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Three-Dimensional Ultrasound Imaging

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TLDR
A review article describes the developments of a number of 3D ultrasound imaging systems using mechanical, free-hand and 2D array scanning techniques and the sources of errors in the reconstruction techniques as well as formulae relating design specification to geometric errors.
Abstract
Ultrasound is an inexpensive and widely used imaging modality for the diagnosis and staging of a number of diseases. In the past two decades, it has benefited from major advances in technology and has become an indispensable imaging modality, due to its flexibility and non-invasive character. In the last decade, research investigators and commercial companies have further advanced ultrasound imaging with the development of 3D ultrasound. This new imaging approach is rapidly achieving widespread use with numerous applications. The major reason for the increase in the use of 3D ultrasound is related to the limitations of 2D viewing of 3D anatomy, using conventional ultrasound. This occurs because: (a) Conventional ultrasound images are 2D, yet the anatomy is 3D, hence the diagnostician must integrate multiple images in his mind. This practice is inefficient, and may lead to variability and incorrect diagnoses. (b) The 2D ultrasound image represents a thin plane at some arbitrary angle in the body. It is difficult to localize the image plane and reproduce it at a later time for follow-up studies. In this review article we describe how 3D ultrasound imaging overcomes these limitations. Specifically, we describe the developments of a number of 3D ultrasound imaging systems using mechanical, free-hand and 2D array scanning techniques. Reconstruction and viewing methods of the 3D images are described with specific examples. Since 3D ultrasound is used to quantify the volume of organs and pathology, the sources of errors in the reconstruction techniques as well as formulae relating design specification to geometric errors are provided. Finally, methods to measure organ volume from the 3D ultrasound images and sources of errors are described.

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References
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TL;DR: The rapidly expanding body of work on the development and application of deformable models to problems of fundamental importance in medical image analysis, including segmentation, shape representation, matching and motion tracking is reviewed.
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TL;DR: This paper presents a front-to-back image-order volume-rendering algorithm and discusses two techniques for improving its performance, which employs a pyramid of binary volumes to encode spatial coherence present in the data and uses an opacity threshold to adaptively terminate ray tracing.
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Review of MR image segmentation techniques using pattern recognition.

TL;DR: This paper has reviewed, with somewhat variable coverage, the nine MR image segmentation techniques itemized in Table II; each has its merits and drawbacks.
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Magnetic Position and Orientation Tracking System

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Multidimensional transfer functions for interactive volume rendering

TL;DR: An important class of 3D transfer functions for scalar data is demonstrated, and the application of multi-dimensional transfer functions to multivariate data is described, and a set of direct manipulation widgets that make specifying such transfer functions intuitive and convenient are presented.
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