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Surface Reconstruction from Sparse and Arbitrarily Oriented Contours in Freehand 3D Ultrasound
Shuangcheng Deng,Yunhua Li,Lipei Jiang,Yingyu Cao
Research Journal of Applied Sciences, Engineering and Technology , 2013,
Abstract: 3D reconstruction for freehand 3D ultrasound is a challenging issue because the recorded B-scans are not only sparse, but also non-parallel (actually they may arbitrarily orient in 3D space and may intersect each other). Conventional volume reconstruction methods can’t reconstruct sparse data efficiently while not introducing geometrical artifacts and conventional surface reconstruction methods can’t reconstruct surfaces from contours that are arbitrarily oriented in 3D space. We developed a new surface reconstruction method for freehand 3D ultrasound based on variational implicit function which is presented by Greg Turk for shape transformation. In the new method, we first constructed on- and off-surface constraints from the segmented contours of all recorded B-scans and then used a variational interpolation technique to get a single implicit function in 3D. Finally, the implicit function was evaluated to extract the zero-valued surface as final reconstruction result. Two experiments was conducted to assess our variational surface reconstruction method and the experiment results have shown that the new method is capable of reconstructing surface smoothly from sparse contours which can be arbitrarily oriented in 3D space.
A survey of freehand 3D ultrasound reconstruction algorithms
Freehand 3维超声重建算法综述

sunyinshan,wudongmei,duzhijiang,sunlining,
孙银山
,吴冬梅,杜志江,孙立宁

中国图象图形学报 , 2010,
Abstract: The research of Freehand 3D ultrasound has been playing an increasingly important role in the 3D reconstruction techniques of ultrasound images in recent decades. 3D ultrasound is classified firstly according to different taking manners. Then the characteristic of Freehand 3D ultrasound system and the principle of 3D reconstruction for Freehand ultrasound images are illuminated. Finally, the overview and comparison analysis of Freehand 3D ultrasound reconstruction algorithms are provided. Synchronously some challenges and research orientations are also indicated.
Calibration of an orientation sensor for freehand 3D ultrasound and its use in a hybrid acquisition system
Richard Housden, Graham M Treece, Andrew H Gee, Richard W Prager
BioMedical Engineering OnLine , 2008, DOI: 10.1186/1475-925x-7-5
Abstract: We investigate an alternative position sensor, the Xsens MT9-B, which is relatively unobtrusive but measures orientation only. We describe a straightforward approach to calibrating the sensor, and we measure the calibration precision (by repeated calibrations) and the orientation accuracy (using independent orientation measurements). We introduce algorithms that allow the MT9-B potentially to correct both linear and angular drift in sensorless reconstructions.The MT9-B can be calibrated to a precision of around 1°. Reconstruction accuracy is also around 1°. The MT9-B was able to eliminate angular drift in sensorless reconstructions, though it had little impact on linear drift. In comparison, six degree-of-freedom drift correction was shown to produce excellent reconstructions.Gold standard freehand 3D ultrasound acquisition requires the synthesis of image-based techniques, for good fine scale detail, and position sensors, for good large scale geometrical accuracy. A hybrid system incorporating the MT9-B offers an attractive compromise between quality and ease of use. The position sensor is unobtrusive and the system is capable of faithful acquisition, with the one exception of linear drift in the elevational direction.3D ultrasound [1,2] is an emerging medical imaging modality with a wide range of potential applications [3]. The data can be acquired using dedicated 3D probes incorporating either a 2D array or an oscillating head which sweeps the B-scan plane over a fixed volume. The alternative, freehand approach involves the clinician manually sweeping a conventional probe over the target: by attaching a position sensor to the probe, each B-scan can be labelled with its position and orientation. The B-scans thus form a 3D data set which can be visualised and processed in a number of ways to extract clinically useful information. The freehand approach offers the advantages of arbitrary acquisition volumes, with translation as well as rotation of the scan head, low c
Reconstructions in Ultrasound Modulated Optical Tomography  [PDF]
Moritz Allmaras,Wolfgang Bangerth
Mathematics , 2009,
Abstract: We introduce a mathematical model for ultrasound modulated optical tomography and present a simple reconstruction scheme for recovering the spatially varying optical absorption coefficient from scanning measurements with narrowly focused ultrasound signals. Computational results for this model show that the reconstruction of sharp features of the absorption coefficient is possible. A formal linearization of the model leads to an equation with a Fredholm operator, which explains the stability observed in our numerical experiments.
