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At Cornell

Tackling the Lung Cancer Problem

Anthony Reeves and students

Cornell Engineers and Physicians at the Leading Edge in CT Screening

Birth of a Collaboration
Lung illustration


A fortuitous meeting between two research groups, the Early Lung Cancer Action Program (ELCAP) at the Weill Cornell Medical College (WCMC) in New York City and the Computer Vision and Image Analysis group (VIA) in the College of Engineering on the Ithaca campus, occurred in February 1997. The ELCAP project, led by Claudia I. Henschke and David F. Yankelevitz, Radiology, WCMC, began in 1993 to conduct studies on lung cancer screening using computer tomography (CT) scans. Henschke and Yankelevitz realized that there was an opportunity for computer analysis methods to play a role in lung cancer screening. In pursuing this idea, they made an initial contact with the Department of Computer Science in Ithaca to identify an appropriate connection. A follow-up visit was planned at WCMC. Through informal discussions, the VIA group in the School of Electrical and Computer Engineering was invited to attend a meeting at which presentations to identify mutual interests were to be made.

I had led the VIA group with a research program in computer vision and high-speed computer architectures since joining the Cornell faculty in 1982. At that time, we had developed a number of techniques that were suitable for analyzing three-dimensional images. These are exactly the type of images that are produced by CT scanners as opposed to the conventional two-dimensional images that we perceive with the retinas of our eyes or that are represented by photographs or television. Without a medical imaging connection, however, there had been no applications to which these techniques could be applied, and this research had remained dormant for 13 years.

The main outcome of the 1997 meeting at WCMC was the identification of a strong synergistic opportunity between the ELCAP and VIA groups that has resulted in an enduring collaboration. Our three-dimensional image analysis techniques could be applied to the lung CT images obtained by the ELCAPAP study to aid in the early diagnosis of lung cancer.


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