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. 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. He is currently an assistant professor at the department of Biomedical Informatics. Dr. Gurcan's research interests include image analysis and understanding, computer vision with applications to medicine. He is the recipient of the British Foreign and Commonwealth Organization Award, caBIG Embodying the Vision Award and The Children Neuroblastoma Cancer Foundation Young Investigator Award. He has been elected to the grade of Senior Member of the Institute of Electrical and Electonics Engineers (IEEE), and is a member of the RSNA and SPIE.
My professional interests revolve around the development, integration and adoption of information technologies in the discipline of Pathology. One of my main areas of interest within this broad discipline has been in the field of digital imaging. We have been exploring pathology imaging on several fronts including interactions between pathology/radiology (High resolution MRI imaging of prostate cancer), development and utilization of computer assisted diagnostic algorithms for machine vision in prostate and breast cancer (Collaboration with Dr. Anant Madabushi, Rutgers) and automated immunohistochemical scoring of TMA (Collaboration with Dr. David Foran at UMDNJ). Our newest area of investigation is the use of multispectral imaging for the analysis of multicolor immunohistochemistry and immunoflourescence and the development of a quantitative system for scoring and analyzing at a cytometric level, multicolor immunostaining on surgical pathology slides.
Dr. Anant Madabhushi is currently an Assistant Professor, Dept. of Biomedical Engineering, Rutgers University. He received his Bachelors Degree in Biomedical Engineering from Mumbai University, India in 1998 and his Masters in Biomedical Engineering from the University of Texas, Austin in 2000. In 2004 he obtained his PhD in Bioengineering from the University of Pennsylvania. Dr. Madabhushi has more than 20 publications and book chapters in leading International journals and his presented his work at a number of prestigious conferences. His research interests are in the area of medical image analysis, computer-aided diagnosis, machine learning, and computer vision.His research focuses on developing novel computer-aided diagnostic (CAD) systems that can assist the doctor by automatically detecting suspicious regions in medical images, such as those obtained from the MRI, CT, and ultrasound scanners.
Nasir Rajpoot is an Associate Professor in Computer Science at the University of Warwick, United Kingdom. He joined the Computer Science department as a Lecturer in 2001, after completing his PhD in image coding at Warwick. He was a visiting postgraduate research fellow at the Applied Mathematics programme of Yale University during 1998-2000. Dr Rajpoot has published over 50 refereed articles in the areas of image coding and denoising, texture analysis, shape analysis, and histology image analysis. He is on the review panels of more than a dozen international journals and on the Programme Committee of a number of international conferences. He was co-chair of the special focus session titled Computational Histopathology: Advances and New Challenges at ISBI 2008 earlier this year. Dr Rajpoot was the technical chair of British Machine Vision Conference (BMVC), held at Warwick in September 2007. His current research interests lie in the areas of efficient image representations and computational histopathology.
