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

Download Mobile App




Events

ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.
30 Jan 2023 - 02 Feb 2023

Artificial Intelligence Technology Produces CT Images Based on MRI Without Exposure to Radiation

By MedImaging International staff writers
Posted on 11 Nov 2021
Print article
Illustration
Illustration

Researchers have developed an artificial intelligence (AI) technology to generate CT images based on MRI images without exposure to radiation.

The results of a simulation experiment conducted by researchers at the Korea Institute of Science and Technology (KIST; Seoul, South Korea) have shown that the transcranial focused ultrasound procedure could be performed with MRI alone. Transcranial focused ultrasound can be used to treat degenerative movement disorders, intractable pain, and mental disorders by delivering ultrasound energy to a specific area of the brain without opening the skull. This treatment must be performed with an image-based technology that can locate the brain lesions.

Doctors typically use CT to obtain information about a patient's skull that is difficult to identify with MRI alone and to accurately focus the ultrasound on the lesions through the skull. However, there have been concerns about the safety of CT scans, during which radiation exposure is inevitable, especially in pediatric and pregnant patients. Efforts have been made to obtain cranial information from MRI images, but special coils for the MRI or imaging protocols that are not widely available in the medical field are required. As an alternative, interest for acquiring AI-based CT images has been high worldwide, but their clinical efficacy has not been proven.

The KIST research team proved that CT images obtained by AI have clinical utility. The researchers developed a three-dimensional conditional adversarial generative network that learns the nonlinear CT transformation process from T1-weighted MRI images, which is one of the most commonly used images in the medical field. The team devised a loss function that minimizes the Hounsfield unit pixel variation error of the CT images, and also optimized the neural network performance by comparing the changes in quality of the synthetic CT images according to the normalization methods of MRI image signals, such as Z-score normalization and partial linear histogram matching normalization.

For safe and effective ultrasound treatment, it is imperative to understand each patient's skull density ratio and skull thickness in advance, and when these skull factors were obtained via the synthetic CT, both factors showed >0.90 correlation with the actual CT. There was no statistically significant difference. Moreover, when simulated ultrasound treatment was performed, the ultrasound focal distance had an error of less than 1 mm, the intracranial peak acoustic pressure had an error of approximately 3.1%, and the focal volume similarity was approximately 83%. This demonstrated that the transcranial focused ultrasound treatment system can be performed with only the MRI image.

"Patients can receive focused ultrasound treatment without being worried about radiation exposure, and as the additional imaging and alignment processes can be omitted, this will reduce the staff's workload, leading to a reduction in time and economic costs," said Dr. Hyungmin Kim at KIST’s Bionics Research Center. "Through follow-up studies on identifying the error associated with the ultrasound parameters and transducers and understanding the possibility of artificial intelligence CT application in various parts of the body, we plan to continue developing the technology for its applicability in various treatment technologies."

Related Links:
Korea Institute of Science and Technology 


Print article
CIRS -  MIRION
Radcal

Channels

MRI

view channel
Image: Hyperpolarized MRI technology reveals changes in heart muscle’s sugar metabolism after heart attack (Photo courtesy of ETH Zurich)

MRI Technology to Visualize Metabolic Processes in Real Time Could Improve Heart Disease Diagnosis

Magnetic resonance imaging (MRI) has become an indispensable part of medicine. It allows unique insights into the body and diagnosis of various diseases. However, current MRI technology has its limitations:... Read more

Ultrasound

view channel
Image: A combination of ultrasound and nanobubbles allows cancerous tumors to be destroyed without surgery (Photo courtesy of Tel Aviv University)

Ultrasound Combined With Nanobubbles Enables Removal of Tumors Without Surgery

The prevalent method of cancer treatment is surgical removal of the tumor, in combination with complementary treatments such as chemotherapy and immunotherapy. Therapeutic ultrasound to destroy the cancerous... 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 © 2000-2022 Globetech Media. All rights reserved.