Visualization of 3D ultrasound data

Nelson, Thomas R.; Elvins, T. Todd

doi:10.1109/38.252557

Cited by 110 publications

(50 citation statements)

References 10 publications

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“…• Extension of ultrasound to 3D provides new images which would otherwise be impossible to visualise, and previously could only be imagined by the clinician building up a mental picture from 2D information [131]. This may make the modality more accessible to those less experienced in analysing ultrasound images.…”

Section: Why 3d Ultrasound?mentioning

confidence: 99%

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Volume Measurement in Sequential Freehand 3-D Ultrasound

Treece

Prager

Gee

et al. 1999

Lecture Notes in Computer Science

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SummaryThree-dimensional (3D) acquisition and visualisation techniques are increasingly being incorporated into commercial ultrasound scanners. The diagnostic benefit of such techniques is not yet convincing, compared to the added inconvenience of using them. Although it is straightforward to use special probes to acquire 3D data, these are more restrictive than conventional 2D probes. The only 3D technique which retains the scanning flexibility and wide area of application of 2D ultrasound, is freehand 3D ultrasound, where a 2D probe is moved manually and its location sensed remotely. However, it is hard to generate a regular volume of data from the resulting non-parallel ultrasound images.Probably the largest body of evidence justifying the use of 3D ultrasound relates to the accurate measurement of volume. However, volume measurement with 3D ultrasound requires segmentation (i.e. outlining of the area of interest), which is a time consuming, manual task. Both this problem, and that of creating a regular volume of data, are eased by the use of sequential freehand 3D ultrasound, a recent technique amplified in this thesis, where all the processing is performed on the original ultrasound images. Thus a regular array of data is not required, and segmentation is performed on images whose features and artifacts are recognisable to the clinician.In this thesis, novel volume measurement and surface visualisation algorithms are developed for sequential freehand 3D ultrasound. A particular emphasis is placed on limiting the number of segmented cross-sections required for a given measurement accuracy. Inherent accuracy is demonstrated by simulation to be within ±2%, from 10 or fewer cross-sections. In vivo precision, including registration and segmentation errors, is shown to be within ±7%, even on complicated objects such as the liver or a foetus, from similar numbers of cross-sections. The volume can be updated in real-time as each image is segmented, and surfaces can be interpolated and visualised within a few seconds. Such visualisation can reveal errors in the segmentation which are otherwise hard to see.In addition, a framework for multiple-sweep data is developed, which allows volume measurement and surface visualisation of anatomy that can only be scanned by several sweeps of the ultrasound probe. Accurate volume measurements can therefore be made of all areas observable by conventional ultrasound. These measurements can be accomplished within approximately 5 minutes of examining the patient.The surface visualisation algorithms can also produce high quality renderings of data from a wide range of sources in medical imaging and other fields. The interpolation of cross-sections is an improvement on shape-based interpolation, and the triangular mesh created from the data is of a much higher quality than that using marching cubes. An extension of the surface interpolation algorithm can also be used to gradually change, or 'morph' one 3D surface to another, a technique commonly used in the film industry.

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Section: Why 3d Ultrasound?mentioning

confidence: 99%

“…Existing ultrasound machines are less expensive both to buy and to run, and require less specialised facilities [131]. They can also be upgraded to 3D surprisingly cheaply [152].…”

Section: Why 3d Ultrasound?mentioning

confidence: 99%

Volume Measurement in Sequential Freehand 3-D Ultrasound

Treece

Prager

Gee

et al. 1999

Lecture Notes in Computer Science

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“…This is typically the receiver of an electromagnetic position sensor [4,5,6,7,8], as illustrated in Figure 1, although alternatives include acoustic spark gaps [9], mechanical arms [10] and optical sensors [11,12]. Measurements from the electromagnetic position sensor are used to determine the positions and orientations of the B-scans with respect to a fixed datum, usually the transmitter of the electromagnetic position sensor.…”

Section: Introductionmentioning

confidence: 99%

PC-Based System for Calibration, Reconstruction, Processing, and Visualization of 3D Ultrasound Data Based on a Magnetic-Field Position and Orientation Sensing System

Boctor

Saad

Chang

et al. 2001

Lecture Notes in Computer Science

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Abstract. 3D-ultrasound can become a new, fast, non-radiative, noninvasive, and inexpensive tomographic medical imaging technique with unique advantages for the localization of vessels and tumors in soft tissue (spleen, kidneys, liver, breast etc.). In general, unlike the usual 2D-ultrasound, in the 3D-case a complete volume is covered with a whole series of cuts, which would enable a 3D reconstruction and visualization.In the last two decades, many researchers have attempted to produce systems that would allow the construction and visualization of threedimensional (3-D) images from ultrasound data. There is a general agreement that this development represents a positive step forward in medical imaging, and clinical applications have been suggested in many different areas. However, it is clear that 3-D ultrasound has not yet gained widespread clinical acceptance, and that there are still important problems to solve before it becomes a common tool.

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“…Earlier work on ultrasound image processing and analysis has focused on 3D reconstruction [8,10,12,11]. Unlike CT or MRI, where 3D data can easily be acquired from tomography machines (by stacking a sequence of parallel 2D images), ultrasound scanners produce a video signal that needs to be discretized to obtain 2D images; however, these images are arbitrarily oriented and special 3D sensors will need to be used to obtain spatial information to orient and locate each 2D image [8]. The problems associated with this process have limited the use of such methods to medical research centers or hospitals.…”

Section: Introductionmentioning

confidence: 99%

Interactive Segmentation and Analysis of Fetal Ultrasound Images

1997

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Abstract. The ability of ultrasound scanners to image anatomical structures in real time have led to their use in two important applications of medicine, (1) for monitoring the unborn baby (fetal ultrasound), and, (2) coronary treatment of blockages in blood vessels (intravascular ultrasound). The generated images (in the form of a continuous video) are typically noisy and contain numerous artifacts, making it difficult to isolate and measure features of interest. We explore the use of two algorithms, region growing and a variant of split/merge algorithm for segmenting sequences of fetal ultrasound images. We describe an interactive system that can rapidly process and segment an arbitrary number of features. The system exploits frame to frame coherence for accelerating the segmentation process, while at the same time combining the strengths of these algorithms and some post-processing for accurate and robust detection of features.

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Visualization of 3D ultrasound data

Cited by 110 publications

References 10 publications

Volume Measurement in Sequential Freehand 3-D Ultrasound

Volume Measurement in Sequential Freehand 3-D Ultrasound

PC-Based System for Calibration, Reconstruction, Processing, and Visualization of 3D Ultrasound Data Based on a Magnetic-Field Position and Orientation Sensing System

Interactive Segmentation and Analysis of Fetal Ultrasound Images

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