764 research outputs found

    Homotopy Based Reconstruction from Acoustic Images

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    Segmentation of neuroanatomy in magnetic resonance images

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    Segmentation in neurological Magnetic Resonance Imaging (MRI) is necessary for volume measurement, feature extraction and for the three-dimensional display of neuroanatomy. This thesis proposes several automated and semi-automated methods which offer considerable advantages over manual methods because of their lack of subjectivity, their data reduction capabilities, and the time savings they give. Work has concentrated on the use of dual echo multi-slice spin-echo data sets in order to take advantage of the intrinsically multi-parametric nature of MRI. Such data is widely acquired clinically and segmentation therefore does not require additional scans. The literature has been reviewed. Factors affecting image non-uniformity for a modem 1.5 Tesla imager have been investigated. These investigations demonstrate that a robust, fast, automatic three-dimensional non-uniformity correction may be applied to data as a pre-processing step. The merit of using an anisotropic smoothing method for noisy data has been demonstrated. Several approaches to neurological MRI segmentation have been developed. Edge-based processing is used to identify the skin (the major outer contour) and the eyes. Edge-focusing, two threshold based techniques and a fast radial CSF identification approach are proposed to identify the intracranial region contour in each slice of the data set. Once isolated, the intracranial region is further processed to identify CSF, and, depending upon the MRI pulse sequence used, the brain itself may be sub-divided into grey matter and white matter using semiautomatic contrast enhancement and clustering methods. The segmentation of Multiple Sclerosis (MS) plaques has also been considered. The utility of the stack, a data driven multi-resolution approach to segmentation, has been investigated, and several improvements to the method suggested. The factors affecting the intrinsic accuracy of neurological volume measurement in MRI have been studied and their magnitudes determined for spin-echo imaging. Geometric distortion - both object dependent and object independent - has been considered, as well as slice warp, slice profile, slice position and the partial volume effect. Finally, the accuracy of the approaches to segmentation developed in this thesis have been evaluated. Intracranial volume measurements are within 5% of expert observers' measurements, white matter volumes within 10%, and CSF volumes consistently lower than the expert observers' measurements due to the observers' inability to take the partial volume effect into account

    Spatial distribution maps for benthic communities

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    Combining global and local information for the segmentation of MR images of the brain

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    Magnetic resonance imaging can provide high resolution volumetric images of the brain with exceptional soft tissue contrast. These factors allow the complex structure of the brain to be clearly visualised. This has lead to the development of quantitative methods to analyse neuroanatomical structures. In turn, this has promoted the use of computational methods to automate and improve these techniques. This thesis investigates methods to accurately segment MRI images of the brain. The use of global and local image information is considered, where global information includes image intensity distributions, means and variances and local information is based on the relationship between spatially neighbouring voxels. Methods are explored that aim to improve the classification and segmentation of MR images of the brain by combining these elements. Some common artefacts exist in MR brain images that can be seriously detrimental to image analysis methods. Methods to correct for these artifacts are assessed by exploring their effect, first with some well established classification methods and then with methods that combine global information with local information in the form of a Markov random field model. Another characteristic of MR images is the partial volume effect that occurs where signals from different tissues become mixed over the finite volume of a voxel. This effect is demonstrated and quantified using a simulation. Analysis methods that address these issues are tested on simulated and real MR images. They are also applied to study the structure of the temporal lobes in a group of patients with temporal lobe epilepsy. The results emphasise the benefits and limitations of applying these methods to a problem of this nature. The work in this thesis demonstrates the advantages of using global and local information together in the segmentation of MR brain images and proposes a generalised framework that allows this information to be combined in a flexible way

    Registration and variability of side scan sonar imagery

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    Submitted in partial fulfillment of the requirements for the degree of Ocean Engineer at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution August 1988This thesis presents the results of several experiments performed on side scan sonar equipment and imagery with the aim of characterizing the acoustic variability of side scan sonar imagery and applying this information to image rectification and registration. A static test tank experiment is presented which analyzes the waveform, power spectral density, and temporal variability of the transmitted waveform. The results of a second static experiment conducted from the Woods Hole Oceanographic Institution Pier in Woods Hole, Massachusetts permit determination of the distribution and moments of intensity fluctuations of echoes from objects imaged in side scan sonograms. This experiment also characterizes temporal and spatial coherence of intensity fluctuations. A third experiment is presented in which a side scan sonar towfish images the bottom adjacent to the pier while running along an underwater track which reduces towfish instability. Imagery from this experiment is used to develop a rectification and registration algorithm for side scan sonat images. Preliminary image processing is described and examples presented, followed by favorable results for automated image rectification and registration.Massachusetts Commonwealth Centers of Excellence, Marine Imaging Systems, and The National Science Foundation for funding this researc

    In-situ identification of marine organisms using high frequency, wideband ultrasound

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    The use of multibeam and split-beam echo sounders for assessing biomass and distribution of spring-spawning Atlantic cod in the Gulf of Maine

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    This research focused on advancing the application of split-beam and multibeam echo sounding to remotely locate and describe spatial distribution, and to provide a relative measure of abundance of the spring-spawning Atlantic cod (Gadus morhua) in the western Gulf of Maine. Specifically, the main objectives of this research were 1) to test the feasibility of a multibeam echo sounder to detect changes in volume backscatter proportional to incrementally decreasing quantities of cod held in a submerged cage, and to compare results to a split-beam echo sounder; 2) to describe the spatio-temporal distribution and estimate biomass of spring-spawning cod in the Gulf of Maine cod spawning protection area (GOMCSPA) by repeated acoustic and trawl surveys; and 3) to determine a predictive relation between target strength and length for 38-kHz and 120-kHz split-beam echo sounders and a 300-kHz multibeam echo sounder, and characterize other factors affecting backscattering of sound. The multibeam echo sounder detected a small and large reduction in volume backscatter proportional to reductions in stocking density of caged cod, while the split-beam echo sounder only detected a large reduction in stocking density. The spatial information from the multibeam echo sounder helped interpret and explain results from the split-beam echo sounder. Repeated acoustic and trawl surveys showed cod were relatively widespread in the survey area in May, but congregated at higher densities in areas adjacent to two elevated bathymetric features. Most cod converged to a single location in June, and were at a higher concentration than observations in May. This congregation decreased in size and density in July. Survey estimates of cod biomass ranged 184-494 mt in May, 138-617 mt in June, and 39-135 mt in July, depending on the estimation method. Based on echo classification and extrapolation, cod biomass to the GOMCSPA ranged 260-466 mt in May, 196-513 mt in June, and 91-198 mt in July. The biomass being protected by the closure may have represented 4-5% of the GOM cod spawning stock biomass at the time of the study based on these estimates. The three echo sounders synchronously collected acoustic data of individual free-swimming captive cod, while the movements of most individuals were observed with underwater video. The standard TS-L equations were TS = 20 log10(L) -- 66.4 at 38 kHz, TS = 20 log10(L) -- 67.4 at 120 kHz, and 〈TS〉 = 20 log10(L) -- 71.4 at 300 kHz. The study demonstrated a significant TS-L relation at 300 kHz from aggregated data collected by a multibeam echo sounder with narrow beams over multiple beam-pointing angles and without split-beam target tracking
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