The project aimed to improve the ability to evaluate the performance of a gastroenterologist performing a
colonoscopy exam. Software was developed to provide a real-time feedback as well as an after-exam report.
Due to a relatively high technical difficulty of operating the endoscope during a colonoscopy exam
(complicated, unintuitive interface) the success of the procedure is largely dependent on the skills of the
doctor. Further, almost no quantitative, universal ways of measuring these skills exist, besides examining the
The project aimed to use only the camera feed in order to objectively and quantitatively evaluate doctor’s
performance and output it in real-time for the doctor, as well as provide a report that can then be used to
asses doctor’s performance and improvement over time and gather data about how the quality of the examination
correlates with detected and missed cancers.
C++, OpenCV, Optical Flow
The software used classical computer vision techniques to asses multiple ways of measuring the quality of the
examination. Clarity of the image, how well the patient has been prepared and so on. The most challenging part
was a map that was going to approximate directly doctor’s technique in operating the endoscope.
One frame of Optical Flow in backwards motion
For that optical flow was used to calculate the distance traveled by the endoscope in patient’s body and a map
was outputted real time that approximated the examined parts of the colon.
The real-time map of visited areas of the colon
My contribution as a Research Assistant
I combined together previous work conducted by other Research Assistants and used optical flow to calculate
the distance traveled by the camera inside patient’s body. I worked closely with a gastroenterologist and
performed a live demo with him during an actual exam.