DICTA 2012   Digital Image Computing: Techniques and Applications


 

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Keynote Speakers

Prof. Maryellen Giger, University of Chicago, USA
Maryellen L. Giger is Professor of Radiology, the Committee on Medical Physics, and the College at the University of Chicago and is Director of the CAMPEP-accredited Graduate Programs in Medical Physics at the University; serving as Chair of the Ph.D. degree granting Committee on Medical Physics in the BSD. She also serves as Vice-Chair for Basic Science Research in the Department of Radiology, University of Chicago and Director of the BSD's Imaging Research Institute.

Dr. Giger is considered one of the pioneers in the development of CAD (computer-aided diagnosis). She has authored or co-authored more than 240 scientific manuscripts, is inventor/co-inventor on approximately 25 patents. Her research focuses on the development of multimodality CAD (computer-aided diagnosis) and quantitative image analysis methods. Her research interests include digital medical imaging, computer-aided diagnosis, quantitative image analysis, and data-mining in breast imaging, chest/CT imaging, cardiac imaging, and bone radiography. The long-term goals of her research are to investigate, develop, and translate multi-modality computerized image analysis techniques, which yield image-based tumor signatures and phenotypes, for improved cancer diagnosis, prognosis, and patient care. Development of these methods includes novel means for lesion segmentation, and 2D and 3D extraction of features characterizing the tumors and local background surround.

Prof. Josef Kittler, University of Surrey, UK
Prof. Josef Kittler is a Distinguished Professor at the University of Surrey. He has worked on various theoretical aspects of Pattern Recognition, Image Analysis and Computer Vision, and on many applications including System Identification, Automatic Inspection, ECG diagnosis, Mammographic Image Interpretation, Remote Sensing, Robotics, Speech Recognition, Character Recognition and Document Processing, Image Coding, Biometrics, Image and Video Database Retrieval, and Surveillance. Contributions to statistical pattern recognition include k-nearest neighbour methods of pattern classification, feature selection, contextual classification, probabilistic relaxation and most recently to multiple expert fusion. In computer vision his major contributions include robust statistical methods for shape analysis and detection, motion estimation and segmentation, and image segmentation by thresholding and edge detection. He has co-authored a book with the title 'Pattern Recognition: a statistical approach' published by Prentice-Hall and published more than 500 papers.

Prof. Zhouchen Lin, Peking University, China
Dr. Zhouchen Lin is a Professor in the Department of Intelligence Sciences, School of Electronic Engineering and Computer Science, Peking University. His research interests include Image Processing, Pattern Recognition, Machine Learning, and Optimization. Prior to his appointment at Peking University he was a Lead Researcher with the Visual Computing Group, Microsoft Research, where he worked in a variety of areas including: Digital Ink, Digital Pen, Pattern Recognition, Machine Learning, Document Processing/Analysis, Biometrics, Numerical Computation, Coding Theory, and Security.

Prof. Anton van den Hengel, Adelaide University, Australia
Anton van den Hengel is the director The Australian Centre for Visual Technologies and Professor in the Department of Computer Science at The University of Adelaide. His interests include: image-based modelling and 3D content generation, augmented reality, robust statistics, and video surveillance.

Prof. Ian Reid, Adelaide University, Australia
Ian's research interests span a wide range of topics in Computer Vision. In particular he is concerned with algorithms for visual control of active head/eye robotic platforms (for surveillance and navigation), visual geometry and camera self-calibration (applications of these to measurement, AR and VR, including sporting events), visual SLAM, human motion capture, activity analysis, and novel view synthesis.