We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

CANON

Canon U.S.A., Inc. provides digital imaging solutions for the healthcare sector, including digital detectors, digital... read more Featured Products: More products

Download Mobile App




Canon Medical Systems Initiates Collaborative Research On AI in MR Imaging

By MedImaging International staff writers
Posted on 05 Apr 2018
Print article
Canon Medical Systems Corporation (Otawara, Tochigi Prefecture, Japan), along with Kumamoto University (Kumamoto Prefecture, Kurokami, Japan) and the University of Bordeaux (Bordeaux, Nouvelle-Aquitaine, France), has initiated collaborative research on the application of Deep Learning Reconstruction (DLR), an Artificial Intelligence (AI)-based technology in magnetic resonance (MR) imaging.

DLR is a reconstruction technology that utilizes deep learning technology to eliminate noise from images. The technology analyzes the relationship between noisy and less noisy images using a computer-generated model, making it possible to eliminate noise from newly acquired images. DLR is capable of acquiring high-resolution images, as well as allowing ultra-high-resolution images to be acquired more quickly in comparison to conventional imaging methods. As a result, the potential applications of this ultra-high-resolution imaging technology in the clinical setting have been attracting significant interest.

Additionally, in comparison to a standard smoothing filter, the noise elimination method employed in DLR causes only a slight reduction in image quality, and signal variation in organ parenchyma is minimized. This improves the image quality and helps to increase accuracy in quantitative analysis, which is easily affected by noise. Hence, DLR is considered as a major technological advance that can dramatically change how MRI examinations will be performed in the future. The combination of the latest AI technology with next-generation MRI scanners is expected to be useful in eliminating noise and improving image quality, as well as in a wide variety of MR-related fields.

“DLR has the potential to transform the conventional concept of MR imaging and is expected to allow the acquisition of super-high-resolution images in a shorter time and contribute to more accurate quantitative analysis,” said Professor Yasuyuki Yamashita of the Department of Diagnostic Radiology, Faculty of Life Science, Kumamoto University.

“When DLR is used in combination, the ultra-high-resolution images acquired using the latest 3-T MRI system from Canon Medical Systems (installed last November) are comparable to images acquired using a 7-T MRI system. This suggests that DLR may be able to take the place of some high-field conventional MRI studies,” added Professor Vincent Dousset, Institut de Bio-Imagerie Université de Bordeaux, Chef de Service Neuro-Imagerie CHU de Bordeaux.

“We are very proud to have started this cutting-edge collaborative research which will lead to the development of next-generation MRI technology at leading medical institutions both in and outside Japan. We anticipate that this research will prove to be of great value by providing higher-resolution images for clinical diagnosis,” said President Takiguchi of Canon Medical Systems Corporation.

Gold Member
Solid State Kv/Dose Multi-Sensor
AGMS-DM+
Under Table Shield
3 Section Double Pivot Under Table Shield
New
Ultrasound Table
Ergonomic Advantage (EA) Line
Computed Tomography (CT) Scanner
Aquilion Serve SP

Print article
Radcal

Channels

MRI

view channel
Image: Shorter scan to diagnose prostate cancer can increase availability and reduce cost (Photo courtesy of 123RF)

Two-Part MRI Scan Detects Prostate Cancer More Quickly without Compromising Diagnostic Quality

Prostate cancer ranks as the most prevalent cancer among men. Over the last decade, the introduction of MRI scans has significantly transformed the diagnosis process, marking the most substantial advancement... Read more

Nuclear Medicine

view channel
Image: The radiotheranostic platform employs a MUC16-targeting humanized antibody, huAR9.6 (Photo courtesy of MSK)

New Radiotheranostic System Detects and Treats Ovarian Cancer Noninvasively

Ovarian cancer is the most lethal gynecological cancer, with less than a 30% five-year survival rate for those diagnosed in late stages. Despite surgery and platinum-based chemotherapy being the standard... Read more

General/Advanced Imaging

view channel
Image: The Tyche machine-learning model could help capture crucial information. (Photo courtesy of 123RF)

New AI Method Captures Uncertainty in Medical Images

In the field of biomedicine, segmentation is the process of annotating pixels from an important structure in medical images, such as organs or cells. Artificial Intelligence (AI) models are utilized to... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.