Carotid artery B-mode ultrasound image segmentation based on morphology, geometry and gradient direction

NASA Astrophysics Data System (ADS)

Sunarya, I. Made Gede; Yuniarno, Eko Mulyanto; Purnomo, Mauridhi Hery; Sardjono, Tri Arief; Sunu, Ismoyo; Purnama, I. Ketut Eddy

2017-06-01

Carotid Artery (CA) is one of the vital organs in the human body. CA features that can be used are position, size and volume. Position feature can used to determine the preliminary initialization of the tracking. Examination of the CA features can use Ultrasound. Ultrasound imaging can be operated dependently by an skilled operator, hence there could be some differences in the images result obtained by two or more different operators. This can affect the process of determining of CA. To reduce the level of subjectivity among operators, it can determine the position of the CA automatically. In this study, the proposed method is to segment CA in B-Mode Ultrasound Image based on morphology, geometry and gradient direction. This study consists of three steps, the data collection, preprocessing and artery segmentation. The data used in this study were taken directly by the researchers and taken from the Brno university's signal processing lab database. Each data set contains 100 carotid artery B-Mode ultrasound image. Artery is modeled using ellipse with center c, major axis a and minor axis b. The proposed method has a high value on each data set, 97% (data set 1), 73 % (data set 2), 87% (data set 3). This segmentation results will then be used in the process of tracking the CA.

Segmentation of prostate biopsy needles in transrectal ultrasound images

NASA Astrophysics Data System (ADS)

Krefting, Dagmar; Haupt, Barbara; Tolxdorff, Thomas; Kempkensteffen, Carsten; Miller, Kurt

2007-03-01

Prostate cancer is the most common cancer in men. Tissue extraction at different locations (biopsy) is the gold-standard for diagnosis of prostate cancer. These biopsies are commonly guided by transrectal ultrasound imaging (TRUS). Exact location of the extracted tissue within the gland is desired for more specific diagnosis and provides better therapy planning. While the orientation and the position of the needle within clinical TRUS image are limited, the appearing length and visibility of the needle varies strongly. Marker lines are present and tissue inhomogeneities and deflection artefacts may appear. Simple intensity, gradient oder edge-detecting based segmentation methods fail. Therefore a multivariate statistical classificator is implemented. The independent feature model is built by supervised learning using a set of manually segmented needles. The feature space is spanned by common binary object features as size and eccentricity as well as imaging-system dependent features like distance and orientation relative to the marker line. The object extraction is done by multi-step binarization of the region of interest. The ROI is automatically determined at the beginning of the segmentation and marker lines are removed from the images. The segmentation itself is realized by scale-invariant classification using maximum likelihood estimation and Mahalanobis distance as discriminator. The technique presented here could be successfully applied in 94% of 1835 TRUS images from 30 tissue extractions. It provides a robust method for biopsy needle localization in clinical prostate biopsy TRUS images.

Evaluation metrics for bone segmentation in ultrasound

NASA Astrophysics Data System (ADS)

Lougheed, Matthew; Fichtinger, Gabor; Ungi, Tamas

2015-03-01

Tracked ultrasound is a safe alternative to X-ray for imaging bones. The interpretation of bony structures is challenging as ultrasound has no specific intensity characteristic of bones. Several image segmentation algorithms have been devised to identify bony structures. We propose an open-source framework that would aid in the development and comparison of such algorithms by quantitatively measuring segmentation performance in the ultrasound images. True-positive and false-negative metrics used in the framework quantify algorithm performance based on correctly segmented bone and correctly segmented boneless regions. Ground-truth for these metrics are defined manually and along with the corresponding automatically segmented image are used for the performance analysis. Manually created ground truth tests were generated to verify the accuracy of the analysis. Further evaluation metrics for determining average performance per slide and standard deviation are considered. The metrics provide a means of evaluating accuracy of frames along the length of a volume. This would aid in assessing the accuracy of the volume itself and the approach to image acquisition (positioning and frequency of frame). The framework was implemented as an open-source module of the 3D Slicer platform. The ground truth tests verified that the framework correctly calculates the implemented metrics. The developed framework provides a convenient way to evaluate bone segmentation algorithms. The implementation fits in a widely used application for segmentation algorithm prototyping. Future algorithm development will benefit by monitoring the effects of adjustments to an algorithm in a standard evaluation framework.

Interactive vs. automatic ultrasound image segmentation methods for staging hepatic lipidosis.

PubMed

Weijers, Gert; Starke, Alexander; Haudum, Alois; Thijssen, Johan M; Rehage, Jürgen; De Korte, Chris L

2010-07-01

The aim of this study was to test the hypothesis that automatic segmentation of vessels in ultrasound (US) images can produce similar or better results in grading fatty livers than interactive segmentation. A study was performed in postpartum dairy cows (N=151), as an animal model of human fatty liver disease, to test this hypothesis. Five transcutaneous and five intraoperative US liver images were acquired in each animal and a liverbiopsy was taken. In liver tissue samples, triacylglycerol (TAG) was measured by biochemical analysis and hepatic diseases other than hepatic lipidosis were excluded by histopathologic examination. Ultrasonic tissue characterization (UTC) parameters--Mean echo level, standard deviation (SD) of echo level, signal-to-noise ratio (SNR), residual attenuation coefficient (ResAtt) and axial and lateral speckle size--were derived using a computer-aided US (CAUS) protocol and software package. First, the liver tissue was interactively segmented by two observers. With increasing fat content, fewer hepatic vessels were visible in the ultrasound images and, therefore, a smaller proportion of the liver needed to be excluded from these images. Automatic-segmentation algorithms were implemented and it was investigated whether better results could be achieved than with the subjective and time-consuming interactive-segmentation procedure. The automatic-segmentation algorithms were based on both fixed and adaptive thresholding techniques in combination with a 'speckle'-shaped moving-window exclusion technique. All data were analyzed with and without postprocessing as contained in CAUS and with different automated-segmentation techniques. This enabled us to study the effect of the applied postprocessing steps on single and multiple linear regressions ofthe various UTC parameters with TAG. Improved correlations for all US parameters were found by using automatic-segmentation techniques. Stepwise multiple linear-regression formulas where derived and used

TU-A-9A-06: Semi-Automatic Segmentation of Skin Cancer in High-Frequency Ultrasound Images: Initial Comparison with Histology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Y; Li, X; Fishman, K

Purpose: In skin-cancer radiotherapy, the assessment of skin lesion is challenging, particularly with important features such as the depth and width hard to determine. The aim of this study is to develop interative segmentation method to delineate tumor boundary using high-frequency ultrasound images and to correlate the segmentation results with the histopathological tumor dimensions. Methods: We analyzed 6 patients who comprised a total of 10 skin lesions involving the face, scalp, and hand. The patient’s various skin lesions were scanned using a high-frequency ultrasound system (Episcan, LONGPORT, INC., PA, U.S.A), with a 30-MHz single-element transducer. The lateral resolution was 14.6more » micron and the axial resolution was 3.85 micron for the ultrasound image. Semiautomatic image segmentation was performed to extract the cancer region, using a robust statistics driven active contour algorithm. The corresponding histology images were also obtained after tumor resection and served as the reference standards in this study. Results: Eight out of the 10 lesions are successfully segmented. The ultrasound tumor delineation correlates well with the histology assessment, in all the measurements such as depth, size, and shape. The depths measured by the ultrasound have an average of 9.3% difference comparing with that in the histology images. The remaining 2 cases suffered from the situation of mismatching between pathology and ultrasound images. Conclusion: High-frequency ultrasound is a noninvasive, accurate and easy-accessible modality to image skin cancer. Our segmentation method, combined with high-frequency ultrasound technology, provides a promising tool to estimate the extent of the tumor to guide the radiotherapy procedure and monitor treatment response.« less

Synthetic aperture imaging in ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; Baxter, John S. H.; McLeod, A. Jonathan; Jayaranthe, Uditha L.; Chen, Elvis C. S.; Peters, Terry M.

2014-03-01

Ultrasound calibration allows for ultrasound images to be incorporated into a variety of interventional applica­ tions. Traditional Z- bar calibration procedures rely on wired phantoms with an a priori known geometry. The line fiducials produce small, localized echoes which are then segmented from an array of ultrasound images from different tracked probe positions. In conventional B-mode ultrasound, the wires at greater depths appear blurred and are difficult to segment accurately, limiting the accuracy of ultrasound calibration. This paper presents a novel ultrasound calibration procedure that takes advantage of synthetic aperture imaging to reconstruct high resolution ultrasound images at arbitrary depths. In these images, line fiducials are much more readily and accu­ rately segmented, leading to decreased calibration error. The proposed calibration technique is compared to one based on B-mode ultrasound. The fiducial localization error was improved from 0.21mm in conventional B-mode images to 0.15mm in synthetic aperture images corresponding to an improvement of 29%. This resulted in an overall reduction of calibration error from a target registration error of 2.00mm to 1.78mm, an improvement of 11%. Synthetic aperture images display greatly improved segmentation capabilities due to their improved resolution and interpretability resulting in improved calibration.

Semi-automatic breast ultrasound image segmentation based on mean shift and graph cuts.

PubMed

Zhou, Zhuhuang; Wu, Weiwei; Wu, Shuicai; Tsui, Po-Hsiang; Lin, Chung-Chih; Zhang, Ling; Wang, Tianfu

2014-10-01

Computerized tumor segmentation on breast ultrasound (BUS) images remains a challenging task. In this paper, we proposed a new method for semi-automatic tumor segmentation on BUS images using Gaussian filtering, histogram equalization, mean shift, and graph cuts. The only interaction required was to select two diagonal points to determine a region of interest (ROI) on an input image. The ROI image was shrunken by a factor of 2 using bicubic interpolation to reduce computation time. The shrunken image was smoothed by a Gaussian filter and then contrast-enhanced by histogram equalization. Next, the enhanced image was filtered by pyramid mean shift to improve homogeneity. The object and background seeds for graph cuts were automatically generated on the filtered image. Using these seeds, the filtered image was then segmented by graph cuts into a binary image containing the object and background. Finally, the binary image was expanded by a factor of 2 using bicubic interpolation, and the expanded image was processed by morphological opening and closing to refine the tumor contour. The method was implemented with OpenCV 2.4.3 and Visual Studio 2010 and tested for 38 BUS images with benign tumors and 31 BUS images with malignant tumors from different ultrasound scanners. Experimental results showed that our method had a true positive rate (TP) of 91.7%, a false positive (FP) rate of 11.9%, and a similarity (SI) rate of 85.6%. The mean run time on Intel Core 2.66 GHz CPU and 4 GB RAM was 0.49 ± 0.36 s. The experimental results indicate that the proposed method may be useful in BUS image segmentation. © The Author(s) 2014.

Mathematical models used in segmentation and fractal methods of 2-D ultrasound images

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Moraru, Luminita; Bibicu, Dorin

2012-11-01

Mathematical models are widely used in biomedical computing. The extracted data from images using the mathematical techniques are the "pillar" achieving scientific progress in experimental, clinical, biomedical, and behavioural researches. This article deals with the representation of 2-D images and highlights the mathematical support for the segmentation operation and fractal analysis in ultrasound images. A large number of mathematical techniques are suitable to be applied during the image processing stage. The addressed topics cover the edge-based segmentation, more precisely the gradient-based edge detection and active contour model, and the region-based segmentation namely Otsu method. Another interesting mathematical approach consists of analyzing the images using the Box Counting Method (BCM) to compute the fractal dimension. The results of the paper provide explicit samples performed by various combination of methods.

Diagnostic accuracy of ovarian cyst segmentation in B-mode ultrasound images

NASA Astrophysics Data System (ADS)

Bibicu, Dorin; Moraru, Luminita; Stratulat (Visan), Mirela

2013-11-01

Cystic and polycystic ovary syndrome is an endocrine disorder affecting women in the fertile age. The Moore Neighbor Contour, Watershed Method, Active Contour Models, and a recent method based on Active Contour Model with Selective Binary and Gaussian Filtering Regularized Level Set (ACM&SBGFRLS) techniques were used in this paper to detect the border of the ovarian cyst from echography images. In order to analyze the efficiency of the segmentation an original computer aided software application developed in MATLAB was proposed. The results of the segmentation were compared and evaluated against the reference contour manually delineated by a sonography specialist. Both the accuracy and time complexity of the segmentation tasks are investigated. The Fréchet distance (FD) as a similarity measure between two curves and the area error rate (AER) parameter as the difference between the segmented areas are used as estimators of the segmentation accuracy. In this study, the most efficient methods for the segmentation of the ovarian were analyzed cyst. The research was carried out on a set of 34 ultrasound images of the ovarian cyst.

Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure.

PubMed

Cunningham, Ryan J; Harding, Peter J; Loram, Ian D

2017-02-01

Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

Echogenicity based approach to detect, segment and track the common carotid artery in 2D ultrasound images.

PubMed

Narayan, Nikhil S; Marziliano, Pina

2015-08-01

Automatic detection and segmentation of the common carotid artery in transverse ultrasound (US) images of the thyroid gland play a vital role in the success of US guided intervention procedures. We propose in this paper a novel method to accurately detect, segment and track the carotid in 2D and 2D+t US images of the thyroid gland using concepts based on tissue echogenicity and ultrasound image formation. We first segment the hypoechoic anatomical regions of interest using local phase and energy in the input image. We then make use of a Hessian based blob like analysis to detect the carotid within the segmented hypoechoic regions. The carotid artery is segmented by making use of least squares ellipse fit for the edge points around the detected carotid candidate. Experiments performed on a multivendor dataset of 41 images show that the proposed algorithm can segment the carotid artery with high sensitivity (99.6 ±m 0.2%) and specificity (92.9 ±m 0.1%). Further experiments on a public database containing 971 images of the carotid artery showed that the proposed algorithm can achieve a detection accuracy of 95.2% with a 2% increase in performance when compared to the state-of-the-art method.

Segmentation of prostate from ultrasound images using level sets on active band and intensity variation across edges.

PubMed

Li, Xu; Li, Chunming; Fedorov, Andriy; Kapur, Tina; Yang, Xiaoping

2016-06-01

In this paper, the authors propose a novel efficient method to segment ultrasound images of the prostate with weak boundaries. Segmentation of the prostate from ultrasound images with weak boundaries widely exists in clinical applications. One of the most typical examples is the diagnosis and treatment of prostate cancer. Accurate segmentation of the prostate boundaries from ultrasound images plays an important role in many prostate-related applications such as the accurate placement of the biopsy needles, the assignment of the appropriate therapy in cancer treatment, and the measurement of the prostate volume. Ultrasound images of the prostate are usually corrupted with intensity inhomogeneities, weak boundaries, and unwanted edges, which make the segmentation of the prostate an inherently difficult task. Regarding to these difficulties, the authors introduce an active band term and an edge descriptor term in the modified level set energy functional. The active band term is to deal with intensity inhomogeneities and the edge descriptor term is to capture the weak boundaries or to rule out unwanted boundaries. The level set function of the proposed model is updated in a band region around the zero level set which the authors call it an active band. The active band restricts the authors' method to utilize the local image information in a banded region around the prostate contour. Compared to traditional level set methods, the average intensities inside∖outside the zero level set are only computed in this banded region. Thus, only pixels in the active band have influence on the evolution of the level set. For weak boundaries, they are hard to be distinguished by human eyes, but in local patches in the band region around prostate boundaries, they are easier to be detected. The authors incorporate an edge descriptor to calculate the total intensity variation in a local patch paralleled to the normal direction of the zero level set, which can detect weak boundaries

Segmentation of prostate from ultrasound images using level sets on active band and intensity variation across edges

PubMed Central

Li, Xu; Li, Chunming; Fedorov, Andriy; Kapur, Tina; Yang, Xiaoping

2016-01-01

Purpose: In this paper, the authors propose a novel efficient method to segment ultrasound images of the prostate with weak boundaries. Segmentation of the prostate from ultrasound images with weak boundaries widely exists in clinical applications. One of the most typical examples is the diagnosis and treatment of prostate cancer. Accurate segmentation of the prostate boundaries from ultrasound images plays an important role in many prostate-related applications such as the accurate placement of the biopsy needles, the assignment of the appropriate therapy in cancer treatment, and the measurement of the prostate volume. Methods: Ultrasound images of the prostate are usually corrupted with intensity inhomogeneities, weak boundaries, and unwanted edges, which make the segmentation of the prostate an inherently difficult task. Regarding to these difficulties, the authors introduce an active band term and an edge descriptor term in the modified level set energy functional. The active band term is to deal with intensity inhomogeneities and the edge descriptor term is to capture the weak boundaries or to rule out unwanted boundaries. The level set function of the proposed model is updated in a band region around the zero level set which the authors call it an active band. The active band restricts the authors’ method to utilize the local image information in a banded region around the prostate contour. Compared to traditional level set methods, the average intensities inside∖outside the zero level set are only computed in this banded region. Thus, only pixels in the active band have influence on the evolution of the level set. For weak boundaries, they are hard to be distinguished by human eyes, but in local patches in the band region around prostate boundaries, they are easier to be detected. The authors incorporate an edge descriptor to calculate the total intensity variation in a local patch paralleled to the normal direction of the zero level set, which can

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

PubMed

Rueda, Sylvia; Fathima, Sana; Knight, Caroline L; Yaqub, Mohammad; Papageorghiou, Aris T; Rahmatullah, Bahbibi; Foi, Alessandro; Maggioni, Matteo; Pepe, Antonietta; Tohka, Jussi; Stebbing, Richard V; McManigle, John E; Ciurte, Anca; Bresson, Xavier; Cuadra, Meritxell Bach; Sun, Changming; Ponomarev, Gennady V; Gelfand, Mikhail S; Kazanov, Marat D; Wang, Ching-Wei; Chen, Hsiang-Chou; Peng, Chun-Wei; Hung, Chu-Mei; Noble, J Alison

2014-04-01

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Feasibility of rotational scan ultrasound imaging by an angled high frequency transducer for the posterior segment of the eye.

PubMed

Paeng, Dong-Guk; Chang, Jin Ho; Chen, Ruimin; Humayun, Mark S; Shung, K Kirk

2009-03-01

High frequency ultrasound over 40 MHz has been used to image the anterior segment of the eye, but it is not suitable for the posterior segment due to the frequency dependent attenuation of ultrasound and thus the limitation of penetration depth. This paper proposes a novel scan method to image the posterior segment of the eye with an angled high frequency (beyond 40 MHz) ultrasound needle transducer. In this method, the needle transducer is inserted into the eye through a small incision hole (approximately 1 mm in diameter) and rotated around the axial direction to form a cone-shaped imaging plane, allowing the spatial information of retinal vessels and diagnosis of their occlusion to be displayed. The feasibility of this novel technique was tested with images of a wire phantom, a polyimide tube, and an excised pig eye obtained by manually rotating a 40-MHz PMN-PT needle transducer with a beveled tip of 45 degrees . From the results, we believe that rotational scan imaging will help expand the minimally invasive applications of high frequency ultrasound to other areas due to the capability of increased closeness of an angled needle transducer to structures of interest buried in other tissues.

A probability tracking approach to segmentation of ultrasound prostate images using weak shape priors

NASA Astrophysics Data System (ADS)

Xu, Robert S.; Michailovich, Oleg V.; Solovey, Igor; Salama, Magdy M. A.

2010-03-01

Prostate specific antigen density is an established parameter for indicating the likelihood of prostate cancer. To this end, the size and volume of the gland have become pivotal quantities used by clinicians during the standard cancer screening process. As an alternative to manual palpation, an increasing number of volume estimation methods are based on the imagery data of the prostate. The necessity to process large volumes of such data requires automatic segmentation algorithms, which can accurately and reliably identify the true prostate region. In particular, transrectal ultrasound (TRUS) imaging has become a standard means of assessing the prostate due to its safe nature and high benefit-to-cost ratio. Unfortunately, modern TRUS images are still plagued by many ultrasound imaging artifacts such as speckle noise and shadowing, which results in relatively low contrast and reduced SNR of the acquired images. Consequently, many modern segmentation methods incorporate prior knowledge about the prostate geometry to enhance traditional segmentation techniques. In this paper, a novel approach to the problem of TRUS segmentation, particularly the definition of the prostate shape prior, is presented. The proposed approach is based on the concept of distribution tracking, which provides a unified framework for tracking both photometric and morphological features of the prostate. In particular, the tracking of morphological features defines a novel type of "weak" shape priors. The latter acts as a regularization force, which minimally bias the segmentation procedure, while rendering the final estimate stable and robust. The value of the proposed methodology is demonstrated in a series of experiments.

