Megavoltage Images in Radiation Therapy
Systems Design Engineering
University of Waterloo
June 24, 2004
11:30 AM - 12:45 PM
MC 5158, University of Waterloo
Each year, the number of cancer cases that are diagnosed worldwide is over 5 million patients. Many of these patients (around 23 million) undergo some form of radiation therapy. The objective of cancer treatment is to eliminate tumors or, at least, avoid spread. Radiation therapy can be used before, during, or after surgery and serves often as an adjuvant treatment. To verify the shape and the location of the therapy beam with respect to the patient’s anatomy, megavoltage images (MVIs or electronic portal images) have become a pivotal data source for nearly all clinicians. Generally, a visual comparison is made between the patient’s actual position in relation to the beam and the planned treatment field. The treatment field is defined during diagnosis and treatment planning. For this purpose, usually a treatment simulation takes place where a simulator image (SI, off-line image, e.g. X-ray or CT image) is captured. Due to physical limitations, the unprocessed MVI is very poor in quality (poor contrast, low resolution, noise corrupted). Compared with MVI, the SI has a relatively high quality, but MVIs are on-line (in-treatment) data, providing information about the real position of the patient and his organs during the treatment. In recent years, a relatively large number of research papers have been dedicated to enhancement and restoration of MVIs. Dr. Tizhoosh will describe his research in this interesting and important area.
Hamid Tizhoosh, an assistant professor in Systems Design at the University of Waterloo, received his M.S. degree in electrical engineering from University of Technology, Aachen, Germany, in 1995. From 1993 to 1996, he worked at Management of Intelligent Technologies Ltd (M.I.T. GmbH), Aachen, Germany, in the area of industrial image processing. Dr. Tizhoosh received his Ph.D. degree from University of Magdeburg, Germany, in 2000 in the field of computer vision. His research encompasses machine intelligence, computer vision and soft computing. He is a member of the Pattern Analysis and Machine Intelligence Group and Medical Instrument Analysis and Machine Intelligence at the University of Waterloo.