51视频

Heart disease is the leading cause of death for men and women in America, according to the .

One person dies every 34 seconds in the United States from cardiovascular disease, the CDC reports, and this costs the country about $229 billion each year in health care services, medicines and lost productivity due to disability or death.

A team of researchers from 51视频, Rensselaer Polytechnic Institute and Vanderbilt University Medical Center led by UML Electrical and Computer Engineering Prof. Hengyong Yu is developing technology that would greatly improve , which doctors currently use to diagnose cardiovascular diseases, so that timely, life-saving treatment and preventive measures can be implemented.聽

Aside from Yu, other key investigators include Electrical and Computer Engineering Prof. Yan Luo (UML), Prof. Ge Wang (RPI) and Prof. J. Jeffrey Carr (VUMC).聽

The project is supported by a four-year grant worth more than $2.4 million from the National Institutes of Health鈥檚 .

A cardiac CT scan, or coronary CT angiography, is an imaging procedure widely used in hospitals that uses powerful X-ray beams to produce highly detailed images of the heart and its blood vessels. Physicians use them to check for narrowed or blocked arteries and other serious heart conditions. The biggest drawback with this imaging technique is that the movement of the beating heart can result in blurry images.聽

Yu and his co-investigators are developing a new image-reconstruction algorithm based on artificial intelligence (AI) that would effectively 鈥渇reeze鈥� the beating heart in CT images within a brief, 60-millisecond time window (one twentieth of a heartbeat).

鈥淭his would eliminate the blurring movement of the coronary arteries in X-ray images and help doctors analyze plaque buildup on the walls of the arteries, which is the main cause of heart attacks,鈥� Yu says.聽

鈥淢oreover, our method will not require patients to hold their breath during the CT exam and will eliminate the need to use beta-blocker drugs to slow down the patients鈥� heart rates,鈥� he says.

According to Yu, the team鈥檚 AI-based computational framework would radically improve the image quality of existing CT scanners and would benefit patients who suffer from tachycardia (rapid heartbeat) and arrhythmia (irregular heartbeat) that commonly occur in older adults, many of whom experience atrial fibrillation (rapid, irregular heart rhythm).

鈥淥ur project will combine two innovative image-processing algorithms 鈥� compressed sensing and deep learning 鈥� to reconstruct cardiac CT images at very high resolution and with lower radiation exposure to patients compared to traditional CT scans,鈥� Yu notes.聽

He says their technique could allow them to help build powerful, low-cost cardiac CT scanners, and possibly retrofit older models to perform cardiac CT exams.聽

鈥淥ur algorithm could dramatically expand the capability of these systems, allowing higher-quality cardiac CT scans in many underprivileged communities worldwide.鈥澛�

Assisting Yu in the lab research is Yongshun Xu, a fourth-year electrical engineering doctorate student.

鈥淚鈥檓 actively recruiting more postdocs and graduate students,鈥� says Yu. 鈥淚 hope to get two postdocs and two Ph.D. students to join the project this fall.鈥