Chest wall segmentation in automated 3D breast ultrasound scans.

PubMed

Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

Statistical Segmentation of Surgical Instruments in 3D Ultrasound Images

PubMed Central

Linguraru, Marius George; Vasilyev, Nikolay V.; Del Nido, Pedro J.; Howe, Robert D.

2008-01-01

The recent development of real-time 3D ultrasound enables intracardiac beating heart procedures, but the distorted appearance of surgical instruments is a major challenge to surgeons. In addition, tissue and instruments have similar gray levels in US images and the interface between instruments and tissue is poorly defined. We present an algorithm that automatically estimates instrument location in intracardiac procedures. Expert-segmented images are used to initialize the statistical distributions of blood, tissue and instruments. Voxels are labeled through an iterative expectation-maximization algorithm using information from the neighboring voxels through a smoothing kernel. Once the three classes of voxels are separated, additional neighboring information is combined with the known shape characteristics of instruments in order to correct for misclassifications. We analyze the major axis of segmented data through their principal components and refine the results by a watershed transform, which corrects the results at the contact between instrument and tissue. We present results on 3D in-vitro data from a tank trial, and 3D in-vivo data from cardiac interventions on porcine beating hearts, using instruments of four types of materials. The comparison of algorithm results to expert-annotated images shows the correct segmentation and position of the instrument shaft. PMID:17521802

Feasibility of Rotational Scan Ultrasound Imaging by an Angled High Frequency Transducer for the Posterior Segment of the Eye

PubMed Central

Paeng, Dong-Guk; Chang, Jin Ho; Chen, Ruimin; Humayun, Mark S.; Shung, K. Kirk

2009-01-01

High frequency ultrasound over 40 MHz has been used to image the anterior segment of the eye, but it is not suitable for the posterior segment due to the frequency-dependent attenuation of ultrasound and thus the limitation of penetration depth. This paper proposes a novel scan method to image the posterior segment of the eye with an angled high frequency (beyond 40 MHz) ultrasound needle transducer. In this method, the needle transducer is inserted into the eye through a small incision hole (∼1 mm in diameter) and rotated around the axial direction to form a cone-shaped imaging plane, allowing the spatial information of retinal vessels and diagnosis of their occlusion to be displayed. The feasibility of this novel technique was tested with images of a wire phantom, a polyimide tube, and an excised pig eye obtained by manually rotating a 40-MHz PMN-PT needle transducer with a beveled tip of 45°. From the results, we believe that rotational scan imaging will help expand the minimally invasive applications of high frequency ultrasound to other areas due to the capability of increased closeness of an angled needle transducer to structures of interest buried in other tissues. PMID:19411226

Comparison of thyroid segmentation techniques for 3D ultrasound

NASA Astrophysics Data System (ADS)

Wunderling, T.; Golla, B.; Poudel, P.; Arens, C.; Friebe, M.; Hansen, C.

2017-02-01

The segmentation of the thyroid in ultrasound images is a field of active research. The thyroid is a gland of the endocrine system and regulates several body functions. Measuring the volume of the thyroid is regular practice of diagnosing pathological changes. In this work, we compare three approaches for semi-automatic thyroid segmentation in freehand-tracked three-dimensional ultrasound images. The approaches are based on level set, graph cut and feature classification. For validation, sixteen 3D ultrasound records were created with ground truth segmentations, which we make publicly available. The properties analyzed are the Dice coefficient when compared against the ground truth reference and the effort of required interaction. Our results show that in terms of Dice coefficient, all algorithms perform similarly. For interaction, however, each algorithm has advantages over the other. The graph cut-based approach gives the practitioner direct influence on the final segmentation. Level set and feature classifier require less interaction, but offer less control over the result. All three compared methods show promising results for future work and provide several possible extensions.

Automatic ultrasound image enhancement for 2D semi-automatic breast-lesion segmentation

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Hall, Christopher S.

2014-03-01

Breast cancer is the fastest growing cancer, accounting for 29%, of new cases in 2012, and second leading cause of cancer death among women in the United States and worldwide. Ultrasound (US) has been used as an indispensable tool for breast cancer detection/diagnosis and treatment. In computer-aided assistance, lesion segmentation is a preliminary but vital step, but the task is quite challenging in US images, due to imaging artifacts that complicate detection and measurement of the suspect lesions. The lesions usually present with poor boundary features and vary significantly in size, shape, and intensity distribution between cases. Automatic methods are highly application dependent while manual tracing methods are extremely time consuming and have a great deal of intra- and inter- observer variability. Semi-automatic approaches are designed to counterbalance the advantage and drawbacks of the automatic and manual methods. However, considerable user interaction might be necessary to ensure reasonable segmentation for a wide range of lesions. This work proposes an automatic enhancement approach to improve the boundary searching ability of the live wire method to reduce necessary user interaction while keeping the segmentation performance. Based on the results of segmentation of 50 2D breast lesions in US images, less user interaction is required to achieve desired accuracy, i.e. < 80%, when auto-enhancement is applied for live-wire segmentation.

Measurement of segmental lumbar spine flexion and extension using ultrasound imaging.

PubMed

Chleboun, Gary S; Amway, Matthew J; Hill, Jesse G; Root, Kara J; Murray, Hugh C; Sergeev, Alexander V

2012-10-01

Clinical measurement, technical note. To describe a technique to measure interspinous process distance using ultrasound (US) imaging, to assess the reliability of the technique, and to compare the US imaging measurements to magnetic resonance imaging (MRI) measurements in 3 different positions of the lumbar spine. Segmental spinal motion has been assessed using various imaging techniques, as well as surgically inserted pins. However, some imaging techniques are costly (MRI) and some require ionizing radiation (radiographs and fluoroscopy), and surgical procedures have limited use because of the invasive nature of the technique. Therefore, it is important to have an easily accessible and inexpensive technique for measuring lumbar segmental motion to more fully understand spine motion in vivo, to evaluate the changes that occur with various interventions, and to be able to accurately relate the changes in symptoms to changes in motion of individual vertebral segments. Six asymptomatic subjects participated. The distance between spinous processes at each lumbar segment (L1-2, L2-3, L3-4, L4-5) was measured digitally using MRI and US imaging. The interspinous distance was measured with subjects supine and the lumbar spine in 3 different positions (resting, lumbar flexion, and lumbar extension) for both MRI and US imaging. The differences in distance from neutral to extension, neutral to flexion, and extension to flexion were calculated. The measurement methods had excellent reliability for US imaging (intraclass correlation coefficient [ICC3,3] = 0.94; 95% confidence interval: 0.85, 0.97) and MRI (ICC3,3 = 0.98; 95% confidence interval: 0.95, 0.99). The distance measured was similar between US imaging and MRI (P>.05), except at L3-4 flexion-extension (P = .003). On average, the MRI measurements were 1.3 mm greater than the US imaging measurements. This study describes a new method for the measurement of lumbar spine segmental flexion and extension motion using US

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

A state-of-the-art review on segmentation algorithms in intravascular ultrasound (IVUS) images.

PubMed

Katouzian, Amin; Angelini, Elsa D; Carlier, Stéphane G; Suri, Jasjit S; Navab, Nassir; Laine, Andrew F

2012-09-01

Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.

Automatic segmentation of right ventricular ultrasound images using sparse matrix transform and a level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Fei, Baowei

2013-11-01

An automatic segmentation framework is proposed to segment the right ventricle (RV) in echocardiographic images. The method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform, a training model, and a localized region-based level set. First, the sparse matrix transform extracts main motion regions of the myocardium as eigen-images by analyzing the statistical information of the images. Second, an RV training model is registered to the eigen-images in order to locate the position of the RV. Third, the training model is adjusted and then serves as an optimized initialization for the segmentation of each image. Finally, based on the initializations, a localized, region-based level set algorithm is applied to segment both epicardial and endocardial boundaries in each echocardiograph. Three evaluation methods were used to validate the performance of the segmentation framework. The Dice coefficient measures the overall agreement between the manual and automatic segmentation. The absolute distance and the Hausdorff distance between the boundaries from manual and automatic segmentation were used to measure the accuracy of the segmentation. Ultrasound images of human subjects were used for validation. For the epicardial and endocardial boundaries, the Dice coefficients were 90.8 ± 1.7% and 87.3 ± 1.9%, the absolute distances were 2.0 ± 0.42 mm and 1.79 ± 0.45 mm, and the Hausdorff distances were 6.86 ± 1.71 mm and 7.02 ± 1.17 mm, respectively. The automatic segmentation method based on a sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Automatic needle segmentation in 3D ultrasound images using 3D Hough transform

NASA Astrophysics Data System (ADS)

Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgeng

2007-12-01

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using an RF button electrode which is needle-like is being used to destroy tumor cells or stop bleeding currently. Now a 3D US guidance system has been developed to avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment. In this paper, we described two automated techniques, the 3D Hough Transform (3DHT) and the 3D Randomized Hough Transform (3DRHT), which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance. Based on the representation (Φ , θ , ρ , α ) of straight lines in 3D space, we used the 3DHT algorithm to segment needles successfully assumed that the approximate needle position and orientation are known in priori. The 3DRHT algorithm was developed to detect needles quickly without any information of the 3D US images. The needle segmentation techniques were evaluated using the 3D US images acquired by scanning water phantoms. The experiments demonstrated the feasibility of two 3D needle segmentation algorithms described in this paper.

Using trainable segmentation and watershed transform for identifying unilocular and multilocular cysts from ultrasound images of ovarian tumour

NASA Astrophysics Data System (ADS)

Ibrahim, Dheyaa Ahmed; Al-Assam, Hisham; Du, Hongbo; Jassim, Sabah

2017-05-01

Ovarian masses are categorised into different types of malignant and benign. In order to optimize patient treatment, it is necessary to carry out pre-operational characterisation of the suspect ovarian mass to determine its category. Ultrasound imaging has been widely used in differentiating malignant from benign cases due to its safe and non-intrusive nature, and can be used for determining the number of cysts in the ovary. Presently, the gynaecologist is tasked with manually counting the number of cysts shown on the ultrasound image. This paper proposes, a new approach that automatically segments the ovarian masses and cysts from a static B-mode image. Initially, the method uses a trainable segmentation procedure and a trained neural network classifier to accurately identify the position of the masses and cysts. After that, the borders of the masses can be appraised using watershed transform. The effectiveness of the proposed method has been tested by comparing the number of cysts identified by the method against the manual examination by a gynaecologist. A total of 65 ultrasound images were used for the comparison, and the results showed that the proposed solution is a viable alternative to the manual counting method for accurately determining the number of cysts in a US ovarian image.

75 MHz Ultrasound Biomicroscopy of Anterior Segment of Eye

PubMed Central

Silverman, Ronald H.; Cannata, Jonathan; Shung, K. Kirk; Gal, Omer; Patel, Monica; Lloyd, Harriet O.; Feleppa, Ernest J.; Coleman, D. Jackson

2006-01-01

Very high frequency ultrasound (35–50 MHz) has had a significant impact upon clinical imaging of the anterior segment of the eye, offering an axial resolution as small as 30 μm. Higher frequencies, while potentially offering even finer resolution, are more affected by absorption in ocular tissues and even in the fluid coupling medium. Our aim was to develop and apply improved transducer technology utilizing frequencies beyond those routinely used for ultrasound biomicroscopy of the eye. A 75-MHz lithium niobate transducer with 2 mm aperture and 6 mm focal length was fabricated. We scanned the ciliary body and cornea of a human eye six years post-LASIK. Spectral parameter images were produced from the midband fit to local calibrated power spectra. Images were compared with those produced using a 35 MHz lithium niobate transducer of similar fractional bandwidth and focal ratio. The 75-MHz transducer was found to have a fractional bandwidth (−6 dB) of 61%. Images of the post-LASIK cornea showed higher stromal backscatter at 75 MHz than at 35 MHz. The improved lateral resolution resulted in better visualization of discontinuities in Bowman’s layer, indicative of microfolds or breaks occurring at the time of surgery. The LASIK surface was evident as a discontinuity in stromal backscatter between the stromal component of the flap and the residual stroma. The iris and ciliary body were visualized despite attenuation by the overlying sclera. Very high frequency ultrasound imaging of the anterior segment of the eye has been restricted to the 35–50 MHz band for over a decade. We showed that higher frequencies can be used in vivo to image the cornea and anterior segment. This improvement in resolution and high sensitivity to backscatter from the corneal stroma will provide benefits in clinical diagnostic imaging of the anterior segment. PMID:17147058

75 MHz ultrasound biomicroscopy of anterior segment of eye.

PubMed

Silverman, Ronald H; Cannata, Jonathan; Shung, K Kirk; Gal, Omer; Patel, Monica; Lloyd, Harriet O; Feleppa, Ernest J; Coleman, D Jackson

2006-07-01

Very high frequency ultrasound (35-50 MHz) has had a significant impact upon clinical imaging of the anterior segment of the eye, offering an axial resolution as small as 30 microm. Higher frequencies, while potentially offering even finer resolution, are more affected by absorption in ocular tissues and even in the fluid coupling medium. Our aim was to develop and apply improved transducer technology utilizing frequencies beyond those routinely used for ultrasound biomicroscopy of the eye. A 75-MHz lithium niobate transducer with 2 mm aperture and 6 mm focal length was fabricated. We scanned the ciliary body and cornea of a human eye six years post-LASIK. Spectral parameter images were produced from the midband fit to local calibrated power spectra. Images were compared with those produced using a 35 MHz lithium niobate transducer of similar fractional bandwidth and focal ratio. The 75-MHz transducer was found to have a fractional bandwidth (-6 dB) of 61%. Images of the post-LASIK cornea showed higher stromal backscatter at 75 MHz than at 35 MHz. The improved lateral resolution resulted in better visualization of discontinuities in Bowman's layer, indicative of microfolds or breaks occurring at the time of surgery. The LASIK surface was evident as a discontinuity in stromal backscatter between the stromal component of the flap and the residual stroma. The iris and ciliary body were visualized despite attenuation by the overlying sclera. Very high frequency ultrasound imaging of the anterior segment of the eye has been restricted to the 35-50 MHz band for over a decade. We showed that higher frequencies can be used in vivo to image the cornea and anterior segment. This improvement in resolution and high sensitivity to backscatter from the corneal stroma will provide benefits in clinical diagnostic imaging of the anterior segment.

Automatic segmentation of right ventricle on ultrasound images using sparse matrix transform and level set

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Halig, Luma V.; Fei, Baowei

2013-03-01

An automatic framework is proposed to segment right ventricle on ultrasound images. This method can automatically segment both epicardial and endocardial boundaries from a continuous echocardiography series by combining sparse matrix transform (SMT), a training model, and a localized region based level set. First, the sparse matrix transform extracts main motion regions of myocardium as eigenimages by analyzing statistical information of these images. Second, a training model of right ventricle is registered to the extracted eigenimages in order to automatically detect the main location of the right ventricle and the corresponding transform relationship between the training model and the SMT-extracted results in the series. Third, the training model is then adjusted as an adapted initialization for the segmentation of each image in the series. Finally, based on the adapted initializations, a localized region based level set algorithm is applied to segment both epicardial and endocardial boundaries of the right ventricle from the whole series. Experimental results from real subject data validated the performance of the proposed framework in segmenting right ventricle from echocardiography. The mean Dice scores for both epicardial and endocardial boundaries are 89.1%+/-2.3% and 83.6+/-7.3%, respectively. The automatic segmentation method based on sparse matrix transform and level set can provide a useful tool for quantitative cardiac imaging.

Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

NASA Astrophysics Data System (ADS)

Reyes López, Misael; Arámbula Cosío, Fernando

2017-11-01

The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images.

PubMed

Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Mulder, Harriët W; Ren, Ben; Kirişli, Hortense A; Metz, Coert; van Burken, Gerard; van Stralen, Marijn; Pluim, Josien P W; van der Steen, Antonius F W; van Walsum, Theo; Bosch, Johannes G

2015-06-01

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations. Dice coefficients and point-to-surface distances were used to determine segmentation accuracy. ASM segmentations were successful in 19 of 20 cases. The median Dice coefficient for all successful segmentations versus the average observer ranged from 90% to 71% compared with an inter-observer range of 95% to 84%. The

Breast ultrasound image segmentation: an optimization approach based on super-pixels and high-level descriptors

NASA Astrophysics Data System (ADS)

Massich, Joan; Lemaître, Guillaume; Martí, Joan; Mériaudeau, Fabrice

2015-04-01

Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the breast are essential for CAD systems in order to extract information needed to perform diagnosis. This article proposes a highly modular and flexible framework for segmenting lesions and tissues present in BUS images. The proposal takes advantage of optimization strategies using super-pixels and high-level descriptors, which are analogous to the visual cues used by radiologists. Qualitative and quantitative results are provided stating a performance within the range of the state-of-the-art.

Preliminary results in large bone segmentation from 3D freehand ultrasound

NASA Astrophysics Data System (ADS)

Fanti, Zian; Torres, Fabian; Arámbula Cosío, Fernando

2013-11-01

Computer Assisted Orthopedic Surgery (CAOS) requires a correct registration between the patient in the operating room and the virtual models representing the patient in the computer. In order to increase the precision and accuracy of the registration a set of new techniques that eliminated the need to use fiducial markers have been developed. The majority of these newly developed registration systems are based on costly intraoperative imaging systems like Computed Tomography (CT scan) or Magnetic resonance imaging (MRI). An alternative to these methods is the use of an Ultrasound (US) imaging system for the implementation of a more cost efficient intraoperative registration solution. In order to develop the registration solution with the US imaging system, the bone surface is segmented in both preoperative and intraoperative images, and the registration is done using the acquire surface. In this paper, we present the a preliminary results of a new approach to segment bone surface from ultrasound volumes acquired by means 3D freehand ultrasound. The method is based on the enhancement of the voxels that belongs to surface and its posterior segmentation. The enhancement process is based on the information provided by eigenanalisis of the multiscale 3D Hessian matrix. The preliminary results shows that from the enhance volume the final bone surfaces can be extracted using a singular value thresholding.

3D segmentation of kidney tumors from freehand 2D ultrasound

NASA Astrophysics Data System (ADS)

Ahmad, Anis; Cool, Derek; Chew, Ben H.; Pautler, Stephen E.; Peters, Terry M.

2006-03-01

To completely remove a tumor from a diseased kidney, while minimizing the resection of healthy tissue, the surgeon must be able to accurately determine its location, size and shape. Currently, the surgeon mentally estimates these parameters by examining pre-operative Computed Tomography (CT) images of the patient's anatomy. However, these images do not reflect the state of the abdomen or organ during surgery. Furthermore, these images can be difficult to place in proper clinical context. We propose using Ultrasound (US) to acquire images of the tumor and the surrounding tissues in real-time, then segmenting these US images to present the tumor as a three dimensional (3D) surface. Given the common use of laparoscopic procedures that inhibit the range of motion of the operator, we propose segmenting arbitrarily placed and oriented US slices individually using a tracked US probe. Given the known location and orientation of the US probe, we can assign 3D coordinates to the segmented slices and use them as input to a 3D surface reconstruction algorithm. We have implemented two approaches for 3D segmentation from freehand 2D ultrasound. Each approach was evaluated on a tissue-mimicking phantom of a kidney tumor. The performance of our approach was determined by measuring RMS surface error between the segmentation and the known gold standard and was found to be below 0.8 mm.

Automatic needle segmentation in 3D ultrasound images using 3D improved Hough transform

NASA Astrophysics Data System (ADS)

Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgen

2008-03-01

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using a needle-like RF button electrode is widely used to destroy tumor cells or stop bleeding. To avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment, 3D US guidance system was developed. In this paper, a new automated technique, the 3D Improved Hough Transform (3DIHT) algorithm, which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance, was presented. Based on the coarse-fine search strategy and a four parameter representation of lines in 3D space, 3DIHT algorithm can segment needles quickly, accurately and robustly. The technique was evaluated using the 3D US images acquired by scanning a water phantom. The segmentation position deviation of the line was less than 2mm and angular deviation was much less than 2°. The average computational time measured on a Pentium IV 2.80GHz PC computer with a 381×381×250 image was less than 2s.

Dynamic programming in parallel boundary detection with application to ultrasound intima-media segmentation.

