scispace - formally typeset
J

J. Michael Brady

Researcher at University of Oxford

Publications -  66
Citations -  16685

J. Michael Brady is an academic researcher from University of Oxford. The author has contributed to research in topics: Image registration & Feature (computer vision). The author has an hindex of 20, co-authored 66 publications receiving 15070 citations.

Papers
More filters
Journal ArticleDOI

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

TL;DR: The authors propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations.
Journal ArticleDOI

SUSAN—A New Approach to Low Level Image Processing

TL;DR: This paper describes a new approach to low level image processing; in particular, edge and corner detection and structure preserving noise reduction and the resulting methods are accurate, noise resistant and fast.
Journal ArticleDOI

Temporal autocorrelation in univariate linear modeling of FMRI data.

TL;DR: Estimation is improved by using nonlinear spatial filtering to smooth the estimated autocorrelation, but only within tissue type, and reduced bias to close to zero at probability levels as low as 1 x 10(-5).
Journal ArticleDOI

The Curvature Primal Sketch

TL;DR: An implemented algorithm is described that computes the Curvature Primal Sketch by matching the multiscale convolutions of a shape, and its performance on a set of tool shapes is illustrated.
Journal ArticleDOI

Imaging biomarker roadmap for cancer studies.

James P B O'Connor, +78 more
TL;DR: Experts assembled to review, debate and summarize the challenges of IB validation and qualification produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical validation, biological/clinical validation and assessment of cost-effectiveness.