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 hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Groundbreaking X-Ray Imaging Technique Could Improve Medical Diagnostics

By MedImaging International staff writers
Posted on 19 Aug 2024
Print article
Image: Overlay of retrieved X-ray differential phase (gradient) image with attenuation and phase image of a wasp from a single-shot X-ray phase imaging system (Photo courtesy of Mini Das/University of Houston)
Image: Overlay of retrieved X-ray differential phase (gradient) image with attenuation and phase image of a wasp from a single-shot X-ray phase imaging system (Photo courtesy of Mini Das/University of Houston)

Older X-ray technology depends on the absorption of X-rays to generate images, which can be challenging when differentiating materials of similar density. This often results in low contrast images, making it difficult to distinguish between different substances, posing challenges in various applications including medical imaging. X-ray phase contrast imaging (PCI), which leverages relative phase changes as X-rays pass through an object, has become increasingly popular for its ability to enhance contrast, particularly for soft tissues. The single-mask differential method is notable among various PCI techniques for its simplicity and effectiveness, offering high-contrast imaging more efficiently and with lower radiation doses. Now, researchers have introduced a novel light transport model for a single-mask phase imaging system that enhances non-destructive deep imaging for visibility of light-element materials, including soft tissues such as cancers. This groundbreaking advancement in X-ray imaging technology could significantly improve medical diagnostics.

The new light transport model developed by researchers at the University of Houston (Houston, TX, USA) significantly enhances the capability of single-mask phase imaging systems, enabling non-destructive deep imaging that improves the visibility of light-element materials, such as soft tissues in medical diagnostics. This new model, detailed in a paper featured on the cover of Optica, facilitates the understanding of how contrast forms and how different contrast features interact within the acquired images. It enables the extraction of images that incorporate two distinct types of contrast mechanisms from a single exposure, marking a major improvement over conventional methods.

The innovative design utilizes an X-ray mask with periodic slits that align with the detector pixels to enhance edge contrast and capture differential phase information, clarifying variations between materials more distinctly. This advancement simplifies the imaging setup by reducing the reliance on high-resolution detectors or elaborate, multi-shot processes. The researchers have conducted extensive simulations and tested this model on a laboratory benchtop X-ray imaging system developed in-house. Their future objectives include adapting this technology for portable systems and retrofitting existing imaging setups, with plans to implement and evaluate it in practical settings such as hospitals.

“Our research opens up new possibilities for X-ray imaging by providing a simple, effective and low-cost method for enhancing image contrast which is a critical need for non-destructive deep imaging,” said Mini Das, Moores professor at UH’s College of Natural Sciences and Mathematics and Cullen College of Engineering. “It makes phase contrast imaging more accessible and practical, leading to better diagnostics and improved security screening. It is a versatile solution for a wide range of imaging challenges. We are in the process of testing the feasibility for a number of applications.”

Related Links:
University of Houston

New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Digital X-Ray Detector Panel
Acuity G4
New
Ultrasound Scanner
TBP-5533
LED-Based X-Ray Viewer
Dixion X-View

Print article

Channels

MRI

view channel
Image: MRI microscopy of mouse and human pancreas with respective histology demonstrating ability of DTI maps to identify pre-malignant lesions (Photo courtesy of Bilreiro C, et al. Investigative Radiology, 2024)

Pioneering MRI Technique Detects Pre-Malignant Pancreatic Lesions for The First Time

Pancreatic cancer is the leading cause of cancer-related fatalities. When the disease is localized, the five-year survival rate is 44%, but once it has spread, the rate drops to around 3%.... Read more

Ultrasound

view channel
Image: A transparent ultrasound transducer-based photoacoustic-ultrasound fusion probe, along with images of a rat’s rectum and a pig’s esophagus (Photo courtesy of POSTECH)

Transparent Ultrasound Transducer for Photoacoustic and Ultrasound Endoscopy to Improve Diagnostic Accuracy

Endoscopic ultrasound is a commonly used tool in gastroenterology for cancer diagnosis; however, it provides limited contrast in soft tissues and only offers structural information, which reduces its diagnostic... Read more

General/Advanced Imaging

view channel
Image: The results of the eight-view 3D CT reconstruction from a public dataset (Photo courtesy of Medical Physics, doi.org/10.1002/mp.12345)

AI Model Reconstructs Sparse-View 3D CT Scan With Much Lower X-Ray Dose

While 3D CT scans provide detailed images of internal structures, the 1,000 to 2,000 X-rays captured from different angles during scanning can increase cancer risk, especially for vulnerable patients.... 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.