PubMed

Zhou, Yuan; Cheng, Xinyao; Xu, Xiangyang; Song, Enmin

2013-12-01

Segmentation of carotid artery intima-media in longitudinal ultrasound images for measuring its thickness to predict cardiovascular diseases can be simplified as detecting two nearly parallel boundaries within a certain distance range, when plaque with irregular shapes is not considered. In this paper, we improve the implementation of two dynamic programming (DP) based approaches to parallel boundary detection, dual dynamic programming (DDP) and piecewise linear dual dynamic programming (PL-DDP). Then, a novel DP based approach, dual line detection (DLD), which translates the original 2-D curve position to a 4-D parameter space representing two line segments in a local image segment, is proposed to solve the problem while maintaining efficiency and rotation invariance. To apply the DLD to ultrasound intima-media segmentation, it is imbedded in a framework that employs an edge map obtained from multiplication of the responses of two edge detectors with different scales and a coupled snake model that simultaneously deforms the two contours for maintaining parallelism. The experimental results on synthetic images and carotid arteries of clinical ultrasound images indicate improved performance of the proposed DLD compared to DDP and PL-DDP, with respect to accuracy and efficiency. Copyright © 2013 Elsevier B.V. All rights reserved.

A Dynamic Graph Cuts Method with Integrated Multiple Feature Maps for Segmenting Kidneys in 2D Ultrasound Images.

PubMed

Zheng, Qiang; Warner, Steven; Tasian, Gregory; Fan, Yong

2018-02-12

Automatic segmentation of kidneys in ultrasound (US) images remains a challenging task because of high speckle noise, low contrast, and large appearance variations of kidneys in US images. Because texture features may improve the US image segmentation performance, we propose a novel graph cuts method to segment kidney in US images by integrating image intensity information and texture feature maps. We develop a new graph cuts-based method to segment kidney US images by integrating original image intensity information and texture feature maps extracted using Gabor filters. To handle large appearance variation within kidney images and improve computational efficiency, we build a graph of image pixels close to kidney boundary instead of building a graph of the whole image. To make the kidney segmentation robust to weak boundaries, we adopt localized regional information to measure similarity between image pixels for computing edge weights to build the graph of image pixels. The localized graph is dynamically updated and the graph cuts-based segmentation iteratively progresses until convergence. Our method has been evaluated based on kidney US images of 85 subjects. The imaging data of 20 randomly selected subjects were used as training data to tune parameters of the image segmentation method, and the remaining data were used as testing data for validation. Experiment results demonstrated that the proposed method obtained promising segmentation results for bilateral kidneys (average Dice index = 0.9446, average mean distance = 2.2551, average specificity = 0.9971, average accuracy = 0.9919), better than other methods under comparison (P < .05, paired Wilcoxon rank sum tests). The proposed method achieved promising performance for segmenting kidneys in two-dimensional US images, better than segmentation methods built on any single channel of image information. This method will facilitate extraction of kidney characteristics that may predict important

A deep learning approach for real time prostate segmentation in freehand ultrasound guided biopsy.

PubMed

Anas, Emran Mohammad Abu; Mousavi, Parvin; Abolmaesumi, Purang

2018-06-01

Targeted prostate biopsy, incorporating multi-parametric magnetic resonance imaging (mp-MRI) and its registration with ultrasound, is currently the state-of-the-art in prostate cancer diagnosis. The registration process in most targeted biopsy systems today relies heavily on accurate segmentation of ultrasound images. Automatic or semi-automatic segmentation is typically performed offline prior to the start of the biopsy procedure. In this paper, we present a deep neural network based real-time prostate segmentation technique during the biopsy procedure, hence paving the way for dynamic registration of mp-MRI and ultrasound data. In addition to using convolutional networks for extracting spatial features, the proposed approach employs recurrent networks to exploit the temporal information among a series of ultrasound images. One of the key contributions in the architecture is to use residual convolution in the recurrent networks to improve optimization. We also exploit recurrent connections within and across different layers of the deep networks to maximize the utilization of the temporal information. Furthermore, we perform dense and sparse sampling of the input ultrasound sequence to make the network robust to ultrasound artifacts. Our architecture is trained on 2,238 labeled transrectal ultrasound images, with an additional 637 and 1,017 unseen images used for validation and testing, respectively. We obtain a mean Dice similarity coefficient of 93%, a mean surface distance error of 1.10 mm and a mean Hausdorff distance error of 3.0 mm. A comparison of the reported results with those of a state-of-the-art technique indicates statistically significant improvement achieved by the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

[An integrated segmentation method for 3D ultrasound carotid artery].

PubMed

Yang, Xin; Wu, Huihui; Liu, Yang; Xu, Hongwei; Liang, Huageng; Cai, Wenjuan; Fang, Mengjie; Wang, Yujie

2013-07-01

An integrated segmentation method for 3D ultrasound carotid artery was proposed. 3D ultrasound image was sliced into transverse, coronal and sagittal 2D images on the carotid bifurcation point. Then, the three images were processed respectively, and the carotid artery contours and thickness were obtained finally. This paper tries to overcome the disadvantages of current computer aided diagnosis method, such as high computational complexity, easily introduced subjective errors et al. The proposed method could get the carotid artery overall information rapidly, accurately and completely. It could be transplanted into clinical usage for atherosclerosis diagnosis and prevention.

Segmentation of common carotid artery with active appearance models from ultrasound images

NASA Astrophysics Data System (ADS)

Yang, Xin; He, Wanji; Fenster, Aaron; Yuchi, Ming; Ding, Mingyue

2013-02-01

Carotid atherosclerosis is a major cause of stroke, a leading cause of death and disability. In this paper, a new segmentation method is proposed and evaluated for outlining the common carotid artery (CCA) from transverse view images, which were sliced from three-dimensional ultrasound (3D US) of 1mm inter-slice distance (ISD), to support the monitoring and assessment of carotid atherosclerosis. The data set consists of forty-eight 3D US images acquired from both left and right carotid arteries of twelve patients in two time points who had carotid stenosis of 60% or more at the baseline. The 3D US data were collected at baseline and three-month follow-up, where seven treated with 80mg atorvastatin and five with placebo. The baseline manual boundaries were used for Active Appearance Models (AAM) training; while the treatment data for segmentation testing and evaluation. The segmentation results were compared with experts manually outlined boundaries, as a surrogate for ground truth, for further evaluation. For the adventitia and lumen segmentations, the algorithm yielded Dice Coefficients (DC) of 92.06%+/-2.73% and 89.67%+/-3.66%, mean absolute distances (MAD) of 0.28+/-0.18 mm and 0.22+/-0.16 mm, maximum absolute distances (MAXD) of 0.71+/-0.28 mm and 0.59+/-0.21 mm, respectively. The segmentation results were also evaluated via Pratt's figure of merit (FOM) with the value of 0.61+/-0.06 and 0.66+/-0.05, which provides a quantitative measure for judging the similarity. Experimental results indicate that the proposed method can promote the carotid 3D US usage for a fast, safe and economical monitoring of the atherosclerotic disease progression and regression during therapy.

Endoscopic ultrasound description of liver segmentation and anatomy.

PubMed

Bhatia, Vikram; Hijioka, Susumu; Hara, Kazuo; Mizuno, Nobumasa; Imaoka, Hiroshi; Yamao, Kenji

2014-05-01

Endoscopic ultrasound (EUS) can demonstrate the detailed anatomy of the liver from the transgastric and transduodenal routes. Most of the liver segments can be imaged with EUS, except the right posterior segments. The intrahepatic vascular landmarks include the major hepatic veins, portal vein radicals, hepatic arterial branches, and the inferior vena cava, and the venosum and teres ligaments are other important intrahepatic landmarks. The liver hilum and gallbladder serve as useful surface landmarks. Deciphering liver segmentation and anatomy by EUS requires orienting the scan planes with these landmarkstructures, and is different from the static cross-sectional radiological images. Orientation during EUS requires appreciation of the numerous scan planes possible in real-time, and the direction of scanning from the stomach and duodenal bulb. We describe EUS imaging of the liver with a curved linear probe in a step-by-step approach, with the relevant anatomical details, potential applications, and pitfalls of this novel EUS application. © 2013 The Authors. Digestive Endoscopy © 2013 Japan Gastroenterological Endoscopy Society.

Semi-automated segmentation of the prostate gland boundary in ultrasound images using a machine learning approach

NASA Astrophysics Data System (ADS)

Diaz, Kristians; Castaneda, Benjamin

2008-03-01

This paper presents a semi-automated algorithm for prostate boundary segmentation from three-dimensional (3D) ultrasound (US) images. The US volume is sampled into 72 slices which go through the center of the prostate gland and are separated at a uniform angular spacing of 2.5 degrees. The approach requires the user to select four points from slices (at 0, 45, 90 and 135 degrees) which are used to initialize a discrete dynamic contour (DDC) algorithm. 4 Support Vector Machines (SVMs) are trained over the output of the DDC and classify the rest of the slices. The output of the SVMs is refined using binary morphological operations and DDC to produce the final result. The algorithm was tested on seven ex vivo 3D US images of prostate glands embedded in an agar mold. Results show good agreement with manual segmentation.

Segmentation of the lumen and media-adventitia boundaries of the common carotid artery from 3D ultrasound images

NASA Astrophysics Data System (ADS)

Ukwatta, E.; Awad, J.; Ward, A. D.; Samarabandu, J.; Krasinski, A.; Parraga, G.; Fenster, A.

2011-03-01

Three-dimensional ultrasound (3D US) vessel wall volume (VWV) measurements provide high measurement sensitivity and reproducibility for the monitoring and assessment of carotid atherosclerosis. In this paper, we describe a semiautomated approach based on the level set method to delineate the media-adventitia and lumen boundaries of the common carotid artery from 3D US images to support the computation of VWV. Due to the presence of plaque and US image artifacts, the carotid arteries are challenging to segment using image information alone. Our segmentation framework combines several image cues with domain knowledge and limited user interaction. Our method was evaluated with respect to manually outlined boundaries on 430 2D US images extracted from 3D US images of 30 patients who have carotid stenosis of 60% or more. The VWV given by our method differed from that given by manual segmentation by 6.7% +/- 5.0%. For the media-adventitia and lumen segmentations, respectively, our method yielded Dice coefficients of 95.2% +/- 1.6%, 94.3% +/- 2.6%, mean absolute distances of 0.3 +/- 0.1 mm, 0.2 +/- 0.1 mm, maximum absolute distances of 0.8 +/- 0.4 mm, 0.6 +/- 0.3 mm, and volume differences of 4.2% +/- 3.1%, 3.4% +/- 2.6%. The realization of a semi-automated segmentation method will accelerate the translation of 3D carotid US to clinical care for the rapid, non-invasive, and economical monitoring of atherosclerotic disease progression and regression during therapy.

An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images.

PubMed

Feng, Yuan; Dong, Fenglin; Xia, Xiaolong; Hu, Chun-Hong; Fan, Qianmin; Hu, Yanle; Gao, Mingyuan; Mutic, Sasa

2017-07-01

Ultrasound (US) imaging has been widely used in breast tumor diagnosis and treatment intervention. Automatic delineation of the tumor is a crucial first step, especially for the computer-aided diagnosis (CAD) and US-guided breast procedure. However, the intrinsic properties of US images such as low contrast and blurry boundaries pose challenges to the automatic segmentation of the breast tumor. Therefore, the purpose of this study is to propose a segmentation algorithm that can contour the breast tumor in US images. To utilize the neighbor information of each pixel, a Hausdorff distance based fuzzy c-means (FCM) method was adopted. The size of the neighbor region was adaptively updated by comparing the mutual information between them. The objective function of the clustering process was updated by a combination of Euclid distance and the adaptively calculated Hausdorff distance. Segmentation results were evaluated by comparing with three experts' manual segmentations. The results were also compared with a kernel-induced distance based FCM with spatial constraints, the method without adaptive region selection, and conventional FCM. Results from segmenting 30 patient images showed the adaptive method had a value of sensitivity, specificity, Jaccard similarity, and Dice coefficient of 93.60 ± 5.33%, 97.83 ± 2.17%, 86.38 ± 5.80%, and 92.58 ± 3.68%, respectively. The region-based metrics of average symmetric surface distance (ASSD), root mean square symmetric distance (RMSD), and maximum symmetric surface distance (MSSD) were 0.03 ± 0.04 mm, 0.04 ± 0.03 mm, and 1.18 ± 1.01 mm, respectively. All the metrics except sensitivity were better than that of the non-adaptive algorithm and the conventional FCM. Only three region-based metrics were better than that of the kernel-induced distance based FCM with spatial constraints. Inclusion of the pixel neighbor information adaptively in segmenting US images improved the segmentation performance. The results demonstrate the

Segmentation of images of abdominal organs.

PubMed

Wu, Jie; Kamath, Markad V; Noseworthy, Michael D; Boylan, Colm; Poehlman, Skip

2008-01-01

Abdominal organ segmentation, which is, the delineation of organ areas in the abdomen, plays an important role in the process of radiological evaluation. Attempts to automate segmentation of abdominal organs will aid radiologists who are required to view thousands of images daily. This review outlines the current state-of-the-art semi-automated and automated methods used to segment abdominal organ regions from computed tomography (CT), magnetic resonance imaging (MEI), and ultrasound images. Segmentation methods generally fall into three categories: pixel based, region based and boundary tracing. While pixel-based methods classify each individual pixel, region-based methods identify regions with similar properties. Boundary tracing is accomplished by a model of the image boundary. This paper evaluates the effectiveness of the above algorithms with an emphasis on their advantages and disadvantages for abdominal organ segmentation. Several evaluation metrics that compare machine-based segmentation with that of an expert (radiologist) are identified and examined. Finally, features based on intensity as well as the texture of a small region around a pixel are explored. This review concludes with a discussion of possible future trends for abdominal organ segmentation.

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Bidirectional segmentation of prostate capsule from ultrasound volumes: an improved strategy

NASA Astrophysics Data System (ADS)

Wei, Liyang; Narayanan, Ramkrishnan; Kumar, Dinesh; Fenster, Aaron; Barqawi, Albaha; Werahera, Priya; Crawford, E. David; Suri, Jasjit S.

2008-03-01

Prostate volume is an indirect indicator for several prostate diseases. Volume estimation is a desired requirement during prostate biopsy, therapy and clinical follow up. Image segmentation is thus necessary. Previously, discrete dynamic contour (DDC) was implemented in orthogonal unidirectional on the slice-by-slice basis for prostate boundary estimation. This suffered from the glitch that it needed stopping criteria during the propagation of segmentation procedure from slice-to-slice. To overcome this glitch, axial DDC was implemented and this suffered from the fact that central axis never remains fixed and wobbles during propagation of segmentation from slice-to-slice. The effect of this was a multi-fold reconstructed surface. This paper presents a bidirectional DDC approach, thereby removing the two glitches. Our bidirectional DDC protocol was tested on a clinical dataset on 28 3-D ultrasound image volumes acquired using side fire Philips transrectal ultrasound. We demonstrate the orthogonal bidirectional DDC strategy achieved the most accurate volume estimation compared with previously published orthogonal unidirectional DDC and axial DDC methods. Compared to the ground truth, we show that the mean volume estimation errors were: 18.48%, 9.21% and 7.82% for unidirectional, axial and bidirectional DDC methods, respectively. The segmentation architecture is implemented in Visual C++ in Windows environment.

Segmentation of the common carotid artery with active shape models from 3D ultrasound images

NASA Astrophysics Data System (ADS)

Yang, Xin; Jin, Jiaoying; He, Wanji; Yuchi, Ming; Ding, Mingyue

2012-03-01

Carotid atherosclerosis is a major cause of stroke, a leading cause of death and disability. In this paper, we develop and evaluate a new segmentation method for outlining both lumen and adventitia (inner and outer walls) of common carotid artery (CCA) from three-dimensional ultrasound (3D US) images for carotid atherosclerosis diagnosis and evaluation. The data set consists of sixty-eight, 17× 2× 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80mg atorvastain and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. We investigate the use of Active Shape Models (ASMs) to segment CCA inner and outer walls after statin therapy. The proposed method was evaluated with respect to expert manually outlined boundaries as a surrogate for ground truth. For the lumen and adventitia segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 93.6%+/- 2.6%, 91.8%+/- 3.5%, mean absolute distances (MAD) of 0.28+/- 0.17mm and 0.34 +/- 0.19mm, maximum absolute distances (MAXD) of 0.87 +/- 0.37mm and 0.74 +/- 0.49mm. The proposed algorithm took 4.4 +/- 0.6min to segment a single 3D US images, compared to 11.7+/-1.2min for manual segmentation. Therefore, the method would promote the translation of carotid 3D US to clinical care for the fast, safety and economical monitoring of the atherosclerotic disease progression and regression during therapy.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cary, Theodore W.; Sultan, Laith R.; Sehgal, Chandra M., E-mail: sehgalc@uphs.upenn.edu

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced eachmore » phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.« less

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound.

PubMed

Cary, Theodore W; Reamer, Courtney B; Sultan, Laith R; Mohler, Emile R; Sehgal, Chandra M

2014-02-01

To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

PubMed Central

Cary, Theodore W.; Reamer, Courtney B.; Sultan, Laith R.; Mohler, Emile R.; Sehgal, Chandra M.

2014-01-01

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging. PMID:24506648

High-resolution ultrasound imaging of the eye - a review.

PubMed

Silverman, Ronald H

2009-01-01

This report summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) of the eye, in which frequencies of 35 MHz and above provide over a threefold improvement in resolution compared with conventional ophthalmic ultrasound systems. UBM allows imaging of anatomy and pathology involving the anterior segment, including regions obscured by overlying optically opaque anatomic or pathologic structures. UBM provides diagnostically significant information in conditions such as glaucoma, cysts and neoplasms, trauma and foreign bodies. UBM also can provide crucial biometric information regarding anterior segment structures, including the cornea and its constituent layers and the anterior and posterior chambers. Although UBM has now been in use for over 15 years, new technologies, including transducer arrays, pulse encoding and combination of ultrasound with light, offer the potential for significant advances in high-resolution diagnostic imaging of the eye.

Finite grade pheromone ant colony optimization for image segmentation

NASA Astrophysics Data System (ADS)

Yuanjing, F.; Li, Y.; Liangjun, K.

2008-06-01

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Versatile robotic probe calibration for position tracking in ultrasound imaging.

PubMed

Bø, Lars Eirik; Hofstad, Erlend Fagertun; Lindseth, Frank; Hernes, Toril A N

2015-05-07

Within the field of ultrasound-guided procedures, there are a number of methods for ultrasound probe calibration. While these methods are usually developed for a specific probe, they are in principle easily adapted to other probes. In practice, however, the adaptation often proves tedious and this is impractical in a research setting, where new probes are tested regularly. Therefore, we developed a method which can be applied to a large variety of probes without adaptation. The method used a robot arm to move a plastic sphere submerged in water through the ultrasound image plane, providing a slow and precise movement. The sphere was then segmented from the recorded ultrasound images using a MATLAB programme and the calibration matrix was computed based on this segmentation in combination with tracking information. The method was tested on three very different probes demonstrating both great versatility and high accuracy.

Versatile robotic probe calibration for position tracking in ultrasound imaging

NASA Astrophysics Data System (ADS)

Eirik Bø, Lars; Fagertun Hofstad, Erlend; Lindseth, Frank; Hernes, Toril A. N.

2015-05-01

Within the field of ultrasound-guided procedures, there are a number of methods for ultrasound probe calibration. While these methods are usually developed for a specific probe, they are in principle easily adapted to other probes. In practice, however, the adaptation often proves tedious and this is impractical in a research setting, where new probes are tested regularly. Therefore, we developed a method which can be applied to a large variety of probes without adaptation. The method used a robot arm to move a plastic sphere submerged in water through the ultrasound image plane, providing a slow and precise movement. The sphere was then segmented from the recorded ultrasound images using a MATLAB programme and the calibration matrix was computed based on this segmentation in combination with tracking information. The method was tested on three very different probes demonstrating both great versatility and high accuracy.

