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Using a PIM interface for improving computer medical image processing abilities.

ABSTRACT: BACKGROUND:Biomedical engineers in particular require fast and powerful data processing systems to process computerized tomography and magnetic resonance imaging scans and other medical imaging technologies. However, current computer data processing technologies are unable to satisfy such requirements. A promising approach to addressing these limitations is processing in memory (PIM). Unfortunately, several issues, such as the compatibility and interconnection of PIM with legacy systems, still remain. OBJECTIVE:This paper proposes a standard memory bus-based PIM interface for medical image processing and a PIM platform. The proposed PIM interface can overcome problems of compatibility with legacy systems. METHODS:We will adapt an embedded system based on a commercial application processor (AP) to a medical image system to verify the functions and the performance of the proposed PIM interface. Using the PIM platform, we apply the proposed PIM interface and the AP to execute an image processing program, measure the image processing times, and compare the results of the measurements. RESULTS:Experimental results show that while the functions of the proposed PIM interface are normal, the processing time of PIM is more than 81% faster than that of the AP. CONCLUSION:The experimental results prove that the proposed PIM interface is able to solve problems of compatibility with legacy systems. We foresee that not only the medical image processing field but also a number of academic fields and professional sectors will use PIM in their data-intensive applications.

SUBMITTER: Kim YK

PROVIDER: S-EPMC7369059 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Using a PIM interface for improving computer medical image processing abilities.

Kim Young-Kyu YK Jang Young-Jong YJ Kim Dong-Sun DS Wei Qun Q

Technology and health care : official journal of the European Society for Engineering and Medicine 20200101 S1

<h4>Background</h4>Biomedical engineers in particular require fast and powerful data processing systems to process computerized tomography and magnetic resonance imaging scans and other medical imaging technologies. However, current computer data processing technologies are unable to satisfy such requirements. A promising approach to addressing these limitations is processing in memory (PIM). Unfortunately, several issues, such as the compatibility and interconnection of PIM with legacy systems, ...[more]

PMID: 32364181

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Project description:BackgroundSafe and accurate execution of surgeries to date mainly rely on preoperative plans generated based on preoperative imaging. Frequent intraoperative interaction with such patient images during the intervention is needed, which is currently a cumbersome process given that such images are generally displayed on peripheral two-dimensional (2D) monitors and controlled through interface devices that are outside the sterile filed. This study proposes a new medical image control concept based on a Brain Computer Interface (BCI) that allows for hands-free and direct image manipulation without relying on gesture recognition methods or voice commands.MethodA software environment was designed for displaying three-dimensional (3D) patient images onto external monitors, with the functionality of hands-free image manipulation based on the user's brain signals detected by the BCI device (i.e., visually evoked signals). In a user study, ten orthopedic surgeons completed a series of standardized image manipulation tasks to navigate and locate predefined 3D points in a Computer Tomography (CT) image using the developed interface. Accuracy was assessed as the mean error between the predefined locations (ground truth) and the navigated locations by the surgeons. All surgeons rated the performance and potential intraoperative usability in a standardized survey using a five-point Likert scale (1 = strongly disagree to 5 = strongly agree).ResultsWhen using the developed interface, the mean image control error was 15.51 mm (SD: 9.57). The user's acceptance was rated with a Likert score of 4.07 (SD: 0.96) while the overall impressions of the interface was rated as 3.77 (SD: 1.02) by the users. We observed a significant correlation between the users' overall impression and the calibration score they achieved.ConclusionsThe use of the developed BCI, that allowed for a purely brain-guided medical image control, yielded promising results, and showed its potential for future intraoperative applications. The major limitation to overcome was noted as the interaction delay.

Dataset Information

Using a PIM interface for improving computer medical image processing abilities.

Publications

Using a PIM interface for improving computer medical image processing abilities.

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