&lt;title&gt;Incremental volume reconstruction and rendering for 3-D ultrasound imaging&lt;/title&gt;

Ohbuchi, Ryutarou; Chen, David; Fuchs, Henry

doi:10.1117/12.131087

Cited by 42 publications

(20 citation statements)

References 37 publications

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“…Our choice of kernel is motivated by need to match the underlying point spread function of the data. In the through slice direction this can be modeled as a Gaussian [31]. The Gaussian kernel is perpendicular to the slice plane, and the standard deviation determining the profile is chosen to match the known acquisition profile.…”

Section: Volume Reconstructionmentioning

confidence: 99%

Registration-Based Approach for Reconstruction of High-Resolution In Utero Fetal MR Brain Images

et al. 2006

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This paper describes a novel approach to forming high resolution MR images of the human fetal brain. It addresses the key problem of fetal motion by proposing a registration refined compounding of multiple sets of orthogonal fast 2D MRI slices, that are currently acquired for clinical studies, into a single high resolution MRI volume.A robust multi-resolution slice alignment is applied iteratively to the data to correct motion of the fetus that occurs between 2D acquisitions. This is combined with an intensity correction step and a super resolution reconstruction step, to form a single high isotropic resolution volume of the fetal brain.Experimental validation on synthetic image data with known motion types and underlying anatomy, together with retrospective application to sets of clinical acquisitions, are included.Results indicate that this method promises a unique route to acquiring high resolution MRI of the fetal brain in vivo allowing comparable quality to that of neonatal MRI. Such data provides a highly valuable window into the process of normal and abnormal brain development which is directly applicable in a clinical setting.

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Section: Volume Reconstructionmentioning

confidence: 99%

Registration-Based Approach for Reconstruction of High-Resolution In Utero Fetal MR Brain Images

et al. 2006

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“…-University of North Carolina at Chapel Hill, Department of computer science: The team at North Carolina has been concentrating on two areas: I-Real-time 3D ultrasound system: they have been working toward an ultimate 3D ultrasound system, which acquires and displays 3D volume data in real time [21]. Real-time display can be crucial for applications such as cardiac diagnosis, which need to detect certain kinetic features.…”

Section: Current State Of Knowledge and Different Schools Of 3d Ultramentioning

confidence: 99%

“…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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“…Electrical Several systems have used a mechanical arm with either one [119], three [138] or six [57] degrees of freedom. Potentiometers are mounted at the arm joints, and the electrical signals from these can be used to calculate the position.…”

Section: Automatic Position Sensingmentioning

confidence: 99%

“…Alternatively, a 3D convolution of the 2D slice with a 3D reconstruction kernel can create the 3D volume incrementally. Both spherical [138] and ellipsoidal [120] Gaussian kernels have been used; the latter is more representative of the actual sampling resolution. A more accurate method has been suggested in which the data is smoothly approximated by using radial basis functions [161]; however the small gain in reconstruction accuracy is matched by a significantly increased processing overhead.…”

Section: Data Interpolationmentioning

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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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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<title>Incremental volume reconstruction and rendering for 3-D ultrasound imaging</title>

Abstract: In this paper, we present approaches toward an interactive visualization of a real time input, applied to 3D

Cited by 42 publications

References 37 publications

Registration-Based Approach for Reconstruction of High-Resolution In Utero Fetal MR Brain Images

Registration-Based Approach for Reconstruction of High-Resolution In Utero Fetal MR Brain Images

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

Volume Measurement in Sequential Freehand 3-D Ultrasound

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