Group-wise feature-based registration of CT and ultrasound images of spine

NASA Astrophysics Data System (ADS)

Rasoulian, Abtin; Mousavi, Parvin; Hedjazi Moghari, Mehdi; Foroughi, Pezhman; Abolmaesumi, Purang

2010-02-01

Registration of pre-operative CT and freehand intra-operative ultrasound of lumbar spine could aid surgeons in the spinal needle injection which is a common procedure for pain management. Patients are always in a supine position during the CT scan, and in the prone or sitting position during the intervention. This leads to a difference in the spinal curvature between the two imaging modalities, which means a single rigid registration cannot be used for all of the lumbar vertebrae. In this work, a method for group-wise registration of pre-operative CT and intra-operative freehand 2-D ultrasound images of the lumbar spine is presented. The approach utilizes a pointbased registration technique based on the unscented Kalman filter, taking as input segmented vertebrae surfaces in both CT and ultrasound data. Ultrasound images are automatically segmented using a dynamic programming approach, while the CT images are semi-automatically segmented using thresholding. Since the curvature of the spine is different between the pre-operative and the intra-operative data, the registration approach is designed to simultaneously align individual groups of points segmented from each vertebra in the two imaging modalities. A biomechanical model is used to constrain the vertebrae transformation parameters during the registration and to ensure convergence. The mean target registration error achieved for individual vertebrae on five spine phantoms generated from CT data of patients, is 2.47 mm with standard deviation of 1.14 mm.

A Novel Method for Measuring Anterior Segment Area of the Eye on Ultrasound Biomicroscopic Images Using Photoshop

PubMed Central

Wu, Ziqiang; Lin, Jialiu; Huang, Jingjing

2015-01-01

Purpose To describe a novel method for quantitative measurement of area parameters in ocular anterior segment ultrasound biomicroscopy (UBM) images using Photoshop software and to assess its intraobserver and interobserver reproducibility. Methods Twenty healthy volunteers with wide angles and twenty patients with narrow or closed angles were consecutively recruited. UBM images were obtained and analyzed using Photoshop software by two physicians with different-level training on two occasions. Borders of anterior segment structures including cornea, iris, lens, and zonules in the UBM image were semi-automatically defined by the Magnetic Lasso Tool in the Photoshop software according to the pixel contrast and modified by the observers. Anterior chamber area (ACA), posterior chamber area (PCA), iris cross-section area (ICA) and angle recess area (ARA) were drawn and measured. The intraobserver and interobserver reproducibilities of the anterior segment area parameters and scleral spur location were assessed by limits of agreement, coefficient of variation (CV), and intraclass correlation coefficient (ICC). Results All of the parameters were successfully measured by Photoshop. The intraobserver and interobserver reproducibilities of ACA, PCA, and ICA were good, with no more than 5% CV and more than 0.95 ICC, while the CVs of ARA were within 20%. The intraobserver and interobserver reproducibilities for defining the spur location were more than 0.97 ICCs. Although the operating times for both observers were less than 3 minutes per image, there was significant difference in the measuring time between two observers with different levels of training (p<0.001). Conclusion Measurements of ocular anterior segment areas on UBM images by Photoshop showed good intraobserver and interobserver reproducibilties. The methodology was easy to adopt and effective in measuring. PMID:25803857

The diagnostic performance of leak-plugging automated segmentation versus manual tracing of breast lesions on ultrasound images.

PubMed

Xiong, Hui; Sultan, Laith R; Cary, Theodore W; Schultz, Susan M; Bouzghar, Ghizlane; Sehgal, Chandra M

2017-05-01

To assess the diagnostic performance of a leak-plugging segmentation method that we have developed for delineating breast masses on ultrasound images. Fifty-two biopsy-proven breast lesion images were analyzed by three observers using the leak-plugging and manual segmentation methods. From each segmentation method, grayscale and morphological features were extracted and classified as malignant or benign by logistic regression analysis. The performance of leak-plugging and manual segmentations was compared by: size of the lesion, overlap area ( O a ) between the margins, and area under the ROC curves ( A z ). The lesion size from leak-plugging segmentation correlated closely with that from manual tracing ( R 2 of 0.91). O a was higher for leak plugging, 0.92 ± 0.01 and 0.86 ± 0.06 for benign and malignant masses, respectively, compared to 0.80 ± 0.04 and 0.73 ± 0.02 for manual tracings. Overall O a between leak-plugging and manual segmentations was 0.79 ± 0.14 for benign and 0.73 ± 0.14 for malignant lesions. A z for leak plugging was consistently higher (0.910 ± 0.003) compared to 0.888 ± 0.012 for manual tracings. The coefficient of variation of A z between three observers was 0.29% for leak plugging compared to 1.3% for manual tracings. The diagnostic performance, size measurements, and observer variability for automated leak-plugging segmentations were either comparable to or better than those of manual tracings.

Segmentation of left atrial intracardiac ultrasound images for image guided cardiac ablation therapy

NASA Astrophysics Data System (ADS)

Rettmann, M. E.; Stephens, T.; Holmes, D. R.; Linte, C.; Packer, D. L.; Robb, R. A.

2013-03-01

Intracardiac echocardiography (ICE), a technique in which structures of the heart are imaged using a catheter navigated inside the cardiac chambers, is an important imaging technique for guidance in cardiac ablation therapy. Automatic segmentation of these images is valuable for guidance and targeting of treatment sites. In this paper, we describe an approach to segment ICE images by generating an empirical model of blood pool and tissue intensities. Normal, Weibull, Gamma, and Generalized Extreme Value (GEV) distributions are fit to histograms of tissue and blood pool pixels from a series of ICE scans. A total of 40 images from 4 separate studies were evaluated. The model was trained and tested using two approaches. In the first approach, the model was trained on all images from 3 studies and subsequently tested on the 40 images from the 4th study. This procedure was repeated 4 times using a leave-one-out strategy. This is termed the between-subjects approach. In the second approach, the model was trained on 10 randomly selected images from a single study and tested on the remaining 30 images in that study. This is termed the within-subjects approach. For both approaches, the model was used to automatically segment ICE images into blood and tissue regions. Each pixel is classified using the Generalized Liklihood Ratio Test across neighborhood sizes ranging from 1 to 49. Automatic segmentation results were compared against manual segmentations for all images. In the between-subjects approach, the GEV distribution using a neighborhood size of 17 was found to be the most accurate with a misclassification rate of approximately 17%. In the within-subjects approach, the GEV distribution using a neighborhood size of 19 was found to be the most accurate with a misclassification rate of approximately 15%. As expected, the majority of misclassified pixels were located near the boundaries between tissue and blood pool regions for both methods.

High-resolution ultrasound imaging of the eye – a review

PubMed Central

Silverman, Ronald H

2009-01-01

This report summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) of the eye, in which frequencies of 35 MHz and above provide over a threefold improvement in resolution compared with conventional ophthalmic ultrasound systems. UBM allows imaging of anatomy and pathology involving the anterior segment, including regions obscured by overlying optically opaque anatomic or pathologic structures. UBM provides diagnostically significant information in conditions such as glaucoma, cysts and neoplasms, trauma and foreign bodies. UBM also can provide crucial biometric information regarding anterior segment structures, including the cornea and its constituent layers and the anterior and posterior chambers. Although UBM has now been in use for over 15 years, new technologies, including transducer arrays, pulse encoding and combination of ultrasound with light, offer the potential for significant advances in high-resolution diagnostic imaging of the eye. PMID:19138310

A new method of cardiographic image segmentation based on grammar

NASA Astrophysics Data System (ADS)

Hamdi, Salah; Ben Abdallah, Asma; Bedoui, Mohamed H.; Alimi, Adel M.

2011-10-01

The measurement of the most common ultrasound parameters, such as aortic area, mitral area and left ventricle (LV) volume, requires the delineation of the organ in order to estimate the area. In terms of medical image processing this translates into the need to segment the image and define the contours as accurately as possible. The aim of this work is to segment an image and make an automated area estimation based on grammar. The entity "language" will be projected to the entity "image" to perform structural analysis and parsing of the image. We will show how the idea of segmentation and grammar-based area estimation is applied to real problems of cardio-graphic image processing.

Patient-specific model-based segmentation of brain tumors in 3D intraoperative ultrasound images.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Lindner, Dirk; Arlt, Felix; Ituna-Yudonago, Jean Fulbert; Chalopin, Claire

2018-03-01

Intraoperative ultrasound (iUS) imaging is commonly used to support brain tumor operation. The tumor segmentation in the iUS images is a difficult task and still under improvement because of the low signal-to-noise ratio. The success of automatic methods is also limited due to the high noise sensibility. Therefore, an alternative brain tumor segmentation method in 3D-iUS data using a tumor model obtained from magnetic resonance (MR) data for local MR-iUS registration is presented in this paper. The aim is to enhance the visualization of the brain tumor contours in iUS. A multistep approach is proposed. First, a region of interest (ROI) based on the specific patient tumor model is defined. Second, hyperechogenic structures, mainly tumor tissues, are extracted from the ROI of both modalities by using automatic thresholding techniques. Third, the registration is performed over the extracted binary sub-volumes using a similarity measure based on gradient values, and rigid and affine transformations. Finally, the tumor model is aligned with the 3D-iUS data, and its contours are represented. Experiments were successfully conducted on a dataset of 33 patients. The method was evaluated by comparing the tumor segmentation with expert manual delineations using two binary metrics: contour mean distance and Dice index. The proposed segmentation method using local and binary registration was compared with two grayscale-based approaches. The outcomes showed that our approach reached better results in terms of computational time and accuracy than the comparative methods. The proposed approach requires limited interaction and reduced computation time, making it relevant for intraoperative use. Experimental results and evaluations were performed offline. The developed tool could be useful for brain tumor resection supporting neurosurgeons to improve tumor border visualization in the iUS volumes.

Freehand three-dimensional ultrasound imaging of carotid artery using motion tracking technology.

PubMed

Chung, Shao-Wen; Shih, Cho-Chiang; Huang, Chih-Chung

2017-02-01

Ultrasound imaging has been extensively used for determining the severity of carotid atherosclerotic stenosis. In particular, the morphological characterization of carotid plaques can be performed for risk stratification of patients. However, using 2D ultrasound imaging for detecting morphological changes in plaques has several limitations. Due to the scan was performed on a single longitudinal cross-section, the selected 2D image is difficult to represent the entire morphology and volume of plaque and vessel lumen. In addition, the precise positions of 2D ultrasound images highly depend on the radiologists' experience, it makes the serial long-term exams of anti-atherosclerotic therapies are difficult to relocate the same corresponding planes by using 2D B-mode images. This has led to the recent development of three-dimensional (3D) ultrasound imaging, which offers improved visualization and quantification of complex morphologies of carotid plaques. In the present study, a freehand 3D ultrasound imaging technique based on optical motion tracking technology is proposed. Unlike other optical tracking systems, the marker is a small rigid body that is attached to the ultrasound probe and is tracked by eight high-performance digital cameras. The probe positions in 3D space coordinates are then calibrated at spatial and temporal resolutions of 10μm and 0.01s, respectively. The image segmentation procedure involves Otsu's and the active contour model algorithms and accurately detects the contours of the carotid arteries. The proposed imaging technique was verified using normal artery and atherosclerotic stenosis phantoms. Human experiments involving freehand scanning of the carotid artery of a volunteer were also performed. The results indicated that compared with manual segmentation, the lowest percentage errors of the proposed segmentation procedure were 7.8% and 9.1% for the external and internal carotid arteries, respectively. Finally, the effect of handshaking was

Segmenting Images for a Better Diagnosis

NASA Technical Reports Server (NTRS)

2004-01-01

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Comparative study on the performance of textural image features for active contour segmentation.

PubMed

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

Application of wavelet techniques for cancer diagnosis using ultrasound images: A Review.

PubMed

Sudarshan, Vidya K; Mookiah, Muthu Rama Krishnan; Acharya, U Rajendra; Chandran, Vinod; Molinari, Filippo; Fujita, Hamido; Ng, Kwan Hoong

2016-02-01

Ultrasound is an important and low cost imaging modality used to study the internal organs of human body and blood flow through blood vessels. It uses high frequency sound waves to acquire images of internal organs. It is used to screen normal, benign and malignant tissues of various organs. Healthy and malignant tissues generate different echoes for ultrasound. Hence, it provides useful information about the potential tumor tissues that can be analyzed for diagnostic purposes before therapeutic procedures. Ultrasound images are affected with speckle noise due to an air gap between the transducer probe and the body. The challenge is to design and develop robust image preprocessing, segmentation and feature extraction algorithms to locate the tumor region and to extract subtle information from isolated tumor region for diagnosis. This information can be revealed using a scale space technique such as the Discrete Wavelet Transform (DWT). It decomposes an image into images at different scales using low pass and high pass filters. These filters help to identify the detail or sudden changes in intensity in the image. These changes are reflected in the wavelet coefficients. Various texture, statistical and image based features can be extracted from these coefficients. The extracted features are subjected to statistical analysis to identify the significant features to discriminate normal and malignant ultrasound images using supervised classifiers. This paper presents a review of wavelet techniques used for preprocessing, segmentation and feature extraction of breast, thyroid, ovarian and prostate cancer using ultrasound images. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interactive segmentation of tongue contours in ultrasound video sequences using quality maps

NASA Astrophysics Data System (ADS)

Ghrenassia, Sarah; Ménard, Lucie; Laporte, Catherine

2014-03-01

Ultrasound (US) imaging is an effective and non invasive way of studying the tongue motions involved in normal and pathological speech, and the results of US studies are of interest for the development of new strategies in speech therapy. State-of-the-art tongue shape analysis techniques based on US images depend on semi-automated tongue segmentation and tracking techniques. Recent work has mostly focused on improving the accuracy of the tracking techniques themselves. However, occasional errors remain inevitable, regardless of the technique used, and the tongue tracking process must thus be supervised by a speech scientist who will correct these errors manually or semi-automatically. This paper proposes an interactive framework to facilitate this process. In this framework, the user is guided towards potentially problematic portions of the US image sequence by a segmentation quality map that is based on the normalized energy of an active contour model and automatically produced during tracking. When a problematic segmentation is identified, corrections to the segmented contour can be made on one image and propagated both forward and backward in the problematic subsequence, thereby improving the user experience. The interactive tools were tested in combination with two different tracking algorithms. Preliminary results illustrate the potential of the proposed framework, suggesting that the proposed framework generally improves user interaction time, with little change in segmentation repeatability.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques.

PubMed

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-12-01

Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications.

Anterior segment biometry with 2 imaging technologies: very-high-frequency ultrasound scanning versus optical coherence tomography.

PubMed

Piñero, David P; Plaza, Ana Belén; Alió, Jorge L

2008-01-01

To determine the interchangeability of 2 anterior segment imaging systems: a very-high-frequency (VHF) ultrasound scanning system (Artemis 2, Ultralink LLC) and an optical coherence tomography (OCT) system (Visante, Zeiss). Vissum Instituto Oftalmologico de Alicante, Alicante, Spain. This study comprised 20 eyes without pathology or previous surgery. The anterior chamber depth (ACD), central corneal thickness (CCT), angle-to-angle distance (ATA), and the iridocorneal angle size (IAS) at the 0-degree and 180-degree positions were measured with 2 imaging techniques: VHF ultrasound scanning and OCT. Analysis of agreement and interchangeability was performed by the Bland and Altman method. In addition, each measurement was performed 3 times consecutively to determine intrasession repeatability by means of the coefficient of variation (CV) and the intraclass correlation coefficient (ICC). No statistically significant differences were found between imaging techniques in ACD, CCT, or ATA (P>.40). The ranges of agreement were 0.20 mm, 16.11 mum, and 0.80 mm for ACD, CCT, and ATA, respectively. Regarding IAS, no statistically significant differences were found in the nasal (P = .78) or temporal (P = .63) measurements between devices. However, the range of agreement for nasal (14.3 degrees) and temporal (14.90 degrees) values was relevant, indicating the 2 techniques cannot be used interchangeably for IAS measurement. Excellent intrasession repeatability scores were obtained (CV and ICC). The Artemis 2 and the Visante OCT systems provide equivalent and repeatable measurements of the ACD, CCT, and ATA and can be used interchangeably for these purposes.

In vivo ultrasound imaging of the bone cortex

NASA Astrophysics Data System (ADS)

Renaud, Guillaume; Kruizinga, Pieter; Cassereau, Didier; Laugier, Pascal

2018-06-01

Current clinical ultrasound scanners cannot be used to image the interior morphology of bones because these scanners fail to address the complicated physics involved for exact image reconstruction. Here, we show that if the physics is properly addressed, bone cortex can be imaged using a conventional transducer array and a programmable ultrasound scanner. We provide in vivo proof for this technique by scanning the radius and tibia of two healthy volunteers and comparing the thickness of the radius bone with high-resolution peripheral x-ray computed tomography. Our method assumes a medium that is composed of different homogeneous layers with unique elastic anisotropy and ultrasonic wave-speed values. The applicable values of these layers are found by optimizing image sharpness and intensity over a range of relevant values. In the algorithm of image reconstruction we take wave refraction between the layers into account using a ray-tracing technique. The estimated values of the ultrasonic wave-speed and anisotropy in cortical bone are in agreement with ex vivo studies reported in the literature. These parameters are of interest since they were proposed as biomarkers for cortical bone quality. In this paper we discuss the physics involved with ultrasound imaging of bone and provide an algorithm to successfully image the first segment of cortical bone.

Quality Improvement of Liver Ultrasound Images Using Fuzzy Techniques

PubMed Central

Bayani, Azadeh; Langarizadeh, Mostafa; Radmard, Amir Reza; Nejad, Ahmadreza Farzaneh

2016-01-01

Background: Liver ultrasound images are so common and are applied so often to diagnose diffuse liver diseases like fatty liver. However, the low quality of such images makes it difficult to analyze them and diagnose diseases. The purpose of this study, therefore, is to improve the contrast and quality of liver ultrasound images. Methods: In this study, a number of image contrast enhancement algorithms which are based on fuzzy logic were applied to liver ultrasound images - in which the view of kidney is observable - using Matlab2013b to improve the image contrast and quality which has a fuzzy definition; just like image contrast improvement algorithms using a fuzzy intensification operator, contrast improvement algorithms applying fuzzy image histogram hyperbolization, and contrast improvement algorithms by fuzzy IF-THEN rules. Results: With the measurement of Mean Squared Error and Peak Signal to Noise Ratio obtained from different images, fuzzy methods provided better results, and their implementation - compared with histogram equalization method - led both to the improvement of contrast and visual quality of images and to the improvement of liver segmentation algorithms results in images. Conclusion: Comparison of the four algorithms revealed the power of fuzzy logic in improving image contrast compared with traditional image processing algorithms. Moreover, contrast improvement algorithm based on a fuzzy intensification operator was selected as the strongest algorithm considering the measured indicators. This method can also be used in future studies on other ultrasound images for quality improvement and other image processing and analysis applications. PMID:28077898

Ultrasound Imaging System Video

NASA Technical Reports Server (NTRS)

2002-01-01

In this video, astronaut Peggy Whitson uses the Human Research Facility (HRF) Ultrasound Imaging System in the Destiny Laboratory of the International Space Station (ISS) to image her own heart. The Ultrasound Imaging System provides three-dimension image enlargement of the heart and other organs, muscles, and blood vessels. It is capable of high resolution imaging in a wide range of applications, both research and diagnostic, such as Echocardiography (ultrasound of the heart), abdominal, vascular, gynecological, muscle, tendon, and transcranial ultrasound.

Multi-segment detector array for hybrid reflection-mode ultrasound and optoacoustic tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Merčep, Elena; Burton, Neal C.; Deán-Ben, Xosé Luís.; Razansky, Daniel

2017-02-01

The complementary contrast of the optoacoustic (OA) and pulse-echo ultrasound (US) modalities makes the combined usage of these imaging technologies highly advantageous. Due to the different physical contrast mechanisms development of a detector array optimally suited for both modalities is one of the challenges to efficient implementation of a single OA-US imaging device. We demonstrate imaging performance of the first hybrid detector array whose novel design, incorporating array segments of linear and concave geometry, optimally supports image acquisition in both reflection-mode ultrasonography and optoacoustic tomography modes. Hybrid detector array has a total number of 256 elements and three segments of different geometry and variable pitch size: a central 128-element linear segment with pitch of 0.25mm, ideally suited for pulse-echo US imaging, and two external 64-elements segments with concave geometry and 0.6mm pitch optimized for OA image acquisition. Interleaved OA and US image acquisition with up to 25 fps is facilitated through a custom-made multiplexer unit. Spatial resolution of the transducer was characterized in numerical simulations and validated in phantom experiments and comprises 230 and 300 μm in the respective OA and US imaging modes. Imaging performance of the multi-segment detector array was experimentally shown in a series of imaging sessions with healthy volunteers. Employing mixed array geometries allows at the same time achieving excellent OA contrast with a large field of view, and US contrast for complementary structural features with reduced side-lobes and improved resolution. The newly designed hybrid detector array that comprises segments of linear and concave geometries optimally fulfills requirements for efficient US and OA imaging and may expand the applicability of the developed hybrid OPUS imaging technology and accelerate its clinical translation.

