Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 307 for “"image segmentation"”.
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Image segmentation, evaluation, and applications
This thesis aims to advance research in image segmentation by developing robust techniques for evaluating image segmentation algorithms. The key contributions of this work are as follows. First, we investigate the characteristics of existing measures for supervised evaluation of automatic image …
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Semi-automatic medical image segmentation
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, February 2002.
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IRIS: Intelligent Roadway Image Segmentation
… be developed that uses a single visual camera to image the roadway, determine where the lane of travel is in the image, and segment that lane. The algorithm would need to be as accurate as current lane finding algorithms as well as faster than a standard k- means segmentation across the entire …
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Text Prompt-Driven Medical Image Segmentation
Medical image segmentation plays a crucial role in accurate diagnosis, treatment planning, and surgical navigation by precisely identifying pathological regions. However, traditional segmentation methods typically rely on dense pixel-level annotations and heavy computational resources, which pose …
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Intercomparison of medical image segmentation algorithms
… are several stages involved in analyzing an MRI image, segmentation being one of the most important. Image segmentation is essentially the process of identifying and classifying the constituent parts of an image, and is usually very complex. Unfortunately, it suffers from artefacts including …
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Connected operators for unsupervised image segmentation
Image segmentation forms the first stage in many image analysis procedures including image sequence re-timing and the emerging field of content based retrieval. By dividing the image into a set of disjoint connected regions, each of which is homogeneous with respect to some measure of the image …
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Curve evolution for medical image segmentation
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
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Digital image segmentation using periodic codings
Digital image segmentation using periodic codings is explored with reference to two applications. First, the application of uniform periodic codings, to the problem of segmenting the in-focus regions in an image from the blurred parts, is discussed. The work presented in this part extends a …
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Machine Learning towards General Medical Image Segmentation
… is proportionate to a physician's workload. Segmentation is a fundamental limiting precursor to diagnostic and therapeutic procedures. Advances in machine learning aims to increase diagnostic efficiency to replace single applications with generalized algorithms. We approached segmentation as …
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Image segmentation based on water flow analogy
… remote sensing, is of practical significance in image analysis. Region growing and snakes are the main methods used in the field, but the former cannot yield an exact result whilst the latter has difficulties with topological changes.<br/>This thesis presents a new method, based on the paradigm …
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0-1 graph partitioning and image segmentation
… also applied the graph partitioning algorithm to image segmentation. In comparison to the Normalized Cut method, we show that the method not only gives good segmentation, but it is also much simpler and faster in terms of the construction of a graph from an image, and robust to any noise contained …
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Model based three dimensional medical image segmentation
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
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"Brownian strings": Image segmentation with stochastically deformable models.
"Brownian strings": Image segmentation with stochastically deformable models.
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Learning with imperfect datasets in medical image segmentation
Medical image segmentation partitions medical images into distinct physiological regions, such as organs and lesions, essential for diagnosis and treatment planning. Deep neural networks have advanced this field recently, yet real-world performance remains unsatisfactory due to imperfect data and …
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Sickle Blood Cell Detection Based on Image Segmentation
… detect sickle blood cells in blood samples using image segmentation and shape detection. This method is based on calculating the max axis and min axis of the cell. The form factor is computed using these properties to determine whether the cell is sickle or not. This method is 90 percent more …
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Graph Models and Shape Deformation for Image Segmentation
… to improve the reliability and accuracy of image segmentation. Specifically, a new shape-deformation method is proposed to incorporate prior template shape information into image segmentation by deforming a given template shape to fit the detected low-level edge features in a target image. …
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Image Segmentation and Robust Estimation Using Parzen Windows
… explores the use of Parzen windows for modeling image data. The validity of such a model is shown to follow naturally from the elementary Gestalt laws of vicinity, similarity, and continuity of direction. Consistency results are derived for Parzen window estimators, both for continuous-time and …
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