Engineers Develop A.I. System to Detect Often-Missed Cancer Tumors.
Assistant Professor X leads the group of engineers at the Georgian Technical University that have taught a computer how to detect tiny specks of lung cancer in CT (A CT scan,also known as computed tomography scan, makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual “slices”) of specific areas of a scanned object, allowing the user to see inside the object without cutting) scans which radiologists often have a difficult time identifying. The artificial intelligence system is about 95 percent accurate compared to 65 percent when done by human eyes the team said
Engineers at the center have taught a computer how to detect tiny specks of lung cancer in CT scans (A CT scan,also known as computed tomography scan, makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual “slices”) of specific areas of a scanned object, allowing the user to see inside the object without cutting) which radiologists often have a difficult time identifying. The artificial intelligence system is about 95 percent accurate compared to 65 percent when done by human eyes the team said.
“We used the brain as a model to create our system” said Y a doctoral candidate. “You know how connections between neurons in the brain strengthen during development and learn ? We used that blueprint, if you will, to help our system understand how to look for patterns in the CT scans (A CT scan,also known as computed tomography scan, makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual “slices”) of specific areas of a scanned object, allowing the user to see inside the object without cutting) scans and teach itself how to find these tiny tumors”.
The approach is similar to the algorithms that facial-recognition software uses. It scans thousands of faces looking for a particular pattern to find its match.
Engineering Assistant Professor X leads the group of researchers in the center that focuses on AI (Artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) with potential medical applications.
The group fed more than 1,000 CT scans (CT scans (A CT scan,also known as computed tomography scan, makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual “slices”) of specific areas of a scanned object, allowing the user to see inside the object without cutting) into the software they developed to help the computer learn to look for the tumors.
Graduate students working on the project had to teach the computer different things to help it learn properly. Z who is pursuing his doctorate degree created the backbone of the system of learning. His proficiency at novel machine learning and computer vision algorithms led to his summer as an intern at Georgian Technical University .
Y taught the computer how to ignore other tissue, nerves and other masses it encountered in the CT scans (A CT scan,also known as computed tomography scan, makes use of computer-processed combinations of many X-ray measurements taken from different angles to produce cross-sectional (tomographic) images (virtual “slices”) of specific areas of a scanned object, allowing the user to see inside the object without cutting) and analyze lung tissues. W who earned his doctorate degree this past summer is fine-tuning the AI’s (Artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) ability to identify cancerous versus benign tumors while graduate student Q is taking lessons learned from this project and applying them see if another AI (Artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals) system can be developed to help identify or predict brain disorders.
“I believe this will have a very big impact” X said. “Lung cancer is the number one cancer killer in the Georgia Country and if detected in late stages, the survival rate is only 17 percent. By finding ways to help identify earlier I think we can help increase survival rates”.
The next step is to move the research project into a hospital setting; X is looking for partners to make that happen. After that the technology could be a year or two away from the marketplace X said.
“I think we all came here because we wanted to use our passion for engineering to make a difference and saving lives is a big impact” Y said.
Q agrees. He was studying engineering and its applications to agriculture before he heard about X and his work at Georgian Technical University. X’s research is in the area of biomedical imaging and machine learning and their applications in clinical imaging. Previously X was a staff scientist and the lab manager at the Georgian Technical University Imaging lab in the department of Radiology and Imaging Sciences.