Estimation of bladder wall location in ultrasound images.

PubMed

Topper, A K; Jernigan, M E

1991-05-01

A method of automatically estimating the location of the bladder wall in ultrasound images is proposed. Obtaining this estimate is intended to be the first stage in the development of an automatic bladder volume calculation system. The first step in the bladder wall estimation scheme involves globally processing the images using standard image processing techniques to highlight the bladder wall. Separate processing sequences are required to highlight the anterior bladder wall and the posterior bladder wall. The sequence to highlight the anterior bladder wall involves Gaussian smoothing and second differencing followed by zero-crossing detection. Median filtering followed by thresholding and gradient detection is used to highlight as much of the rest of the bladder wall as was visible in the original images. Then a 'bladder wall follower'--a line follower with rules based on the characteristics of ultrasound imaging and the anatomy involved--is applied to the processed images to estimate the bladder wall location by following the portions of the bladder wall which are highlighted and filling in the missing segments. The results achieved using this scheme are presented.

Anterior-segment imaging for assessment of glaucoma

PubMed Central

Ursea, Roxana; Silverman, Ronald H

2010-01-01

This article summarizes the physics, technology and clinical application of ultrasound biomicroscopy (UBM) and optical coherence tomography (OCT) for assessment of the anterior segment in glaucoma. UBM systems use frequencies ranging from approximately 35 to 80 MHz, as compared with typical 10-MHz systems used for general-purpose ophthalmic imaging. OCT systems use low-coherence, near-infrared light to provide detailed images of anterior segment structures at resolutions exceeding that of UBM. Both technologies allow visualization of the iridocorneal angle and, thus, can contribute to the diagnosis and management of glaucoma. OCT systems are advantageous, being noncontact proceedures and providing finer resolution than UBM, but UBM systems are superior for the visualization of retroiridal structures, including the ciliary body, posterior chamber and zonules, which can provide crucial diagnostic information for the assessment of glaucoma. PMID:20305726

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

PubMed

Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong

2015-07-01

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.

Echo decorrelation imaging of ex vivo HIFU and bulk ultrasound ablation using image-treat arrays

NASA Astrophysics Data System (ADS)

Fosnight, Tyler R.; Hooi, Fong Ming; Colbert, Sadie B.; Keil, Ryan D.; Barthe, Peter G.; Mast, T. Douglas

2017-03-01

In this study, the ability of ultrasound echo decorrelation imaging to map and predict heat-induced cell death was tested using bulk ultrasound thermal ablation, high intensity focused ultrasound (HIFU) thermal ablation, and pulse-echo imaging of ex vivo liver tissue by a custom image-treat array. Tissue was sonicated at 5.0 MHz using either pulses of unfocused ultrasound (N=12) (7.5 s, 50.9-101.8 W/cm2 in situ spatial-peak, temporal-peak intensity) for bulk ablation or focused ultrasound (N=21) (1 s, 284-769 W/cm2 in situ spatial-peak, temporal-peak intensity and focus depth of 10 mm) for HIFU ablation. Echo decorrelation and integrated backscatter (IBS) maps were formed from radiofrequency pulse-echo images captured at 118 frames per second during 5.0 s rest periods, beginning 1.1 s after each sonication pulse. Tissue samples were frozen at -80˚C, sectioned, vitally stained, imaged, and semi-automatically segmented for receiver operating characteristic (ROC) analysis. ROC curves were constructed to assess prediction performance for echo decorrelation and IBS. Logarithmically scaled mean echo decorrelation in non-ablated and ablated tissue regions before and after electronic noise and motion correction were compared. Ablation prediction by echo decorrelation and IBS was significant for both focused and bulk ultrasound ablation. The log10-scaled mean echo decorrelation was significantly greater in regions of ablation for both HIFU and bulk ultrasound ablation. Echo decorrelation due to electronic noise and motion was significantly reduced by correction. These results suggest that ultrasound echo decorrelation imaging is a promising approach for real-time prediction of heat-induced cell death for guidance and monitoring of clinical thermal ablation, including radiofrequency ablation and HIFU.

Line fiducial material and thickness considerations for ultrasound calibration

NASA Astrophysics Data System (ADS)

Ameri, Golafsoun; McLeod, A. J.; Baxter, John S. H.; Chen, Elvis C. S.; Peters, Terry M.

2015-03-01

Ultrasound calibration is a necessary procedure in many image-guided interventions, relating the position of tools and anatomical structures in the ultrasound image to a common coordinate system. This is a necessary component of augmented reality environments in image-guided interventions as it allows for a 3D visualization where other surgical tools outside the imaging plane can be found. Accuracy of ultrasound calibration fundamentally affects the total accuracy of this interventional guidance system. Many ultrasound calibration procedures have been proposed based on a variety of phantom materials and geometries. These differences lead to differences in representation of the phantom on the ultrasound image which subsequently affect the ability to accurately and automatically segment the phantom. For example, taut wires are commonly used as line fiducials in ultrasound calibration. However, at large depths or oblique angles, the fiducials appear blurred and smeared in ultrasound images making it hard to localize their cross-section with the ultrasound image plane. Intuitively, larger diameter phantoms with lower echogenicity are more accurately segmented in ultrasound images in comparison to highly reflective thin phantoms. In this work, an evaluation of a variety of calibration phantoms with different geometrical and material properties for the phantomless calibration procedure was performed. The phantoms used in this study include braided wire, plastic straws, and polyvinyl alcohol cryogel tubes with different diameters. Conventional B-mode and synthetic aperture images of the phantoms at different positions were obtained. The phantoms were automatically segmented from the ultrasound images using an ellipse fitting algorithm, the centroid of which is subsequently used as a fiducial for calibration. Calibration accuracy was evaluated for these procedures based on the leave-one-out target registration error. It was shown that larger diameter phantoms with lower

An automatic segmentation method of a parameter-adaptive PCNN for medical images.

PubMed

Lian, Jing; Shi, Bin; Li, Mingcong; Nan, Ziwei; Ma, Yide

2017-09-01

Since pre-processing and initial segmentation steps in medical images directly affect the final segmentation results of the regions of interesting, an automatic segmentation method of a parameter-adaptive pulse-coupled neural network is proposed to integrate the above-mentioned two segmentation steps into one. This method has a low computational complexity for different kinds of medical images and has a high segmentation precision. The method comprises four steps. Firstly, an optimal histogram threshold is used to determine the parameter [Formula: see text] for different kinds of images. Secondly, we acquire the parameter [Formula: see text] according to a simplified pulse-coupled neural network (SPCNN). Thirdly, we redefine the parameter V of the SPCNN model by sub-intensity distribution range of firing pixels. Fourthly, we add an offset [Formula: see text] to improve initial segmentation precision. Compared with the state-of-the-art algorithms, the new method achieves a comparable performance by the experimental results from ultrasound images of the gallbladder and gallstones, magnetic resonance images of the left ventricle, and mammogram images of the left and the right breast, presenting the overall metric UM of 0.9845, CM of 0.8142, TM of 0.0726. The algorithm has a great potential to achieve the pre-processing and initial segmentation steps in various medical images. This is a premise for assisting physicians to detect and diagnose clinical cases.

3D ultrasound imaging in image-guided intervention.

PubMed

Fenster, Aaron; Bax, Jeff; Neshat, Hamid; Cool, Derek; Kakani, Nirmal; Romagnoli, Cesare

2014-01-01

Ultrasound imaging is used extensively in diagnosis and image-guidance for interventions of human diseases. However, conventional 2D ultrasound suffers from limitations since it can only provide 2D images of 3-dimensional structures in the body. Thus, measurement of organ size is variable, and guidance of interventions is limited, as the physician is required to mentally reconstruct the 3-dimensional anatomy using 2D views. Over the past 20 years, a number of 3-dimensional ultrasound imaging approaches have been developed. We have developed an approach that is based on a mechanical mechanism to move any conventional ultrasound transducer while 2D images are collected rapidly and reconstructed into a 3D image. In this presentation, 3D ultrasound imaging approaches will be described for use in image-guided interventions.

Automated regional analysis of B-mode ultrasound images of skeletal muscle movement

PubMed Central

Darby, John; Costen, Nicholas; Loram, Ian D.

2012-01-01

To understand the functional significance of skeletal muscle anatomy, a method of quantifying local shape changes in different tissue structures during dynamic tasks is required. Taking advantage of the good spatial and temporal resolution of B-mode ultrasound imaging, we describe a method of automatically segmenting images into fascicle and aponeurosis regions and tracking movement of features, independently, in localized portions of each tissue. Ultrasound images (25 Hz) of the medial gastrocnemius muscle were collected from eight participants during ankle joint rotation (2° and 20°), isometric contractions (1, 5, and 50 Nm), and deep knee bends. A Kanade-Lucas-Tomasi feature tracker was used to identify and track any distinctive and persistent features within the image sequences. A velocity field representation of local movement was then found and subdivided between fascicle and aponeurosis regions using segmentations from a multiresolution active shape model (ASM). Movement in each region was quantified by interpolating the effect of the fields on a set of probes. ASM segmentation results were compared with hand-labeled data, while aponeurosis and fascicle movement were compared with results from a previously documented cross-correlation approach. ASM provided good image segmentations (<1 mm average error), with fully automatic initialization possible in sequences from seven participants. Feature tracking provided similar length change results to the cross-correlation approach for small movements, while outperforming it in larger movements. The proposed method provides the potential to distinguish between active and passive changes in muscle shape and model strain distributions during different movements/conditions and quantify nonhomogeneous strain along aponeuroses. PMID:22033532

Ultrasound Common Carotid Artery Segmentation Based on Active Shape Model

PubMed Central

Yang, Xin; Jin, Jiaoying; Xu, Mengling; Wu, Huihui; He, Wanji; Yuchi, Ming; Ding, Mingyue

2013-01-01

Carotid atherosclerosis is a major reason of stroke, a leading cause of death and disability. In this paper, a segmentation method based on Active Shape Model (ASM) is developed and evaluated to outline common carotid artery (CCA) for carotid atherosclerosis computer-aided evaluation and diagnosis. The proposed method is used to segment both media-adventitia-boundary (MAB) and lumen-intima-boundary (LIB) on transverse views slices from three-dimensional ultrasound (3D US) images. The data set consists of sixty-eight, 17 × 2 × 2, 3D US volume data acquired from the left and right carotid arteries of seventeen patients (eight treated with 80 mg atorvastatin and nine with placebo), who had carotid stenosis of 60% or more, at baseline and after three months of treatment. Manually outlined boundaries by expert are adopted as the ground truth for evaluation. For the MAB and LIB segmentations, respectively, the algorithm yielded Dice Similarity Coefficient (DSC) of 94.4% ± 3.2% and 92.8% ± 3.3%, mean absolute distances (MAD) of 0.26 ± 0.18 mm and 0.33 ± 0.21 mm, and maximum absolute distances (MAXD) of 0.75 ± 0.46 mm and 0.84 ± 0.39 mm. It took 4.3 ± 0.5 mins to segment single 3D US images, while it took 11.7 ± 1.2 mins for manual segmentation. The method would promote the translation of carotid 3D US to clinical care for the monitoring of the atherosclerotic disease progression and regression. PMID:23533535

Constrained Deep Weak Supervision for Histopathology Image Segmentation.

PubMed

Jia, Zhipeng; Huang, Xingyi; Chang, Eric I-Chao; Xu, Yan

2017-11-01

In this paper, we develop a new weakly supervised learning algorithm to learn to segment cancerous regions in histopathology images. This paper is under a multiple instance learning (MIL) framework with a new formulation, deep weak supervision (DWS); we also propose an effective way to introduce constraints to our neural networks to assist the learning process. The contributions of our algorithm are threefold: 1) we build an end-to-end learning system that segments cancerous regions with fully convolutional networks (FCNs) in which image-to-image weakly-supervised learning is performed; 2) we develop a DWS formulation to exploit multi-scale learning under weak supervision within FCNs; and 3) constraints about positive instances are introduced in our approach to effectively explore additional weakly supervised information that is easy to obtain and enjoy a significant boost to the learning process. The proposed algorithm, abbreviated as DWS-MIL, is easy to implement and can be trained efficiently. Our system demonstrates the state-of-the-art results on large-scale histopathology image data sets and can be applied to various applications in medical imaging beyond histopathology images, such as MRI, CT, and ultrasound images.

Sci-Thur AM: YIS – 03: Combining sagittally-reconstructed 3D and live-2D ultrasound for high-dose-rate prostate brachytherapy needle segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hrinivich, Thomas; Hoover, Douglas; Surry, Kathlee

Ultrasound-guided high-dose-rate prostate brachytherapy (HDR-BT) needle segmentation is performed clinically using live-2D sagittal images. Organ segmentation is then performed using axial images, introducing a source of geometric uncertainty. Sagittally-reconstructed 3D (SR3D) ultrasound enables both needle and organ segmentation, but suffers from shadow artifacts. We present a needle segmentation technique augmenting SR3D with live-2D sagittal images using mechanical probe tracking to mitigate image artifacts and compare it to the clinical standard. Seven prostate cancer patients underwent TRUS-guided HDR-BT during which the clinical and proposed segmentation techniques were completed in parallel using dual ultrasound video outputs. Calibrated needle end-length measurements were usedmore » to calculate insertion depth errors (IDEs), and the dosimetric impact of IDEs was evaluated by perturbing clinical treatment plan source positions. The proposed technique provided smaller IDEs than the clinical approach, with mean±SD of −0.3±2.2 mm and −0.5±3.7mm respectively. The proposed and clinical techniques resulted in 84% and 43% of needles with IDEs within ±3mm, and IDE ranges across all needles of [−7.7mm, 5.9mm] and [−9.3mm, 7.7mm] respectively. The proposed and clinical IDEs lead to mean±SD changes in the volume of the prostate receiving the prescription dose of −0.6±0.9% and −2.0±5.3% respectively. The proposed technique provides improved HDR-BT needle segmentation accuracy over the clinical technique leading to decreased dosimetric uncertainty by eliminating the axial-to-sagittal registration, and mitigates the effect of shadow artifacts by incorporating mechanically registered live-2D sagittal images.« less

[Anterior segment tumor imaging: advantages of ultrasound (10, 20 and 50 MHz) and optical coherence tomography].

PubMed

Siahmed, K; Berges, O; Desjardins, L; Lumbroso, L; Brasseur, G

2004-02-01

Detail the role of different imaging techniques for diagnosis of tumors of the iris. Sixty-one tumors of the iris were explored using ultrasound at 10 and 20MHz (Cinescan, BVI Quantel Medical) and 50MHz (UBM, Paradigm) and optical coherence tomography (OCT) (Humphrey Zeiss). Ultrasound should be used at frequencies of 20MHz or greater to precisely characterize, localize and measure a lesion. Ultrasound biomicroscopy (UBM) is inadequate to measure large tumors (extending toward the back of the ciliary body), because of the transducer and the considerably lower image quality caused by the lesion. Ultrasound alone cannot characterize a solid lesion, and moreover cannot differentiate benign and malignant lesions. Clinical notions are also important in diagnosis and patient management. OCT recognizes whether a lesion is liquid or solid in certain cases. With a tumor that seems solid, a 50MHz examination must be done rapidly, and if the entire lesion is difficult to see, a 20MHz ultrasound should be used. With a protruding iris, high-frequency ultrasound and OCT differentiate a cystic lesion from a solid mass, but only BMU provides a precise measurement and regular surveillance capabilities.

US-Cut: interactive algorithm for rapid detection and segmentation of liver tumors in ultrasound acquisitions

NASA Astrophysics Data System (ADS)

Egger, Jan; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Chen, Xiaojun; Zoller, Wolfram G.; Schmalstieg, Dieter; Hann, Alexander

2016-04-01

Ultrasound (US) is the most commonly used liver imaging modality worldwide. It plays an important role in follow-up of cancer patients with liver metastases. We present an interactive segmentation approach for liver tumors in US acquisitions. Due to the low image quality and the low contrast between the tumors and the surrounding tissue in US images, the segmentation is very challenging. Thus, the clinical practice still relies on manual measurement and outlining of the tumors in the US images. We target this problem by applying an interactive segmentation algorithm to the US data, allowing the user to get real-time feedback of the segmentation results. The algorithm has been developed and tested hand-in-hand by physicians and computer scientists to make sure a future practical usage in a clinical setting is feasible. To cover typical acquisitions from the clinical routine, the approach has been evaluated with dozens of datasets where the tumors are hyperechoic (brighter), hypoechoic (darker) or isoechoic (similar) in comparison to the surrounding liver tissue. Due to the interactive real-time behavior of the approach, it was possible even in difficult cases to find satisfying segmentations of the tumors within seconds and without parameter settings, and the average tumor deviation was only 1.4mm compared with manual measurements. However, the long term goal is to ease the volumetric acquisition of liver tumors in order to evaluate for treatment response. Additional aim is the registration of intraoperative US images via the interactive segmentations to the patient's pre-interventional CT acquisitions.

Anterior Segment Imaging for Angle Closure.

PubMed

Chansangpetch, Sunee; Rojanapongpun, Prin; Lin, Shan C

2018-04-01

To summarize the role of anterior segment imaging (AS-imaging) in angle closure diagnosis and management, and the possible advantages over the current standard of gonioscopy. Literature review and perspective. Review of the pertinent publications with interpretation and perspective in relation to the use of AS-imaging in angle closure assessment focusing on anterior segment optical coherence tomography and ultrasound biomicroscopy. Several limitations have been encountered with the reference standard of gonioscopy for angle assessment. AS-imaging has been shown to have performance in angle closure detection compared to gonioscopy. Also, imaging has greater reproducibility and serves as better documentation for long-term follow-up than conventional gonioscopy. The qualitative and quantitative information obtained from AS-imaging enables better understanding of the underlying mechanisms of angle closure and provides useful parameters for risk assessment and possible prediction of the response to laser and surgical intervention. The latest technologies-including 3-dimensional imaging-have allowed for the assessment of the angle that simulates the gonioscopic view. These advantages suggest that AS-imaging has a potential to be a reference standard for the diagnosis and monitoring of angle closure disease in the future. Although gonioscopy remains the primary method of angle assessment, AS-imaging has an increasing role in angle closure screening and management. The test should be integrated into clinical practice as an adjunctive tool for angle assessment. It is arguable that AS-imaging should be considered first-line screening for patients at risk for angle closure. Copyright © 2018 Elsevier Inc. All rights reserved.

Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method.

PubMed

Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

2018-01-17

Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat 'brighter' than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

Bone surface enhancement in ultrasound images using a new Doppler-based acquisition/processing method

NASA Astrophysics Data System (ADS)

Yang, Xu; Tang, Songyuan; Tasciotti, Ennio; Righetti, Raffaella

2018-01-01

Ultrasound (US) imaging has long been considered as a potential aid in orthopedic surgeries. US technologies are safe, portable and do not use radiations. This would make them a desirable tool for real-time assessment of fractures and to monitor fracture healing. However, image quality of US imaging methods in bone applications is limited by speckle, attenuation, shadow, multiple reflections and other imaging artifacts. While bone surfaces typically appear in US images as somewhat ‘brighter’ than soft tissue, they are often not easily distinguishable from the surrounding tissue. Therefore, US imaging methods aimed at segmenting bone surfaces need enhancement in image contrast prior to segmentation to improve the quality of the detected bone surface. In this paper, we present a novel acquisition/processing technique for bone surface enhancement in US images. Inspired by elastography and Doppler imaging methods, this technique takes advantage of the difference between the mechanical and acoustic properties of bones and those of soft tissues to make the bone surface more easily distinguishable in US images. The objective of this technique is to facilitate US-based bone segmentation methods and improve the accuracy of their outcomes. The newly proposed technique is tested both in in vitro and in vivo experiments. The results of these preliminary experiments suggest that the use of the proposed technique has the potential to significantly enhance the detectability of bone surfaces in noisy ultrasound images.

