The Moffitt Cancer Center and the University of South Florida, both in Tampa, have collaborated with researchers in China, the United Kingdom, the Netherlands, and Germany to develop a new computational method to assess lung cancer tumors using CT, PET, or MRI diagnostic technologies. The method, called single click ensemble segmentation (SCES), uses a new computer algorithm they developed to help segment and extract features of a tumor. This new approach not only improves diagnosis and prognosis assessments, but also saves time and health care dollars.
Tumor segmentation had been difficult because of the diverse composition of cancer lesions when compared to normal tissues. The new segmentation method marks a great improvement over a previously used manual method, said the researchers.
Their development of SCES offers a highly automatic, accurate, and reproducible lung tumor delineation algorithm, which requires less time and effort. According to the researchers, the measurement can be used to determine if the tumor is increasing or decreasing in size, as well as describe features such as shape and texture.
The capabilities of the new algorithm were successfully tested on a large patient tumor imaging data set.
