Background

Lung cancer remains the number one killer in all cancer-related deaths in the United States. Virtual biopsy on detected lung nodules has been challenging due to the high prevalence of lung cancer and the difficulty of differentiating nodules. Computer-assisted detection of the nodules is also challenging because of the large volume of data that must be read by radiologists. This invention provides a way to differentiate nodules while also addressing the issues with computer-assisted detection.

Technology

Researchers at Stony Brook University have been using computer-aided detection (CADe) and computer-aided diagnosis (CADx) to increase the efficiency of Computed Tomography (CT) lung scanning. CADe can be used to improve Radiologists? efficiency in image interpretation. CADe will ultimately advance CT scanning toward a fully screening modality for detection of nodule presence, differentiation of nodule types, and optimal management of nodule treatment or management. Implementing these two techniques for CT lung scanning will greatly increase its efficiency for the purpose of preventing lung cancer.

Advantages

Will advance CT lung scanning toward a fully screening modality with the capability to perform the automated detection of the presence of nodules and the differentiation of nodule types for nodule management for adequate, cost-effective treatment.

Application

Improve the efficiency of CT lung scanning for the purpose of preventing lung cancer.