4,912 research outputs found
A Learning Approach to Optical Tomography
We describe a method for imaging 3D objects in a tomographic configuration
implemented by training an artificial neural network to reproduce the complex
amplitude of the experimentally measured scattered light. The network is
designed such that the voxel values of the refractive index of the 3D object
are the variables that are adapted during the training process. We demonstrate
the method experimentally by forming images of the 3D refractive index
distribution of cells
Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation
Copyright @ 2011 Shadi AlZubi et al. This article has been made available through the Brunel Open Access Publishing Fund.The experimental study presented in this paper is aimed at the development of an automatic image segmentation system for classifying region of interest (ROI) in medical images which are obtained from different medical scanners such as PET, CT, or MRI. Multiresolution analysis (MRA) using wavelet, ridgelet, and curvelet transforms has been used in the proposed segmentation system. It is particularly a challenging task to classify cancers in human organs in scanners output using shape or gray-level information; organs shape changes throw different slices in medical stack and the gray-level intensity overlap in soft tissues. Curvelet transform is a new extension of wavelet and ridgelet transforms which aims to deal with interesting phenomena occurring along curves. Curvelet transforms has been tested on medical data sets, and results are compared with those obtained from the other transforms. Tests indicate that using curvelet significantly improves the classification of abnormal tissues in the scans and reduce the surrounding noise
Full field inversion in photoacoustic tomography with variable sound speed
Recently, a novel measurement setup has been introduced to photoacoustic
tomography, that collects data in the form of projections of the full 3D
acoustic pressure distribution at a certain time instant. Existing imaging
algorithms for this kind of data assume a constant speed of sound. This
assumption is not always met in practice and thus leads to erroneous
reconstructions. In this paper, we present a two-step reconstruction method for
full field detection photoacoustic tomography that takes variable speed of
sound into account. In the first step, by applying the inverse Radon transform,
the pressure distribution at the measurement time is reconstructed point-wise
from the projection data. In the second step, one solves a final time wave
inversion problem where the initial pressure distribution is recovered from the
known pressure distribution at the measurement time. For the latter problem, we
derive an iterative solution approach, compute the required adjoint operator,
and show its uniqueness and stability
Fast Mojette Transform for Discrete Tomography
A new algorithm for reconstructing a two dimensional object from a set of one
dimensional projected views is presented that is both computationally exact and
experimentally practical. The algorithm has a computational complexity of O(n
log2 n) with n = N^2 for an NxN image, is robust in the presence of noise and
produces no artefacts in the reconstruction process, as is the case with
conventional tomographic methods. The reconstruction process is approximation
free because the object is assumed to be discrete and utilizes fully discrete
Radon transforms. Noise in the projection data can be suppressed further by
introducing redundancy in the reconstruction. The number of projections
required for exact reconstruction and the response to noise can be controlled
without comprising the digital nature of the algorithm. The digital projections
are those of the Mojette Transform, a form of discrete linogram. A simple
analytical mapping is developed that compacts these projections exactly into
symmetric periodic slices within the Discrete Fourier Transform. A new digital
angle set is constructed that allows the periodic slices to completely fill all
of the objects Discrete Fourier space. Techniques are proposed to acquire these
digital projections experimentally to enable fast and robust two dimensional
reconstructions.Comment: 22 pages, 13 figures, Submitted to Elsevier Signal Processin
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