MMSE Reconstruction for 3D Freehand Ultrasound Imaging  [PDF]
Wei Huang,Yibin Zheng
International Journal of Biomedical Imaging , 2008, DOI: 10.1155/2008/274164
Abstract: The reconstruction of 3D ultrasound (US) images from mechanically registered, but otherwise irregularly positioned, B-scan slices is of great interest in image guided therapy procedures. Conventional 3D ultrasound algorithms have low computational complexity, but the reconstructed volume suffers from severe speckle contamination. Furthermore, the current method cannot reconstruct uniform high-resolution data from several low-resolution B-scans. In this paper, the minimum mean-squared error (MMSE) method is applied to 3D ultrasound reconstruction. Data redundancies due to overlapping samples as well as correlation of the target and speckle are naturally accounted for in the MMSE reconstruction algorithm. Thus, the reconstruction process unifies the interpolation and spatial compounding. Simulation results for synthetic US images are presented to demonstrate the excellent reconstruction.
A pilot study to evaluate assisted freehand ultrasound elasticity imaging in the sizing of early breast cancer: a comparison of B-mode and assisted freehand ultrasound elasticity ultrasound with histopathology measurements
R English, J Li, A Parker, D Roskell, RF Adams, V Parulekar, J Baldwin, Y Chi, A Noble
Breast Cancer Research , 2010, DOI: 10.1186/bcr2659
Abstract: Twenty-three patients with early breast cancer were recruited with ethical approval through the NHSBSP. B-mode ultrasound and AFUSON images were acquired in predefined planes. Pathology slices were taken in the corresponding longitudinal plane and were digitally scanned. Assessment of tumour dimensions, area and contour were made on B-mode, AFUSON and histopathology scans. The findings were correlated.Although there were significant limitations in this pilot study, the tumour dimension accuracy increased from 66% (B-mode alone) to 82% (AFUSON). Tumour area accuracy increased from 61% (B-mode alone) to 90% (AFUSON). Some AFUSON contour images showed a high visual correlation with the equivalent histopathology scans.This pilot study suggests that AFUSON may be useful in early breast cancer sizing. Further studies will be done to acquire more data and to address some of the shortfalls in the study.
Rigid Registration of Freehand 3D Ultrasound and CT-Scan Kidney Images  [PDF]
Antoine Leroy,Pierre Mozer,Yohan Payan,Jocelyne Troccaz
Physics , 2006,
Abstract: This paper presents a method to register a preoperative CT volume to a sparse set of intraoperative US slices. In the context of percutaneous renal puncture, the aim is to transfer a planning information to an intraoperative coordinate system. The spatial position of the US slices is measured by localizing a calibrated probe. Our method consists in optimizing a rigid 6 degree of freedom (DOF) transform by evaluating at each step the similarity between the set of US images and the CT volume. The images have been preprocessed in order to increase the relationship between CT and US pixels. Correlation Ratio turned out to be the most accurate and appropriate similarity measure to be used in a Powell-Brent minimization scheme. Results are compared to a standard rigid point-to-point registration involving segmentation, and discussed.