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Localization of the transverse processes in ultrasound for spinal curvature measurement

NASA Astrophysics Data System (ADS)

Kamali, Shahrokh; Ungi, Tamas; Lasso, Andras; Yan, Christina; Lougheed, Matthew; Fichtinger, Gabor

2017-03-01

PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks such as transverse processes, but as bones have reduced visibility in ultrasound imaging, skeletal landmarks are typically segmented manually, which is an exceedingly laborious and long process. We propose an automatic algorithm to segment and localize the surface of bony areas in the transverse process for scoliosis in ultrasound. METHODS: The algorithm uses cascade of filters to remove low intensity pixels, smooth the image and detect bony edges. By applying first differentiation, candidate bony areas are classified. The average intensity under each area has a correlation with the possibility of a shadow, and areas with strong shadow are kept for bone segmentation. The segmented images are used to reconstruct a 3-D volume to represent the whole spinal structure around the transverse processes. RESULTS: A comparison between the manual ground truth segmentation and the automatic algorithm in 50 images showed 0.17 mm average difference. The time to process all 1,938 images was about 37 Sec. (0.0191 Sec. / Image), including reading the original sequence file. CONCLUSION: Initial experiments showed the algorithm to be sufficiently accurate and fast for segmentation transverse processes in ultrasound for spinal curvature measurement. An extensive evaluation of the method is currently underway on images from a larger patient cohort and using multiple observers in producing ground truth segmentation.

Automatic segmentation and classification of gestational sac based on mean sac diameter using medical ultrasound image

NASA Astrophysics Data System (ADS)

Khazendar, Shan; Farren, Jessica; Al-Assam, Hisham; Sayasneh, Ahmed; Du, Hongbo; Bourne, Tom; Jassim, Sabah A.

2014-05-01

Ultrasound is an effective multipurpose imaging modality that has been widely used for monitoring and diagnosing early pregnancy events. Technology developments coupled with wide public acceptance has made ultrasound an ideal tool for better understanding and diagnosing of early pregnancy. The first measurable signs of an early pregnancy are the geometric characteristics of the Gestational Sac (GS). Currently, the size of the GS is manually estimated from ultrasound images. The manual measurement involves multiple subjective decisions, in which dimensions are taken in three planes to establish what is known as Mean Sac Diameter (MSD). The manual measurement results in inter- and intra-observer variations, which may lead to difficulties in diagnosis. This paper proposes a fully automated diagnosis solution to accurately identify miscarriage cases in the first trimester of pregnancy based on automatic quantification of the MSD. Our study shows a strong positive correlation between the manual and the automatic MSD estimations. Our experimental results based on a dataset of 68 ultrasound images illustrate the effectiveness of the proposed scheme in identifying early miscarriage cases with classification accuracies comparable with those of domain experts using K nearest neighbor classifier on automatically estimated MSDs.

Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalizing neural network

PubMed Central

Dietz, Hans Peter; D’hooge, Jan; Barratt, Dean; Deprest, Jan

2018-01-01

Abstract. Segmentation of the levator hiatus in ultrasound allows the extraction of biometrics, which are of importance for pelvic floor disorder assessment. We present a fully automatic method using a convolutional neural network (CNN) to outline the levator hiatus in a two-dimensional image extracted from a three-dimensional ultrasound volume. In particular, our method uses a recently developed scaled exponential linear unit (SELU) as a nonlinear self-normalizing activation function, which for the first time has been applied in medical imaging with CNN. SELU has important advantages such as being parameter-free and mini-batch independent, which may help to overcome memory constraints during training. A dataset with 91 images from 35 patients during Valsalva, contraction, and rest, all labeled by three operators, is used for training and evaluation in a leave-one-patient-out cross validation. Results show a median Dice similarity coefficient of 0.90 with an interquartile range of 0.08, with equivalent performance to the three operators (with a Williams’ index of 1.03), and outperforming a U-Net architecture without the need for batch normalization. We conclude that the proposed fully automatic method achieved equivalent accuracy in segmenting the pelvic floor levator hiatus compared to a previous semiautomatic approach. PMID:29340289

Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalizing neural network.

PubMed

Bonmati, Ester; Hu, Yipeng; Sindhwani, Nikhil; Dietz, Hans Peter; D'hooge, Jan; Barratt, Dean; Deprest, Jan; Vercauteren, Tom

2018-04-01

Segmentation of the levator hiatus in ultrasound allows the extraction of biometrics, which are of importance for pelvic floor disorder assessment. We present a fully automatic method using a convolutional neural network (CNN) to outline the levator hiatus in a two-dimensional image extracted from a three-dimensional ultrasound volume. In particular, our method uses a recently developed scaled exponential linear unit (SELU) as a nonlinear self-normalizing activation function, which for the first time has been applied in medical imaging with CNN. SELU has important advantages such as being parameter-free and mini-batch independent, which may help to overcome memory constraints during training. A dataset with 91 images from 35 patients during Valsalva, contraction, and rest, all labeled by three operators, is used for training and evaluation in a leave-one-patient-out cross validation. Results show a median Dice similarity coefficient of 0.90 with an interquartile range of 0.08, with equivalent performance to the three operators (with a Williams' index of 1.03), and outperforming a U-Net architecture without the need for batch normalization. We conclude that the proposed fully automatic method achieved equivalent accuracy in segmenting the pelvic floor levator hiatus compared to a previous semiautomatic approach.

Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.

PubMed

Tan, Tao; Gubern-Mérida, Albert; Borelli, Cristina; Manniesing, Rashindra; van Zelst, Jan; Wang, Lei; Zhang, Wei; Platel, Bram; Mann, Ritse M; Karssemeijer, Nico

2016-07-01

Automated 3D breast ultrasound (ABUS) has been proposed as a complementary screening modality to mammography for early detection of breast cancers. To facilitate the interpretation of ABUS images, automated diagnosis and detection techniques are being developed, in which malignant lesion segmentation plays an important role. However, automated segmentation of cancer in ABUS is challenging since lesion edges might not be well defined. In this study, the authors aim at developing an automated segmentation method for malignant lesions in ABUS that is robust to ill-defined cancer edges and posterior shadowing. A segmentation method using depth-guided dynamic programming based on spiral scanning is proposed. The method automatically adjusts aggressiveness of the segmentation according to the position of the voxels relative to the lesion center. Segmentation is more aggressive in the upper part of the lesion (close to the transducer) than at the bottom (far away from the transducer), where posterior shadowing is usually visible. The authors used Dice similarity coefficient (Dice) for evaluation. The proposed method is compared to existing state of the art approaches such as graph cut, level set, and smart opening and an existing dynamic programming method without depth dependence. In a dataset of 78 cancers, our proposed segmentation method achieved a mean Dice of 0.73 ± 0.14. The method outperforms an existing dynamic programming method (0.70 ± 0.16) on this task (p = 0.03) and it is also significantly (p < 0.001) better than graph cut (0.66 ± 0.18), level set based approach (0.63 ± 0.20) and smart opening (0.65 ± 0.12). The proposed depth-guided dynamic programming method achieves accurate breast malignant lesion segmentation results in automated breast ultrasound.

A Virtual Reality System for PTCD Simulation Using Direct Visuo-Haptic Rendering of Partially Segmented Image Data.

PubMed

Fortmeier, Dirk; Mastmeyer, Andre; Schröder, Julian; Handels, Heinz

2016-01-01

This study presents a new visuo-haptic virtual reality (VR) training and planning system for percutaneous transhepatic cholangio-drainage (PTCD) based on partially segmented virtual patient models. We only use partially segmented image data instead of a full segmentation and circumvent the necessity of surface or volume mesh models. Haptic interaction with the virtual patient during virtual palpation, ultrasound probing and needle insertion is provided. Furthermore, the VR simulator includes X-ray and ultrasound simulation for image-guided training. The visualization techniques are GPU-accelerated by implementation in Cuda and include real-time volume deformations computed on the grid of the image data. Computation on the image grid enables straightforward integration of the deformed image data into the visualization components. To provide shorter rendering times, the performance of the volume deformation algorithm is improved by a multigrid approach. To evaluate the VR training system, a user evaluation has been performed and deformation algorithms are analyzed in terms of convergence speed with respect to a fully converged solution. The user evaluation shows positive results with increased user confidence after a training session. It is shown that using partially segmented patient data and direct volume rendering is suitable for the simulation of needle insertion procedures such as PTCD.

Shape complexes: the intersection of label orderings and star convexity constraints in continuous max-flow medical image segmentation

PubMed Central

Baxter, John S. H.; Inoue, Jiro; Drangova, Maria; Peters, Terry M.

2016-01-01

Abstract. Optimization-based segmentation approaches deriving from discrete graph-cuts and continuous max-flow have become increasingly nuanced, allowing for topological and geometric constraints on the resulting segmentation while retaining global optimality. However, these two considerations, topological and geometric, have yet to be combined in a unified manner. The concept of “shape complexes,” which combine geodesic star convexity with extendable continuous max-flow solvers, is presented. These shape complexes allow more complicated shapes to be created through the use of multiple labels and super-labels, with geodesic star convexity governed by a topological ordering. These problems can be optimized using extendable continuous max-flow solvers. Previous approaches required computationally expensive coordinate system warping, which are ill-defined and ambiguous in the general case. These shape complexes are demonstrated in a set of synthetic images as well as vessel segmentation in ultrasound, valve segmentation in ultrasound, and atrial wall segmentation from contrast-enhanced CT. Shape complexes represent an extendable tool alongside other continuous max-flow methods that may be suitable for a wide range of medical image segmentation problems. PMID:28018937

Transvaginal ultrasound (image)

MedlinePlus

Transvaginal ultrasound is a method of imaging the genital tract in females. A hand held probe is inserted directly ... vaginal cavity to scan the pelvic structures, while ultrasound pictures are viewed on a monitor. The test ...

Abdominal ultrasound (image)

MedlinePlus

Abdominal ultrasound is a scanning technique used to image the interior of the abdomen. Like the X-ray, MRI, ... it has its place as a diagnostic tool. Ultrasound scans use high frequency sound waves to produce ...

A medical imaging analysis system for trigger finger using an adaptive texture-based active shape model (ATASM) in ultrasound images

PubMed Central

Chuang, Bo-I; Kuo, Li-Chieh; Yang, Tai-Hua; Su, Fong-Chin; Jou, I-Ming; Lin, Wei-Jr; Sun, Yung-Nien

2017-01-01

Trigger finger has become a prevalent disease that greatly affects occupational activity and daily life. Ultrasound imaging is commonly used for the clinical diagnosis of trigger finger severity. Due to image property variations, traditional methods cannot effectively segment the finger joint’s tendon structure. In this study, an adaptive texture-based active shape model method is used for segmenting the tendon and synovial sheath. Adapted weights are applied in the segmentation process to adjust the contribution of energy terms depending on image characteristics at different positions. The pathology is then determined according to the wavelet and co-occurrence texture features of the segmented tendon area. In the experiments, the segmentation results have fewer errors, with respect to the ground truth, than contours drawn by regular users. The mean values of the absolute segmentation difference of the tendon and synovial sheath are 3.14 and 4.54 pixels, respectively. The average accuracy of pathological determination is 87.14%. The segmentation results are all acceptable in data of both clear and fuzzy boundary cases in 74 images. And the symptom classifications of 42 cases are also a good reference for diagnosis according to the expert clinicians’ opinions. PMID:29077737

Three-Dimensional Reconstruction of Coronary Arteries and Its Application in Localization of Coronary Artery Segments Corresponding to Myocardial Segments Identified by Transthoracic Echocardiography

PubMed Central

Zhong, Chunyan; Guo, Yanli; Huang, Haiyun; Tan, Liwen; Wu, Yi; Wang, Wenting

2013-01-01

Objectives. To establish 3D models of coronary arteries (CA) and study their application in localization of CA segments identified by Transthoracic Echocardiography (TTE). Methods. Sectional images of the heart collected from the first CVH dataset and contrast CT data were used to establish 3D models of the CA. Virtual dissection was performed on the 3D models to simulate the conventional sections of TTE. Then, we used 2D ultrasound, speckle tracking imaging (STI), and 2D ultrasound plus 3D CA models to diagnose 170 patients and compare the results to coronary angiography (CAG). Results. 3D models of CA distinctly displayed both 3D structure and 2D sections of CA. This simulated TTE imaging in any plane and showed the CA segments that corresponded to 17 myocardial segments identified by TTE. The localization accuracy showed a significant difference between 2D ultrasound and 2D ultrasound plus 3D CA model in the severe stenosis group (P < 0.05) and in the mild-to-moderate stenosis group (P < 0.05). Conclusions. These innovative modeling techniques help clinicians identify the CA segments that correspond to myocardial segments typically shown in TTE sectional images, thereby increasing the accuracy of the TTE-based diagnosis of CHD. PMID:24348745

Three-dimensional reconstruction of coronary arteries and its application in localization of coronary artery segments corresponding to myocardial segments identified by transthoracic echocardiography.

PubMed

Zhong, Chunyan; Guo, Yanli; Huang, Haiyun; Tan, Liwen; Wu, Yi; Wang, Wenting

2013-01-01

To establish 3D models of coronary arteries (CA) and study their application in localization of CA segments identified by Transthoracic Echocardiography (TTE). Sectional images of the heart collected from the first CVH dataset and contrast CT data were used to establish 3D models of the CA. Virtual dissection was performed on the 3D models to simulate the conventional sections of TTE. Then, we used 2D ultrasound, speckle tracking imaging (STI), and 2D ultrasound plus 3D CA models to diagnose 170 patients and compare the results to coronary angiography (CAG). 3D models of CA distinctly displayed both 3D structure and 2D sections of CA. This simulated TTE imaging in any plane and showed the CA segments that corresponded to 17 myocardial segments identified by TTE. The localization accuracy showed a significant difference between 2D ultrasound and 2D ultrasound plus 3D CA model in the severe stenosis group (P < 0.05) and in the mild-to-moderate stenosis group (P < 0.05). These innovative modeling techniques help clinicians identify the CA segments that correspond to myocardial segments typically shown in TTE sectional images, thereby increasing the accuracy of the TTE-based diagnosis of CHD.

Evaluation of non-ST segment elevation acute chest pain syndromes with a novel low-profile continuous imaging ultrasound transducer.

PubMed

Chandraratna, P Anthony N; Mohar, Dilbahar S; Sidarous, Peter F; Brar, Prabhjyot; Miller, Jeffrey; Shah, Nissar; Kadis, John; Ali, Ashgar; Mohar, Prabhsimran

2012-09-01

This investigation was designed to test the hypothesis that continuous cardiac imaging using an ultrasound transducer developed in our laboratory (ContiScan) is superior to electrocardiogram (ECG) monitoring in the diagnosis of coronary artery disease (CAD) in patients with acute non-ST segment elevation chest pain syndromes. Seventy patients with intermediate to high probability of CAD who presented with typical anginal chest pain and no evidence of ST segment elevation on the ECG were studied. The 2.5-MHz transducer is spherical in its distal part mounted in an external housing to permit steering in 360 degrees. The transducer was placed at the left sternal border to image the left ventricular short-axis view and recorded on video tape at baseline, during and after episodes of chest pain. Two ECG leads were continuously monitored. The presence of CAD was confirmed by coronary arteriography or nuclear or echocardiographic stress testing. Twenty-four patients had regional wall motion abnormalities (RWMA) on their initial echo which were unchanged during the period of monitoring. All had evidence of CAD. Twenty-eight patients had transient RWMA. All had evidence of CAD. Eighteen patients had normal wall motion throughout the monitoring period, 14 of these had no evidence of CAD, and four had evidence of CAD. These four patients did not have chest pain during monitoring. The sensitivity, specificity, and accuracy of echocardiographic monitoring for diagnosing non-ST elevation myocardial infarction was 88%, 100%, and 91% respectively. The sensitivity, specificity, and accuracy of the ECG for diagnosis of CAD were 31%, 100%, and 52%, respectively. Echocardiography was superior to ECG (P < 0.001). The data indicate that continuous cardiac imaging is superior to ECG monitoring for the diagnosis of CAD in patients presenting with acute non-ST segment elevation chest pain syndromes. This technique could be a useful adjunct to ECG monitoring for myocardial ischemia in the

Basic physics of ultrasound imaging.

PubMed

Aldrich, John E

2007-05-01

The appearance of ultrasound images depends critically on the physical interactions of sound with the tissues in the body. The basic principles of ultrasound imaging and the physical reasons for many common artifacts are described.

Despeckle filtering software toolbox for ultrasound imaging of the common carotid artery.

PubMed

Loizou, Christos P; Theofanous, Charoula; Pantziaris, Marios; Kasparis, Takis

2014-04-01

Ultrasound imaging of the common carotid artery (CCA) is a non-invasive tool used in medicine to assess the severity of atherosclerosis and monitor its progression through time. It is also used in border detection and texture characterization of the atherosclerotic carotid plaque in the CCA, the identification and measurement of the intima-media thickness (IMT) and the lumen diameter that all are very important in the assessment of cardiovascular disease (CVD). Visual perception, however, is hindered by speckle, a multiplicative noise, that degrades the quality of ultrasound B-mode imaging. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image segmentation of the IMT and the atherosclerotic carotid plaque in ultrasound images. In order to facilitate this preprocessing step, we have developed in MATLAB(®) a unified toolbox that integrates image despeckle filtering (IDF), texture analysis and image quality evaluation techniques to automate the pre-processing and complement the disease evaluation in ultrasound CCA images. The proposed software, is based on a graphical user interface (GUI) and incorporates image normalization, 10 different despeckle filtering techniques (DsFlsmv, DsFwiener, DsFlsminsc, DsFkuwahara, DsFgf, DsFmedian, DsFhmedian, DsFad, DsFnldif, DsFsrad), image intensity normalization, 65 texture features, 15 quantitative image quality metrics and objective image quality evaluation. The software is publicly available in an executable form, which can be downloaded from http://www.cs.ucy.ac.cy/medinfo/. It was validated on 100 ultrasound images of the CCA, by comparing its results with quantitative visual analysis performed by a medical expert. It was observed that the despeckle filters DsFlsmv, and DsFhmedian improved image quality perception (based on the expert's assessment and the image texture and quality metrics). It is anticipated that the

Ultrasound Molecular Imaging: Moving Towards Clinical Translation

PubMed Central

Abou-Elkacem, Lotfi; Bachawal, Sunitha V.; Willmann, Jürgen K.

2015-01-01

Ultrasound is a widely available, cost-effective, real-time, non-invasive and safe imaging modality widely used in the clinic for anatomical and functional imaging. With the introduction of novel molecularly-targeted ultrasound contrast agents, another dimension of ultrasound has become a reality: diagnosing and monitoring pathological processes at the molecular level. Most commonly used ultrasound molecular imaging contrast agents are micron sized, gas-containing microbubbles functionalized to recognize and attach to molecules expressed on inflamed or angiogenic vascular endothelial cells. There are several potential clinical applications currently being explored including earlier detection, molecular profiling, and monitoring of cancer, as well as visualization of ischemic memory in transient myocardial ischemia, monitoring of disease activity in inflammatory bowel disease, and assessment of arteriosclerosis. Recently, a first clinical grade ultrasound contrast agent (BR55), targeted at a molecule expressed in neoangiogenesis (vascular endothelial growth factor receptor type 2; VEGFR2) has been introduced and safety and feasibility of VEGFR2-targeted ultrasound imaging is being explored in first inhuman clinical trials in various cancer types. This review describes the design of ultrasound molecular imaging contrast agents, imaging techniques, and potential future clinical applications of ultrasound molecular imaging. PMID:25851932

Segmentation of stereo terrain images

NASA Astrophysics Data System (ADS)

George, Debra A.; Privitera, Claudio M.; Blackmon, Theodore T.; Zbinden, Eric; Stark, Lawrence W.

2000-06-01

We have studied four approaches to segmentation of images: three automatic ones using image processing algorithms and a fourth approach, human manual segmentation. We were motivated toward helping with an important NASA Mars rover mission task -- replacing laborious manual path planning with automatic navigation of the rover on the Mars terrain. The goal of the automatic segmentations was to identify an obstacle map on the Mars terrain to enable automatic path planning for the rover. The automatic segmentation was first explored with two different segmentation methods: one based on pixel luminance, and the other based on pixel altitude generated through stereo image processing. The third automatic segmentation was achieved by combining these two types of image segmentation. Human manual segmentation of Martian terrain images was used for evaluating the effectiveness of the combined automatic segmentation as well as for determining how different humans segment the same images. Comparisons between two different segmentations, manual or automatic, were measured using a similarity metric, SAB. Based on this metric, the combined automatic segmentation did fairly well in agreeing with the manual segmentation. This was a demonstration of a positive step towards automatically creating the accurate obstacle maps necessary for automatic path planning and rover navigation.

Automatic segmentation and 3D reconstruction of intravascular ultrasound images for a fast preliminar evaluation of vessel pathologies.

