data, and it is difficult to photograph road signs from various directions at various places. In this research, we propose a method for generating training images for Deep Learning using 3D urban model simulation for detecting road signs. The appearance of road signs taken in the simulation depends on the distance and direction from the camera and the brightness of the scene. These changes were applied to Japanese road signs, and 303,750 types of sign images and their mask areas were automatically generated and used for training. As a result of training YOLO detectors using these training images, in detection for some road sign class groups, the F values of 66.7% to 88.9% could be obtained.

Projection Simulator to Support Design Development of Spherical Immersive Display

This research aims to develop a simulator that supports the construction of a spherical immersive display, which is a system that can provide a realistic presence, as if the user exists in another space. In general, when developing a display, it is necessary to perform optical design of the projection system in considering special distortion correction on the dome screen. However, accuracy of the optical system that is actually manufactured is not guaranteed to be when it is simulated, and fine adjustment is again necessary when the display is used. In this research, we report on the development of a projection simulator that can perform optical system adjustment and distortion correction simultaneously during optical design of the projection system.

Minimizing data size for efficient data reuse in grid-enabled medical applications

This paper presents a data minimization method that aims at reducing overhead for data reuse in grid environments. The data reuse here is designed to promote efficient use of grid resources by avoiding multiple executions of the same computation in a collaborative community. To promote this at the program block level, our method minimizes the data size of attribute values, which are used for identification of computation products stored in a database (DB) server. Because attribute values are specified in queries used for store, search, or retrieval of computation products, their reduction leads to less communication between computing nodes and the DB server, minimizing the runtime overhead of data reuse. We also show some experimental results obtained using a time-consuming medical application. We find that the method successfully reduces the data size of a query from 683 MB to 52 B. This reduction allows our data reuse framework to reduce execution time from approximately 9 minutes to 27 seconds.