Intensity-Based Registration of Freehand 3D Ultrasound and CT-scan Images of the Kidney  [PDF]
Antoine Leroy,Pierre Mozer,Yohan Payan,Jocelyne Troccaz
Physics , 2007, DOI: 10.1007/s11548-007-0077-5
Abstract: This paper presents a method to register a pre-operative Computed-Tomography (CT) volume to a sparse set of intra-operative Ultra-Sound (US) slices. In the context of percutaneous renal puncture, the aim is to transfer planning information to an intra-operative coordinate system. The spatial position of the US slices is measured by optically localizing a calibrated probe. Assuming the reproducibility of kidney motion during breathing, and no deformation of the organ, the method consists in optimizing a rigid 6 Degree Of Freedom (DOF) transform by evaluating at each step the similarity between the set of US images and the CT volume. The correlation between CT and US images being naturally rather poor, the images have been preprocessed in order to increase their similarity. Among the similarity measures formerly studied in the context of medical image registration, Correlation Ratio (CR) turned out to be one of the most accurate and appropriate, particularly with the chosen non-derivative minimization scheme, namely Powell-Brent's. The resulting matching transforms are compared to a standard rigid surface registration involving segmentation, regarding both accuracy and repeatability. The obtained results are presented and discussed.
Eleven fetal echocardiographic planes using 4-dimensional ultrasound with spatio-temporal image correlation (STIC): a logical approach to fetal heart volume analysis
Surasak Jantarasaengaram, Kittipong Vairojanavong
Cardiovascular Ultrasound , 2010, DOI: 10.1186/1476-7120-8-41
Abstract: Fetal heart volume datasets were acquired by transverse acquisition from 200 normal fetuses at 15 to 40 weeks of gestation. Analysis of the volume datasets using the described technique to display 11 echocardiographic planes in the multiplanar display mode were performed offline.Volume datasets from 18 fetuses were excluded due to poor image resolution. The mean visualization rates for all echocardiographic planes at 15-17, 18-22, 23-27, 28-32 and 33-40 weeks of gestation fetuses were 85.6% (range 45.2-96.8%, N = 31), 92.9% (range 64.0-100%, N = 64), 93.4% (range 51.4-100%, N = 37), 88.7%(range 54.5-100%, N = 33) and 81.8% (range 23.5-100%, N = 17) respectively.Overall, the applied technique can favorably display the pertinent echocardiographic planes. Description of the presented method provides a logical approach to explore the fetal heart volumes.Fetal heart examination is based upon visualization of certain cross-sectional planes or views on conventional two-dimensional (2D) ultrasound scanning. The abdominal view, the four-chamber view, and both cardiac outflow tracts should be obtained at screening level[1]. Additional fetal cardiac views are crucial for the sequential segmental analysis to assess the connections and anatomical detail[2-6]. Unfortunately, the fetal heart is not only small but also beating at high rates. Fetal heart geometry is quite complex, so it needs the three-dimensional (3D) mental reconstructions to understand chambers-vessel spatial connections and relationships. Furthermore, directing the ultrasound beam in the correct plane is complicated by different fetal positions. Therefore, a specific training and a considerable scanning experience are required for an examiner to be able to display the pertinent fetal cardiac planes.Progress in diagnostic ultrasound using the volume ultrasound and spatio-temporal image correlation (STIC) technique enables examiners to generate a volume dataset of the fetal heart with cardiac motion. Along with th
Freehand Sketch Recognition Using Deep Features  [PDF]
Ravi Kiran Sarvadevabhatla,R. Venkatesh Babu
Computer Science , 2015,
Abstract: Freehand sketches often contain sparse visual detail. In spite of the sparsity, they are easily and consistently recognized by humans across cultures, languages and age groups. Therefore, analyzing such sparse sketches can aid our understanding of the neuro-cognitive processes involved in visual representation and recognition. In the recent past, Convolutional Neural Networks (CNNs) have emerged as a powerful framework for feature representation and recognition for a variety of image domains. However, the domain of sketch images has not been explored. This paper introduces a freehand sketch recognition framework based on "deep" features extracted from CNNs. We use two popular CNNs for our experiments -- Imagenet CNN and a modified version of LeNet CNN. We evaluate our recognition framework on a publicly available benchmark database containing thousands of freehand sketches depicting everyday objects. Our results are an improvement over the existing state-of-the-art accuracies by 3% - 11%. The effectiveness and relative compactness of our deep features also make them an ideal candidate for related problems such as sketch-based image retrieval. In addition, we provide a preliminary glimpse of how such features can help identify crucial attributes (e.g. object-parts) of the sketched objects.
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