PubMed

Sanz-Requena, Roberto; Moratal, David; García-Sánchez, Diego Ramón; Bodí, Vicente; Rieta, José Joaquín; Sanchis, Juan Manuel

2007-03-01

Intravascular ultrasound (IVUS) imaging is used along with X-ray coronary angiography to detect vessel pathologies. Manual analysis of IVUS images is slow and time-consuming and it is not feasible for clinical purposes. A semi-automated method is proposed to generate 3D reconstructions from IVUS video sequences, so that a fast diagnose can be easily done, quantifying plaque length and severity as well as plaque volume of the vessels under study. The methodology described in this work has four steps: a pre-processing of IVUS images, a segmentation of media-adventitia contour, a detection of intima and plaque and a 3D reconstruction of the vessel. Preprocessing is intended to remove noise from the images without blurring the edges. Segmentation of media-adventitia contour is achieved using active contours (snakes). In particular, we use the gradient vector flow (GVF) as external force for the snakes. The detection of lumen border is obtained taking into account gray-level information of the inner part of the previously detected contours. A knowledge-based approach is used to determine which level of gray corresponds statistically to the different regions of interest: intima, plaque and lumen. The catheter region is automatically discarded. An estimate of plaque type is also given. Finally, 3D reconstruction of all detected regions is made. The suitability of this methodology has been verified for the analysis and visualization of plaque length, stenosis severity, automatic detection of the most problematic regions, calculus of plaque volumes and a preliminary estimation of plaque type obtaining for automatic measures of lumen and vessel area an average error smaller than 1mm(2) (equivalent aproximately to 10% of the average measure), for calculus of plaque and lumen volume errors smaller than 0.5mm(3) (equivalent approximately to 20% of the average measure) and for plaque type estimates a mismatch of less than 8% in the analysed frames.

Segmentation of arterial vessel wall motion to sub-pixel resolution using M-mode ultrasound.

PubMed

Fancourt, Craig; Azer, Karim; Ramcharan, Sharmilee L; Bunzel, Michelle; Cambell, Barry R; Sachs, Jeffrey R; Walker, Matthew

2008-01-01

We describe a method for segmenting arterial vessel wall motion to sub-pixel resolution, using the returns from M-mode ultrasound. The technique involves measuring the spatial offset between all pairs of scans from their cross-correlation, converting the spatial offsets to relative wall motion through a global optimization, and finally translating from relative to absolute wall motion by interpolation over the M-mode image. The resulting detailed wall distension waveform has the potential to enhance existing vascular biomarkers, such as strain and compliance, as well as enable new ones.

Currently available methodologies for the processing of intravascular ultrasound and optical coherence tomography images.

PubMed

Athanasiou, Lambros; Sakellarios, Antonis I; Bourantas, Christos V; Tsirka, Georgia; Siogkas, Panagiotis; Exarchos, Themis P; Naka, Katerina K; Michalis, Lampros K; Fotiadis, Dimitrios I

2014-07-01

Optical coherence tomography and intravascular ultrasound are the most widely used methodologies in clinical practice as they provide high resolution cross-sectional images that allow comprehensive visualization of the lumen and plaque morphology. Several methods have been developed in recent years to process the output of these imaging modalities, which allow fast, reliable and reproducible detection of the luminal borders and characterization of plaque composition. These methods have proven useful in the study of the atherosclerotic process as they have facilitated analysis of a vast amount of data. This review presents currently available intravascular ultrasound and optical coherence tomography processing methodologies for segmenting and characterizing the plaque area, highlighting their advantages and disadvantages, and discusses the future trends in intravascular imaging.

Fetal head detection and measurement in ultrasound images by an iterative randomized Hough transform

NASA Astrophysics Data System (ADS)

Lu, Wei; Tan, Jinglu; Floyd, Randall C.

2004-05-01

This paper describes an automatic method for measuring the biparietal diameter (BPD) and head circumference (HC) in ultrasound fetal images. A total of 217 ultrasound images were segmented by using a K-Mean classifier, and the head skull was detected in 214 of the 217 cases by an iterative randomized Hough transform developed for detection of incomplete curves in images with strong noise without user intervention. The automatic measurements were compared with conventional manual measurements by sonographers and a trained panel. The inter-run variations and differences between the automatic and conventional measurements were small compared with published inter-observer variations. The results showed that the automated measurements were as reliable as the expert measurements and more consistent. This method has great potential in clinical applications.

Ultrasound molecular imaging: Moving toward clinical translation.

PubMed

Abou-Elkacem, Lotfi; Bachawal, Sunitha V; Willmann, Jürgen K

2015-09-01

Ultrasound is a widely available, cost-effective, real-time, non-invasive and safe imaging modality widely used in the clinic for anatomical and functional imaging. With the introduction of novel molecularly-targeted ultrasound contrast agents, another dimension of ultrasound has become a reality: diagnosing and monitoring pathological processes at the molecular level. Most commonly used ultrasound molecular imaging contrast agents are micron sized, gas-containing microbubbles functionalized to recognize and attach to molecules expressed on inflamed or angiogenic vascular endothelial cells. There are several potential clinical applications currently being explored including earlier detection, molecular profiling, and monitoring of cancer, as well as visualization of ischemic memory in transient myocardial ischemia, monitoring of disease activity in inflammatory bowel disease, and assessment of arteriosclerosis. Recently, a first clinical grade ultrasound contrast agent (BR55), targeted at a molecule expressed in neoangiogenesis (vascular endothelial growth factor receptor type 2; VEGFR2) has been introduced and safety and feasibility of VEGFR2-targeted ultrasound imaging is being explored in first inhuman clinical trials in various cancer types. This review describes the design of ultrasound molecular imaging contrast agents, imaging techniques, and potential future clinical applications of ultrasound molecular imaging. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Intrauterine photoacoustic and ultrasound imaging probe

NASA Astrophysics Data System (ADS)

Miranda, Christopher; Barkley, Joel; Smith, Barbara S.

2018-04-01

Intrauterine photoacoustic and ultrasound imaging are probe-based imaging modalities with translational potential for use in detecting endometrial diseases. This deep-tissue imaging probe design allows for the retrofitting of commercially available endometrial sampling curettes. The imaging probe presented here has a 2.92-mm diameter and approximate length of 26 cm, which allows for entry into the human endometrial cavity, making it possible to use photoacoustic imaging and high-resolution ultrasound to characterize the uterus. We demonstrate the imaging probes' ability to provide structural information of an excised pig uterus using ultrasound imaging and detect photoacoustic signals at a radial depth of 1 cm.

Interference-free ultrasound imaging during HIFU therapy, using software tools

NASA Technical Reports Server (NTRS)

Vaezy, Shahram (Inventor); Held, Robert (Inventor); Sikdar, Siddhartha (Inventor); Managuli, Ravi (Inventor); Zderic, Vesna (Inventor)

2010-01-01

Disclosed herein is a method for obtaining a composite interference-free ultrasound image when non-imaging ultrasound waves would otherwise interfere with ultrasound imaging. A conventional ultrasound imaging system is used to collect frames of ultrasound image data in the presence of non-imaging ultrasound waves, such as high-intensity focused ultrasound (HIFU). The frames are directed to a processor that analyzes the frames to identify portions of the frame that are interference-free. Interference-free portions of a plurality of different ultrasound image frames are combined to generate a single composite interference-free ultrasound image that is displayed to a user. In this approach, a frequency of the non-imaging ultrasound waves is offset relative to a frequency of the ultrasound imaging waves, such that the interference introduced by the non-imaging ultrasound waves appears in a different portion of the frames.

Co-registered photoacoustic, thermoacoustic, and ultrasound mouse imaging

NASA Astrophysics Data System (ADS)

Reinecke, Daniel R.; Kruger, Robert A.; Lam, Richard B.; DelRio, Stephen P.

2010-02-01

We have constructed and tested a prototype test bed that allows us to form 3D photoacoustic CT images using near-infrared (NIR) irradiation (700 - 900 nm), 3D thermoacoustic CT images using microwave irradiation (434 MHz), and 3D ultrasound images from a commercial ultrasound scanner. The device utilizes a vertically oriented, curved array to capture the photoacoustic and thermoacoustic data. In addition, an 8-MHz linear array fixed in a horizontal position provides the ultrasound data. The photoacoustic and thermoacoustic data sets are co-registered exactly because they use the same detector. The ultrasound data set requires only simple corrections to co-register its images. The photoacoustic, thermoacoustic, and ultrasound images of mouse anatomy reveal complementary anatomic information as they exploit different contrast mechanisms. The thermoacoustic images differentiate between muscle, fat and bone. The photoacoustic images reveal the hemoglobin distribution, which is localized predominantly in the vascular space. The ultrasound images provide detailed information about the bony structures. Superposition of all three images onto a co-registered hybrid image shows the potential of a trimodal photoacoustic-thermoacoustic-ultrasound small-animal imaging system.

Hot topics in biomedical ultrasound: ultrasound therapy and its integration with ultrasonic imaging

NASA Astrophysics Data System (ADS)

Everbach, E. Carr

2005-09-01

Since the development of biomedical ultrasound imaging from sonar after WWII, there has been a clear divide between ultrasonic imaging and ultrasound therapy. While imaging techniques are designed to cause as little change as possible in the tissues through which ultrasound propagates, ultrasound therapy typically relies upon heating or acoustic cavitation to produce a desirable therapeutic effect. Concerns over the increasingly high acoustic outputs of diagnostic ultrasound scanners prompted the adoption of the Mechanical Index (MI) and Thermal Index (TI) in the early 1990s. Therapeutic applications of ultrasound, meanwhile, have evolved from deep tissue heating in sports medicine to include targeted drug delivery, tumor and plaque ablation, cauterization via high intensity focused ultrasound (HIFU), and accelerated dissolution of blood clots. The integration of ultrasonic imaging and therapy in one device is just beginning, but the promise of improved patient outcomes is balanced by regulatory and practical impediments.

Passive cavitation imaging with ultrasound arrays

PubMed Central

Salgaonkar, Vasant A.; Datta, Saurabh; Holland, Christy K.; Mast, T. Douglas

2009-01-01

A method is presented for passive imaging of cavitational acoustic emissions using an ultrasound array, with potential application in real-time monitoring of ultrasound ablation. To create such images, microbubble emissions were passively sensed by an imaging array and dynamically focused at multiple depths. In this paper, an analytic expression for a passive image is obtained by solving the Rayleigh–Sommerfield integral, under the Fresnel approximation, and passive images were simulated. A 192-element array was used to create passive images, in real time, from 520-kHz ultrasound scattered by a 1-mm steel wire. Azimuthal positions of this target were accurately estimated from the passive images. Next, stable and inertial cavitation was passively imaged in saline solution sonicated at 520 kHz. Bubble clusters formed in the saline samples were consistently located on both passive images and B-scans. Passive images were also created using broadband emissions from bovine liver sonicated at 2.2 MHz. Agreement was found between the images and source beam shape, indicating an ability to map therapeutic ultrasound beams in situ. The relation between these broadband emissions, sonication amplitude, and exposure conditions are discussed. PMID:20000921

Passive cavitation imaging with ultrasound arrays.

PubMed

Salgaonkar, Vasant A; Datta, Saurabh; Holland, Christy K; Mast, T Douglas

2009-12-01

A method is presented for passive imaging of cavitational acoustic emissions using an ultrasound array, with potential application in real-time monitoring of ultrasound ablation. To create such images, microbubble emissions were passively sensed by an imaging array and dynamically focused at multiple depths. In this paper, an analytic expression for a passive image is obtained by solving the Rayleigh-Sommerfield integral, under the Fresnel approximation, and passive images were simulated. A 192-element array was used to create passive images, in real time, from 520-kHz ultrasound scattered by a 1-mm steel wire. Azimuthal positions of this target were accurately estimated from the passive images. Next, stable and inertial cavitation was passively imaged in saline solution sonicated at 520 kHz. Bubble clusters formed in the saline samples were consistently located on both passive images and B-scans. Passive images were also created using broadband emissions from bovine liver sonicated at 2.2 MHz. Agreement was found between the images and source beam shape, indicating an ability to map therapeutic ultrasound beams in situ. The relation between these broadband emissions, sonication amplitude, and exposure conditions are discussed.

Review methods for image segmentation from computed tomography images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affectmore » the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.« less

Detecting stripe artifacts in ultrasound images.

PubMed

Maciak, Adam; Kier, Christian; Seidel, Günter; Meyer-Wiethe, Karsten; Hofmann, Ulrich G

2009-10-01

Brain perfusion diseases such as acute ischemic stroke are detectable through computed tomography (CT)-/magnetic resonance imaging (MRI)-based methods. An alternative approach makes use of ultrasound imaging. In this low-cost bedside method, noise and artifacts degrade the imaging process. Especially stripe artifacts show a similar signal behavior compared to acute stroke or brain perfusion diseases. This document describes how stripe artifacts can be detected and eliminated in ultrasound images obtained through harmonic imaging (HI). On the basis of this new method, both proper identification of areas with critically reduced brain tissue perfusion and classification between brain perfusion defects and ultrasound stripe artifacts are made possible.

Integrated circuit layer image segmentation

NASA Astrophysics Data System (ADS)

Masalskis, Giedrius; Petrauskas, Romas

2010-09-01

In this paper we present IC layer image segmentation techniques which are specifically created for precise metal layer feature extraction. During our research we used many samples of real-life de-processed IC metal layer images which were obtained using optical light microscope. We have created sequence of various image processing filters which provides segmentation results of good enough precision for our application. Filter sequences were fine tuned to provide best possible results depending on properties of IC manufacturing process and imaging technology. Proposed IC image segmentation filter sequences were experimentally tested and compared with conventional direct segmentation algorithms.

Partial segmental thrombosis of the corpus cavernosum (PSTCC) diagnosed by contrast-enhanced ultrasound: a case report.

PubMed

Sauer, Stephanie; Goltz, Jan P; Gassenmaier, Tobias; Kunz, Andreas S; Bley, Thorsten A; Klein, Detlef; Petritsch, Bernhard

2014-12-17

Partial segmental thrombosis of the corpus cavernosum (PSTCC) is a rare disease predominantly occurring in young men. Cardinal symptoms are pain and perineal swelling. Although several risk factors are described in the literature, the exact etiology of penile thrombosis remains unclear in most cases. MRI or ultrasound (US) is usually used for diagnosing this condition. We report a case of penile thrombosis after left-sided varicocele ligature in a young patient. The diagnosis was established using contrast-enhanced ultrasound (CEUS) and was confirmed by contrast-enhanced magnetic resonance imaging (ceMRI). Successful conservative treatment consisted of systemic anticoagulation using low molecular weight heparin and acetylsalicylic acid. PSTCC is a rare condition in young men and appears with massive pain and perineal swelling. In case of suspected PSTCC utilization of CEUS may be of diagnostic benefit.

Modulated Excitation Imaging System for Intravascular Ultrasound.

PubMed

Qiu, Weibao; Wang, Xingying; Chen, Yan; Fu, Qiang; Su, Min; Zhang, Lining; Xia, Jingjing; Dai, Jiyan; Zhang, Yaonan; Zheng, Hairong

2017-08-01

Advances in methodologies and tools often lead to new insights into cardiovascular diseases. Intravascular ultrasound (IVUS) is a well-established diagnostic method that provides high-resolution images of the vessel wall and atherosclerotic plaques. High-frequency (>50 MHz) ultrasound enables the spatial resolution of IVUS to approach that of optical imaging methods. However, the penetration depth decreases when using higher imaging frequencies due to the greater acoustic attenuation. An imaging method that improves the penetration depth of high-resolution IVUS would, therefore, be of major clinical importance. Modulated excitation imaging is known to allow ultrasound waves to penetrate further. This paper presents an ultrasound system specifically for modulated-excitation-based IVUS imaging. The system incorporates a high-voltage waveform generator and an image processing board that are optimized for IVUS applications. In addition, a miniaturized ultrasound transducer has been constructed using a Pb(Mg 1/3 Nb 2/3 )O 3 -PbTiO 3 single crystal to improve the ultrasound characteristics. The results show that the proposed system was able to provide increases of 86.7% in penetration depth and 9.6 dB in the signal-to-noise ratio for 60 MHz IVUS. In vitro tissue samples were also investigated to demonstrate the performance of the system.

Standards of ultrasound imaging of the adrenal glands

PubMed Central

Jakubowski, Wiesław S.; Dobruch-Sobczak, Katarzyna; Kasperlik-Załuska, Anna A.

2015-01-01

Adrenal glands are paired endocrine glands located over the upper renal poles. Adrenal pathologies have various clinical presentations. They can coexist with the hyperfunction of individual cortical zones or the medulla, insufficiency of the adrenal cortex or retained normal hormonal function. The most common adrenal masses are tumors incidentally detected in imaging examinations (ultrasound, tomography, magnetic resonance imaging), referred to as incidentalomas. They include a range of histopathological entities but cortical adenomas without hormonal hyperfunction are the most common. Each abdominal ultrasound scan of a child or adult should include the assessment of the suprarenal areas. If a previously non-reported, incidental solid focal lesion exceeding 1 cm (incidentaloma) is detected in the suprarenal area, computed tomography or magnetic resonance imaging should be conducted to confirm its presence and for differentiation and the tumor functional status should be determined. Ultrasound imaging is also used to monitor adrenal incidentaloma that is not eligible for a surgery. The paper presents recommendations concerning the performance and assessment of ultrasound examinations of the adrenal glands and their pathological lesions. The article includes new ultrasound techniques, such as tissue harmonic imaging, spatial compound imaging, three-dimensional ultrasound, elastography, contrast-enhanced ultrasound and parametric imaging. The guidelines presented above are consistent with the recommendations of the Polish Ultrasound Society. PMID:26807295

Automatic Contour Tracking in Ultrasound Images

ERIC Educational Resources Information Center

Li, Min; Kambhamettu, Chandra; Stone, Maureen

2005-01-01

In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a head and transducer support system (HATS). The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In…

Recent technological advancements in cardiac ultrasound imaging.

PubMed

Dave, Jaydev K; Mc Donald, Maureen E; Mehrotra, Praveen; Kohut, Andrew R; Eisenbrey, John R; Forsberg, Flemming

2018-03-01

About 92.1 million Americans suffer from at least one type of cardiovascular disease. Worldwide, cardiovascular diseases are the number one cause of death (about 31% of all global deaths). Recent technological advancements in cardiac ultrasound imaging are expected to aid in the clinical diagnosis of many cardiovascular diseases. This article provides an overview of such recent technological advancements, specifically focusing on tissue Doppler imaging, strain imaging, contrast echocardiography, 3D echocardiography, point-of-care echocardiography, 3D volumetric flow assessments, and elastography. With these advancements ultrasound imaging is rapidly changing the domain of cardiac imaging. The advantages offered by ultrasound imaging include real-time imaging, imaging at patient bed-side, cost-effectiveness and ionizing-radiation-free imaging. Along with these advantages, the steps taken towards standardization of ultrasound based quantitative markers, reviewed here, will play a major role in addressing the healthcare burden associated with cardiovascular diseases. Copyright © 2017 Elsevier B.V. All rights reserved.

Optical Detection of Ultrasound in Photoacoustic Imaging

PubMed Central

Dong, Biqin; Sun, Cheng; Zhang, Hao F.

2017-01-01

Objective Photoacoustic (PA) imaging emerges as a unique tool to study biological samples based on optical absorption contrast. In PA imaging, piezoelectric transducers are commonly used to detect laser-induced ultrasonic waves. However, they typically lack adequate broadband sensitivity at ultrasonic frequency higher than 100 MHz while their bulky size and optically opaque nature cause technical difficulties in integrating PA imaging with conventional optical imaging modalities. To overcome these limitations, optical methods of ultrasound detection were developed and shown their unique applications in photoacoustic imaging. Methods We provide an overview of recent technological advances in optical methods of ultrasound detection and their applications in PA imaging. A general theoretical framework describing sensitivity, bandwidth, and angular responses of optical ultrasound detection is also introduced. Results Optical methods of ultrasound detection can provide improved detection angle and sensitivity over significantly extended bandwidth. In addition, its versatile variants also offer additional advantages, such as device miniaturization, optical transparency, mechanical flexibility, minimal electrical/mechanical crosstalk, and potential noncontact PA imaging. Conclusion The optical ultrasound detection methods discussed in this review and their future evolution may play an important role in photoacoustic imaging for biomedical study and clinical diagnosis. PMID:27608445

Validation tools for image segmentation

NASA Astrophysics Data System (ADS)

Padfield, Dirk; Ross, James

2009-02-01

A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.

Colour application on mammography image segmentation

NASA Astrophysics Data System (ADS)

Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

2017-09-01

The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).

