
Andinet Enquobahrie is a Technical Leader at Kitware. Andinet is responsible for technical contribution and management of image guided intervention and surgical simulation projects. His recent efforts are focused on use of PET-CT imaging to improve the clinical effectiveness of lesion biopsy, laparoscopic surgical procedures and tools for image-guided intervention application development and bioinformatics analysis. He is one of the main developers of the Image Guided Surgery Application (IGSTK) toolkit, a cross platform, open-source C++ software library that provides basic components needed to prototype image-guided surgery applications.
Dr. Enquobahrie received his Ph.D. in Electrical and Computer Engineering from Cornell University. While at Cornell, as a member of the Vision and Image Analysis (VIA) Group, he worked in the algorithm development of computer aided diagnosis applications for lung cancer. His dissertation work focused on CT scan based automated techniques for early lung cancer detection. The VIA group provides technical support for IELCAP (International Early Lung Cancer Program), an international collaboration of institutions and experts on lung cancer from around the world. In addition, he was the technical member of the LIDC (Lung Imaging Database Consortium) research group, a consortium of five academic institutions working together to develop publicly accessible CT image database. The database facilitates development and evaluation of CAD algorithms for detection of pulmonary nodules in CT scans.
At Ohio State University, where he received his Master's degree, he was a member of the Digital Photogrammetry Group, a world leader in cutting edge research in image processing and computer vision techniques applied to photogrammetry applications. He was involved in development of multisensor aerial triangulation and automated road sign extraction packages for digital map production. Dr. Enquobahrie received his B.S. in Electrical Engineering from Addis Ababa University, Ethiopia.