Journal ArticleDOI
Wavelets in Temporal and Spatial Processing of Biomedical Images
TLDR
Key concepts in the processing of medical images with wavelet transforms and multiscale analysis are reviewed, including time-frequency tiling, overcomplete representations, higher dimensional bases, symmetry, boundary effects, translational invariance, orientation selectivity, and best-basis selection.Abstract:
▪ Abstract We review some of the most recent advances in the area of wavelet applications in medical imaging. We first review key concepts in the processing of medical images with wavelet transforms and multiscale analysis, including time-frequency tiling, overcomplete representations, higher dimensional bases, symmetry, boundary effects, translational invariance, orientation selectivity, and best-basis selection. We next describe some applications in magnetic resonance imaging, including activation detection and denoising of functional magnetic resonance imaging and encoding schemes. We then present an overview in the area of ultrasound, including computational anatomy with three-dimensional cardiac ultrasound. Next, wavelets in tomography are reviewed, including their relationship to the radon transform and applications in position emission tomography imaging. Finally, wavelet applications in digital mammography are reviewed, including computer-assisted diagnostic systems that support the detection and ...read more
Citations
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Journal ArticleDOI
Two-dimensional windowed Fourier transform for fringe pattern analysis: Principles, applications and implementations
TL;DR: Two algorithms, one based on filtering and the other based on similarity measure, are developed and some applications based on these two algorithms are explored, including strain determination, phase unwrapping, phase-shifter calibration, fault detection, edge detection and fringe segmentation.
Journal ArticleDOI
Complex wavelets for extended depth‐of‐field: A new method for the fusion of multichannel microscopy images
TL;DR: This work shows how the wavelet‐based image fusion technique can be improved and easily extended to multichannel data and proposes the use of complex‐valued wavelet bases, which seem to outperform traditional real‐valuedWavelet transforms.
Journal ArticleDOI
Diffusional Trapping of GluR1 AMPA Receptors by Input-Specific Synaptic Activity
TL;DR: It is reported that synaptic activity locally immobilizes GluR1 AMPA receptors at individual synapses, defining an input-specific mechanism for regulating AMPA receptor composition and abundance.
Journal ArticleDOI
Wavelets and functional magnetic resonance imaging of the human brain.
Edward T. Bullmore,Jalal M. Fadili,Voichita Maxim,Levent Sendur,Brandon Whitcher,John Suckling,Michael Brammer,Michael Breakspear +7 more
TL;DR: It is concluded that the wavelet domain is a rich source of new concepts and techniques to enhance the power of statistical analysis of human fMRI data.
Journal ArticleDOI
Wavelets and statistical analysis of functional magnetic resonance images of the human brain.
Edward T. Bullmore,Jalal M. Fadili,Michael Breakspear,Raymond Salvador,John Suckling,Michael Brammer +5 more
TL;DR: This work focuses on time series resampling by ‘wavestrapping’ of wavelet coefficients, methods for efficient linear model estimation in the wavelet domain, and wavelet-based methods for multiple hypothesis testing, all of which are somewhat simplified by the decorrelating property of the DWT.
References
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Journal ArticleDOI
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
Journal ArticleDOI
A theory for multiresolution signal decomposition: the wavelet representation
TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
Book
A wavelet tour of signal processing
TL;DR: An introduction to a Transient World and an Approximation Tour of Wavelet Packet and Local Cosine Bases.
Book
Ten lectures on wavelets
TL;DR: This paper presents a meta-analyses of the wavelet transforms of Coxeter’s inequality and its applications to multiresolutional analysis and orthonormal bases.
Journal ArticleDOI
Ten Lectures on Wavelets
TL;DR: In this article, the regularity of compactly supported wavelets and symmetry of wavelet bases are discussed. But the authors focus on the orthonormal bases of wavelets, rather than the continuous wavelet transform.