His primary scientific interests are in Artificial intelligence, Computer vision, Pattern recognition, Image processing and Algorithm. His studies deal with areas such as Markov chain and Affine transformation as well as Artificial intelligence. His work carried out in the field of Computer vision brings together such families of science as Function, Linear model and Interpolation.
His studies in Pattern recognition integrate themes in fields like Image, Image formation and Brain mapping. His research investigates the connection with Image processing and areas like Markov random field which intersect with concerns in Stochastic optimization, Image compression and Computational complexity theory. Michael Brady incorporates Robustness and Process in his research.
Michael Brady focuses on Artificial intelligence, Computer vision, Pattern recognition, Segmentation and Algorithm. His study in Image segmentation, Image processing, Image registration, Feature and Image falls under the purview of Artificial intelligence. His Image segmentation research is mostly focused on the topic Scale-space segmentation.
Many of his studies on Computer vision involve topics that are commonly interrelated, such as Pattern recognition. His Pattern recognition study combines topics from a wide range of disciplines, such as Salient, Breast cancer and Ground truth. The various areas that Michael Brady examines in his Segmentation study include Contrast and Magnetic resonance imaging, Mr images.
Michael Brady mostly deals with Artificial intelligence, Computer vision, Radiology, Image registration and Algorithm. His research combines Pattern recognition and Artificial intelligence. Michael Brady has researched Computer vision in several fields, including Mixture model, Differential geometry and Joint entropy.
His study in Radiology is interdisciplinary in nature, drawing from both Blood sampling and Cohort. His research in Image registration intersects with topics in Landmark, Matching, Computed tomography, Biomedical engineering and Pattern recognition. His Algorithm research incorporates elements of Image processing, Lymph node, Ideal and Lymph.
Michael Brady spends much of his time researching Artificial intelligence, Computer vision, Image registration, Algorithm and Image processing. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Bioinformatics. The study incorporates disciplines such as Computational complexity theory and Pattern recognition in addition to Computer vision.
His Image registration research includes elements of Molecular imaging, Positron emission tomography, Attenuation, Correction for attenuation and Motion correction. In his research on the topic of Algorithm, Robustness, Steatosis, Noise and Imaging phantom is strongly related with Ideal. His Image processing research is multidisciplinary, incorporating elements of Markov random field, Pixel, Scale-space segmentation and Microscope.
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IMPROVED OPTIMIZATION FOR THE ROBUST AND ACCURATE LINEAR REGISTRATION AND MOTION CORRECTION OF BRAIN IMAGES
Mark Jenkinson;Peter R. Bannister;Peter R. Bannister;Michael Brady;Stephen M. Smith.
Saliency, Scale and Image Description
Timor Kadir;Michael Brady.
International Journal of Computer Vision (2001)
MRI-Based Attenuation Correction for PET/MRI: A Novel Approach Combining Pattern Recognition and Atlas Registration
Matthias Hofmann;Florian Steinke;Verena Scheel;Guillaume Charpiat.
The Journal of Nuclear Medicine (2008)
Estimating the bias field of MR images
R. Guillemaud;M. Brady.
IEEE Transactions on Medical Imaging (1997)
Imaging biomarker roadmap for cancer studies.
James P.B. O'Connor;Eric O. Aboagye;Judith E. Adams;Hugo J.W.L. Aerts;Hugo J.W.L. Aerts.
Nature Reviews Clinical Oncology (2017)
Real-time corner detection algorithm for motion estimation
Han Wang;Michael Brady.
Image and Vision Computing (1995)
3D motion recovery via affine epipolar geometry
Larry S. Shapiro;Andrew Zisserman;Michael Brady.
International Journal of Computer Vision (1995)
Segmentation of ultrasound B-mode images with intensity inhomogeneity correction
Guofang Xiao;M. Brady;J.A. Noble;Yongyue Zhang.
IEEE Transactions on Medical Imaging (2002)
A Linguistic Feature Vector for the Visual Interpretation of Sign Language
Richard Bowden;Richard Bowden;David Windridge;Timor Kadir;Andrew Zisserman.
european conference on computer vision (2004)
Estimation of the partial volume effect in MRI.
Miguel Ángel González Ballester;Andrew P. Zisserman;Michael Brady.
Medical Image Analysis (2002)
Profile was last updated on December 6th, 2021.
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