ICASSP 2010 - 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing - March 14 - 19, 2010 - Dallas, Texas, USA

Tutorial 3: Biomedical Image Processing and Analysis Techniques

Presented by

Metin N. Gurcan


Biomedical image processing and analysis requires coordinated efforts of medical professionals, algorithmic and software engineers, and statisticians. Basic image processing techniques are frequently used in every aspect of the development from initial pre-processing techniques for noise reduction, to segmentation of lesions, to registration of lesions. Recent advances in hardware and software have made it possible to create digital scans of whole slides. These images are relatively large (100k x 100k) and in color, hence processing them present new challenges. Similarly, new computed tomography and magnetic resonance imaging scanners produce thousands of slices of images. The processing need for these images are enormous. Although biomedical image analysis research is getting increasingly popular, it does not receive sufficient coverage in most curriculums. This tutorial will introduce the current challenges and recent advances and innovations in this newly developing area while reviewing several frequently used image processing techniques in this context. It will be taught from the perspective of a researcher, who carried out biomedical image analysis and processing research for over 10 years both in academia and industry.

While most images can be easily processed using a high-end computer, very large scale microscopic images require special processing techniques. This tutorial will talk about virtual microscopy, cluster/grid computing and parallel processing techniques. Some novel computational architectures such as general purpose GPUs and cell blades (e.g. those in Sony PlayStation™ 3) are extremely suitable to process these types of images, however, they require special coding techniques. It will also discuss how some of microscopic image processing can be done using these novel computational architectures, which can also be used for efficient processing of all kinds of images.

Speaker Biography

Dr. Gurcan received his BSc. and Ph.D. degrees in Electrical and Electronics Engineering from Bilkent University, Turkey and his MSc. Degree in Digital Systems Engineering from the University of Manchester Institute of Science and Technology, England. He is the recipient of the British Foreign and Commonwealth Organization Award, Children¹s Neuroblastoma Cancer Foundation Young Investigator Award and National Cancer Institute¹s caBIG Embodying the Vision Award. During the winters of 1996 and 1997 he was a visiting researcher at the University of Minnesota, Minneapolis. From 1999 to 2001, he was a postdoctoral research fellow and later a research investigator in the Department of Radiology at the University of Michigan, Ann Arbor. Prior to joining the Ohio State University in October 2005, he worked as a senior researcher and product director at a high-tech company, specializing in computer-aided detection and diagnosis of cancer from radiological images. Dr. Gurcan is a senior member of IEEE, SPIE and RSNA. Dr. Gurcan currently manages several image analysis related projects funded by the National Cancer Institute, National Library of Medicine, American Cancer Society, Department of Defense and Children¹s Neuroblastoma Cancer Foundation. He teaches tutorials IEEE ICIP and ICASSP conferences, and is the organizer of and lecturer at several meetings, workshops, special focus sessions at leading conferences in areas of image analysis.

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