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Journal ArticleDOI

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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Citations
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Journal ArticleDOI

Breast cancer diagnosis using three-dimensional ultrasound and pixel relation analysis

TL;DR: In this article, Chen et al. used pixel relation analysis techniques for use with 3-D breast US images and compared its performance to 2-D versions of the images, and found that the features from only several slices are enough to provide good diagnostic results if the adopted features are modified from the 2D features.
Journal ArticleDOI

Robot-Assisted Medical Imaging: A Review

TL;DR: The view of the state of the art in ultrasound, endoscopy, X-ray, optical coherence tomography, and nuclear medicine is described and approaches to autonomous scanning and physics-driven approaches such as elastography and photoacoustic tomography are discussed.
Book

Automated Evaluation of Three Dimensional Ultrasonic Datasets

Ahmad Osman
TL;DR: In this paper, the authors proposed an analysis chain dedicated to automatically process the 3D ultrasound volumes obtained using the sampling phased array technique, which is adapted for ultrasound 3D data and has the objective to detect all potential defects inside the input volume.
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Compressed sensing reconstruction of synthetic transmit aperture dataset for volumetric diverging wave imaging.

TL;DR: 3D CS-STA has great potential of providing high quality volumetric image with a higher volume rate and is compared with 3D single-line-transmit (SLT) and 3D diverging wave compounding (DWC).
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Extracelluar matrix metalloproteinase as a novel target for pancreatic cancer therapy.

TL;DR: In the residual tumor model, tumor growth of anti-EMMPRIN-treated group was successfully arrested for 21 days and lowered tumor volume increase by approximately 40% compared with the control, regardless of the dose amount.
References
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Multidimensional transfer functions for interactive volume rendering

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