Seminar: Anti-Correlated Noise Reduction in Triple-Energy Photon-Counting Angiography
- Date
- February 09, 2024
- Time
- 12:00 PM EST - 1:30 PM EST
- Location
- KHE 225
- Open To
- Students, Faculty, Adjunct Faculty, Staff and Post-Doctoral Fellows
Student: Kaitlyn Sims
Supervisor: Dr. Jesse Tanguay
Abstract
Interventional radiology (IR) provides real-time X-ray imaging to doctors during a variety of procedures and has been increasingly utilized due to advances in technology. IR can be employed for various organs or vessels; it is commonly used for procedures involving the cardiovascular system. One of the leading causes of death globally is cardiovascular disease, with one of the most common types being coronary artery disease (CAD). When a patient is suspected of having CAD, they will undergo a coronary angiogram, which is an IR procedure using twodimensional X-ray-based imaging, and a contrast agent is used to acquire high-quality images. Within the chest, there are sources of anatomic noise, such as bone and soft tissue, which can impact visualization. Through the subtraction of anatomic noise, there is the potential to improve visualization. Currently, the subtraction-based methods used to remove anatomic noise from an Xray image are digital subtraction angiography and kV-switching dual-energy angiography. However, these techniques are not used on coronary arteries due to motion artifacts and tube loading demands, respectively. Single-exposure photon-counting angiography has also been proposed, utilizing the photon-counter X-ray detector's ability to estimate the energy distribution of photons. However, all these techniques can only subtract one source of anatomic noise. Using a photon-counting X-ray detector with three energy bins will allow for the subtraction of two sources of anatomic noise, thereby increasing visualization. Previous studies on dual-energy imaging have shown an increase in quantum noise with multi-energy images, as such, an anticorrelated noise reduction algorithm was designed. The purpose of this project is to extend anticorrelated noise reduction to triple-energy photon-counting angiography and optimize using the detectability index.