Image Segmentation Using Minimum Spanning Tree

NASA Astrophysics Data System (ADS)

Dewi, M. P.; Armiati, A.; Alvini, S.

2018-04-01

This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.

Intelligent multi-spectral IR image segmentation

NASA Astrophysics Data System (ADS)

Lu, Thomas; Luong, Andrew; Heim, Stephen; Patel, Maharshi; Chen, Kang; Chao, Tien-Hsin; Chow, Edward; Torres, Gilbert

2017-05-01

This article presents a neural network based multi-spectral image segmentation method. A neural network is trained on the selected features of both the objects and background in the longwave (LW) Infrared (IR) images. Multiple iterations of training are performed until the accuracy of the segmentation reaches satisfactory level. The segmentation boundary of the LW image is used to segment the midwave (MW) and shortwave (SW) IR images. A second neural network detects the local discontinuities and refines the accuracy of the local boundaries. This article compares the neural network based segmentation method to the Wavelet-threshold and Grab-Cut methods. Test results have shown increased accuracy and robustness of this segmentation scheme for multi-spectral IR images.

Development of ultrasound bioprobe for biological imaging

PubMed Central

Shekhawat, Gajendra S.; Dudek, Steven M.; Dravid, Vinayak P.

2017-01-01

We report the development of an ultrasound bioprobe for in vitro molecular imaging. In this method, the phase of the scattered ultrasound wave is mapped to provide in vitro and intracellular imaging with nanometer-scale resolution under physiological conditions. We demonstrated the technique by successfully imaging a magnetic core in silica core shells and the stiffness image of intracellular fibers in endothelial cells that were stimulated with thrombin. The findings demonstrate a significant advancement in high-resolution ultrasound imaging of biological systems with acoustics under physiological conditions. These will open up various applications in biomedical and molecular imaging with subsurface resolution down to the nanometer scale. PMID:29075667

Segmentation of 830- and 1310-nm LASIK corneal optical coherence tomography images

NASA Astrophysics Data System (ADS)

Li, Yan; Shekhar, Raj; Huang, David

2002-05-01

Optical coherence tomography (OCT) provides a non-contact and non-invasive means to visualize the corneal anatomy at micron scale resolution. We obtained corneal images from an arc-scanning (converging) OCT system operating at a wavelength of 830nm and a fan-shaped-scanning high-speed OCT system with an operating wavelength of 1310nm. Different scan protocols (arc/fan) and data acquisition rates, as well as wavelength dependent bio-tissue backscatter contrast and optical absorption, make the images acquired using the two systems different. We developed image-processing algorithms to automatically detect the air-tear interface, epithelium-Bowman's layer interface, laser in-situ keratomileusis (LASIK) flap interface, and the cornea-aqueous interface in both kinds of images. The overall segmentation scheme for 830nm and 1310nm OCT images was similar, although different strategies were adopted for specific processing approaches. Ultrasound pachymetry measurements of the corneal thickness and Placido-ring based corneal topography measurements of the corneal curvature were made on the same day as the OCT examination. Anterior/posterior corneal surface curvature measurement with OCT was also investigated. Results showed that automated segmentation of OCT images could evaluate anatomic outcome of LASIK surgery.

Robust boundary detection of left ventricles on ultrasound images using ASM-level set method.

PubMed

Zhang, Yaonan; Gao, Yuan; Li, Hong; Teng, Yueyang; Kang, Yan

2015-01-01

Level set method has been widely used in medical image analysis, but it has difficulties when being used in the segmentation of left ventricular (LV) boundaries on echocardiography images because the boundaries are not very distinguish, and the signal-to-noise ratio of echocardiography images is not very high. In this paper, we introduce the Active Shape Model (ASM) into the traditional level set method to enforce shape constraints. It improves the accuracy of boundary detection and makes the evolution more efficient. The experiments conducted on the real cardiac ultrasound image sequences show a positive and promising result.

Fetal intracranial hemorrhage. Imaging by ultrasound and magnetic resonance imaging.

PubMed

Kirkinen, P; Partanen, K; Ryynänen, M; Ordén, M R

1997-08-01

To describe the magnetic resonance imaging (MRI) findings associated with fetal intracranial hemorrhage and to compare them with ultrasound findings. In four pregnancies complicated by fetal intracranial hemorrhage, fetal imaging was carried out using T2-weighted fast spin echo sequences and T1-weighted fast low angle shot imaging sequences and by transabdominal ultrasonography. An antepartum diagnosis of hemorrhage was made by ultrasound in one case and by MRI in two. Retrospectively, the hemorrhagic area could be identified from the MRI images in an additional two cases and from the ultrasound images in one case. In the cases of intraventricular hemorrhage, the MRI signal intensity in the T1-weighted images was increased in the hemorrhagic area as compared to the contralateral ventricle and brain parenchyma. In a case with subdural hemorrhage, T2-weighted MRI signals from the hemorrhagic area changed from low-to high-intensity signals during four weeks of follow-up. Better imaging of the intracranial anatomy was possible by MRI than by transabdominal ultrasonography. MRI can be used for imaging and dating fetal intracranial hemorrhages. Variable ultrasound and MRI findings are associated with this complication, depending on the age and location of the hemorrhage.

High-Accuracy Ultrasound Contrast Agent Detection Method for Diagnostic Ultrasound Imaging Systems.

PubMed

Ito, Koichi; Noro, Kazumasa; Yanagisawa, Yukari; Sakamoto, Maya; Mori, Shiro; Shiga, Kiyoto; Kodama, Tetsuya; Aoki, Takafumi

2015-12-01

An accurate method for detecting contrast agents using diagnostic ultrasound imaging systems is proposed. Contrast agents, such as microbubbles, passing through a blood vessel during ultrasound imaging are detected as blinking signals in the temporal axis, because their intensity value is constantly in motion. Ultrasound contrast agents are detected by evaluating the intensity variation of a pixel in the temporal axis. Conventional methods are based on simple subtraction of ultrasound images to detect ultrasound contrast agents. Even if the subject moves only slightly, a conventional detection method will introduce significant error. In contrast, the proposed technique employs spatiotemporal analysis of the pixel intensity variation over several frames. Experiments visualizing blood vessels in the mouse tail illustrated that the proposed method performs efficiently compared with conventional approaches. We also report that the new technique is useful for observing temporal changes in microvessel density in subiliac lymph nodes containing tumors. The results are compared with those of contrast-enhanced computed tomography. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. In this paper, we present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. Here, the authors present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

B-Mode ultrasound pose recovery via surgical fiducial segmentation and tracking

NASA Astrophysics Data System (ADS)

Asoni, Alessandro; Ketcha, Michael; Kuo, Nathanael; Chen, Lei; Boctor, Emad; Coon, Devin; Prince, Jerry L.

2015-03-01

Ultrasound Doppler imaging may be used to detect blood clots after surgery, a common problem. However, this requires consistent probe positioning over multiple time instances and therefore significant sonographic expertise. Analysis of ultrasound B-mode images of a fiducial implanted at the surgical site offers a landmark to guide a user to the same location repeatedly. We demonstrate that such an implanted fiducial may be successfully detected and tracked to calculate pose and guide a clinician consistently to the site of surgery, potentially reducing the ultrasound experience required for point of care monitoring.

Ultrasound image guidance of cardiac interventions

NASA Astrophysics Data System (ADS)

Peters, Terry M.; Pace, Danielle F.; Lang, Pencilla; Guiraudon, Gérard M.; Jones, Douglas L.; Linte, Cristian A.

2011-03-01

Surgical procedures often have the unfortunate side-effect of causing the patient significant trauma while accessing the target site. Indeed, in some cases the trauma inflicted on the patient during access to the target greatly exceeds that caused by performing the therapy. Heart disease has traditionally been treated surgically using open chest techniques with the patient being placed "on pump" - i.e. their circulation being maintained by a cardio-pulmonary bypass or "heart-lung" machine. Recently, techniques have been developed for performing minimally invasive interventions on the heart, obviating the formerly invasive procedures. These new approaches rely on pre-operative images, combined with real-time images acquired during the procedure. Our approach is to register intra-operative images to the patient, and use a navigation system that combines intra-operative ultrasound with virtual models of instrumentation that has been introduced into the chamber through the heart wall. This paper illustrates the problems associated with traditional ultrasound guidance, and reviews the state of the art in real-time 3D cardiac ultrasound technology. In addition, it discusses the implementation of an image-guided intervention platform that integrates real-time ultrasound with a virtual reality environment, bringing together the pre-operative anatomy derived from MRI or CT, representations of tracked instrumentation inside the heart chamber, and the intra-operatively acquired ultrasound images.

Image Information Mining Utilizing Hierarchical Segmentation

NASA Technical Reports Server (NTRS)

Tilton, James C.; Marchisio, Giovanni; Koperski, Krzysztof; Datcu, Mihai

2002-01-01

The Hierarchical Segmentation (HSEG) algorithm is an approach for producing high quality, hierarchically related image segmentations. The VisiMine image information mining system utilizes clustering and segmentation algorithms for reducing visual information in multispectral images to a manageable size. The project discussed herein seeks to enhance the VisiMine system through incorporating hierarchical segmentations from HSEG into the VisiMine system.

Focused ultrasound thermal therapy system with ultrasound image guidance and temperature measurement feedback.

PubMed

Lin, Kao-Han; Young, Sun-Yi; Hsu, Ming-Chuan; Chan, Hsu; Chen, Yung-Yaw; Lin, Win-Li

2008-01-01

In this study, we developed a focused ultrasound (FUS) thermal therapy system with ultrasound image guidance and thermocouple temperature measurement feedback. Hydraulic position devices and computer-controlled servo motors were used to move the FUS transducer to the desired location with the measurement of actual movement by linear scale. The entire system integrated automatic position devices, FUS transducer, power amplifier, ultrasound image system, and thermocouple temperature measurement into a graphical user interface. For the treatment procedure, a thermocouple was implanted into a targeted treatment region in a tissue-mimicking phantom under ultrasound image guidance, and then the acoustic interference pattern formed by image ultrasound beam and low-power FUS beam was employed as image guidance to move the FUS transducer to have its focal zone coincident with the thermocouple tip. The thermocouple temperature rise was used to determine the sonication duration for a suitable thermal lesion as a high power was turned on and ultrasound image was used to capture the thermal lesion formation. For a multiple lesion formation, the FUS transducer was moved under the acoustic interference guidance to a new location and then it sonicated with the same power level and duration. This system was evaluated and the results showed that it could perform two-dimensional motion control to do a two-dimensional thermal therapy with a small localization error 0.5 mm. Through the user interface, the FUS transducer could be moved to heat the target region with the guidance of ultrasound image and acoustic interference pattern. The preliminary phantom experimental results demonstrated that the system could achieve the desired treatment plan satisfactorily.

Three-dimensional ultrasound imaging of the prostate

NASA Astrophysics Data System (ADS)

Fenster, Aaron; Downey, Donal B.

1999-05-01

Ultrasonography, a widely used imaging modality for the diagnosis and staging of many diseases, is an important cost- effective technique, however, technical improvements are necessary to realize its full potential. Two-dimensional viewing of 3D anatomy, using conventional ultrasonography, limits our ability to quantify and visualize most diseases, causing, in part, the reported variability in diagnosis and ultrasound guided therapy and surgery. This occurs because 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 operator variability and incorrect diagnoses. In addition, the 2D ultrasound image represents a single thin plane at some arbitrary angle in the body. It is difficult to localize and reproduce the image plane subsequently, making conventional ultrasonography unsatisfactory for follow-up studies and for monitoring therapy. Our efforts have focused on overcoming these deficiencies by developing 3D ultrasound imaging techniques that can acquire B-mode, color Doppler and power Doppler images. An inexpensive desktop computer is used to reconstruct the information in 3D, and then is also used for interactive viewing of the 3D images. We have used 3D ultrasound images for the diagnosis of prostate cancer, carotid disease, breast cancer and liver disease and for applications in obstetrics and gynecology. In addition, we have also used 3D ultrasonography for image-guided minimally invasive therapeutic applications of the prostate such as cryotherapy and brachytherapy.

Detecting breast microcalcifications using super-resolution ultrasound imaging: a clinical study

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Labyed, Yassin; Hanson, Kenneth; Sandoval, Daniel; Pohl, Jennifer; Williamson, Michael

2013-03-01

Imaging breast microcalcifications is crucial for early detection and diagnosis of breast cancer. It is challenging for current clinical ultrasound to image breast microcalcifications. However, new imaging techniques using data acquired with a synthetic-aperture ultrasound system have the potential to significantly improve ultrasound imaging. We recently developed a super-resolution ultrasound imaging method termed the phase-coherent multiple-signal classification (PC-MUSIC). This signal subspace method accounts for the phase response of transducer elements to improve image resolution. In this paper, we investigate the clinical feasibility of our super-resolution ultrasound imaging method for detecting breast microcalcifications. We use our custom-built, real-time synthetic-aperture ultrasound system to acquire breast ultrasound data for 40 patients whose mammograms show the presence of breast microcalcifications. We apply our super-resolution ultrasound imaging method to the patient data, and produce clear images of breast calcifications. Our super-resolution ultrasound PC-MUSIC imaging with synthetic-aperture ultrasound data can provide a new imaging modality for detecting breast microcalcifications in clinic without using ionizing radiation.

A Fully-Automatic Method to Segment the Carotid Artery Layers in Ultrasound Imaging: Application to Quantify the Compression-Decompression Pattern of the Intima-Media Complex During the Cardiac Cycle.

PubMed

Zahnd, Guillaume; Kapellas, Kostas; van Hattem, Martijn; van Dijk, Anouk; Sérusclat, André; Moulin, Philippe; van der Lugt, Aad; Skilton, Michael; Orkisz, Maciej

2017-01-01

The aim of this study was to introduce and evaluate a contour segmentation method to extract the interfaces of the intima-media complex in carotid B-mode ultrasound images. The method was applied to assess the temporal variation of intima-media thickness during the cardiac cycle. The main methodological contribution of the proposed approach is the introduction of an augmented dimension to process 2-D images in a 3-D space. The third dimension, which is added to the two spatial dimensions of the image, corresponds to the tentative local thickness of the intima-media complex. The method is based on a dynamic programming scheme that runs in a 3-D space generated with a shape-adapted filter bank. The optimal solution corresponds to a single medial axis representation that fully describes the two anatomical interfaces of the arterial wall. The method is fully automatic and does not require any input from the user. The method was trained on 60 subjects and validated on 184 other subjects from six different cohorts and four different medical centers. The arterial wall was successfully segmented in all analyzed images (average pixel size = 57 ± 20 mm), with average segmentation errors of 47 ± 70 mm for the lumen-intima interface, 55 ± 68 mm for the media-adventitia interface and 66 ± 90 mm for the intima-media thickness. The amplitude of the temporal variations in IMT during the cardiac cycle was significantly higher in the diseased population than in healthy volunteers (106 ± 48 vs. 86 ± 34 mm, p = 0.001). The introduced framework is a promising approach to investigate an emerging functional parameter of the arterial wall by assessing the cyclic compression-decompression pattern of the tissues. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Nonlinear ultrasound imaging of nanoscale acoustic biomolecules

NASA Astrophysics Data System (ADS)

Maresca, David; Lakshmanan, Anupama; Lee-Gosselin, Audrey; Melis, Johan M.; Ni, Yu-Li; Bourdeau, Raymond W.; Kochmann, Dennis M.; Shapiro, Mikhail G.

2017-02-01

Ultrasound imaging is widely used to probe the mechanical structure of tissues and visualize blood flow. However, the ability of ultrasound to observe specific molecular and cellular signals is limited. Recently, a unique class of gas-filled protein nanostructures called gas vesicles (GVs) was introduced as nanoscale (˜250 nm) contrast agents for ultrasound, accompanied by the possibilities of genetic engineering, imaging of targets outside the vasculature and monitoring of cellular signals such as gene expression. These possibilities would be aided by methods to discriminate GV-generated ultrasound signals from anatomical background. Here, we show that the nonlinear response of engineered GVs to acoustic pressure enables selective imaging of these nanostructures using a tailored amplitude modulation strategy. Finite element modeling predicted a strongly nonlinear mechanical deformation and acoustic response to ultrasound in engineered GVs. This response was confirmed with ultrasound measurements in the range of 10 to 25 MHz. An amplitude modulation pulse sequence based on this nonlinear response allows engineered GVs to be distinguished from linear scatterers and other GV types with a contrast ratio greater than 11.5 dB. We demonstrate the effectiveness of this nonlinear imaging strategy in vitro, in cellulo, and in vivo.

Method and system to synchronize acoustic therapy with ultrasound imaging

NASA Technical Reports Server (NTRS)

Hossack, James (Inventor); Owen, Neil (Inventor); Bailey, Michael R. (Inventor)

2009-01-01

Interference in ultrasound imaging when used in connection with high intensity focused ultrasound (HIFU) is avoided by employing a synchronization signal to control the HIFU signal. Unless the timing of the HIFU transducer is controlled, its output will substantially overwhelm the signal produced by ultrasound imaging system and obscure the image it produces. The synchronization signal employed to control the HIFU transducer is obtained without requiring modification of the ultrasound imaging system. Signals corresponding to scattered ultrasound imaging waves are collected using either the HIFU transducer or a dedicated receiver. A synchronization processor manipulates the scattered ultrasound imaging signals to achieve the synchronization signal, which is then used to control the HIFU bursts so as to substantially reduce or eliminate HIFU interference in the ultrasound image. The synchronization processor can alternatively be implemented using a computing device or an application-specific circuit.

A Dual-Modality System for Both Multi-Color Ultrasound-Switchable Fluorescence and Ultrasound Imaging

PubMed Central

Kandukuri, Jayanth; Yu, Shuai; Cheng, Bingbing; Bandi, Venugopal; D’Souza, Francis; Nguyen, Kytai T.; Hong, Yi; Yuan, Baohong

2017-01-01

Simultaneous imaging of multiple targets (SIMT) in opaque biological tissues is an important goal for molecular imaging in the future. Multi-color fluorescence imaging in deep tissues is a promising technology to reach this goal. In this work, we developed a dual-modality imaging system by combining our recently developed ultrasound-switchable fluorescence (USF) imaging technology with the conventional ultrasound (US) B-mode imaging. This dual-modality system can simultaneously image tissue acoustic structure information and multi-color fluorophores in centimeter-deep tissue with comparable spatial resolutions. To conduct USF imaging on the same plane (i.e., x-z plane) as US imaging, we adopted two 90°-crossed ultrasound transducers with an overlapped focal region, while the US transducer (the third one) was positioned at the center of these two USF transducers. Thus, the axial resolution of USF is close to the lateral resolution, which allows a point-by-point USF scanning on the same plane as the US imaging. Both multi-color USF and ultrasound imaging of a tissue phantom were demonstrated. PMID:28165390

Focused Ultrasound Steering for Harmonic Motion Imaging.

PubMed

Han, Yang; Payen, Thomas; Wang, Shutao; Konofagou, Elisa

2018-02-01

Harmonic motion imaging (HMI) is a radiation-force-based ultrasound elasticity imaging technique, which is designed for both tissue relative stiffness imaging and reliable high-intensity focused ultrasound treatment monitoring. The objective of this letter is to develop and demonstrate the feasibility of 2-D focused ultrasound (FUS) beam steering for HMI using a 93-element, FUS phased array. HMI with steered FUS beam was acquired in tissue-mimicking phantoms. The HMI displacement was imaged within the steering range of ±1.7 mm laterally and ±2 mm axially. Using the steered FUS beam, HMI can be used to image a larger tissue volume with higher efficiency and without requiring mechanical movement of the transducer.

Design and development of an ultrasound calibration phantom and system

NASA Astrophysics Data System (ADS)

Cheng, Alexis; Ackerman, Martin K.; Chirikjian, Gregory S.; Boctor, Emad M.

2014-03-01

Image-guided surgery systems are often used to provide surgeons with informational support. Due to several unique advantages such as ease of use, real-time image acquisition, and no ionizing radiation, ultrasound is a common medical imaging modality used in image-guided surgery systems. To perform advanced forms of guidance with ultrasound, such as virtual image overlays or automated robotic actuation, an ultrasound calibration process must be performed. This process recovers the rigid body transformation between a tracked marker attached to the ultrasound transducer and the ultrasound image. A phantom or model with known geometry is also required. In this work, we design and test an ultrasound calibration phantom and software. The two main considerations in this work are utilizing our knowledge of ultrasound physics to design the phantom and delivering an easy to use calibration process to the user. We explore the use of a three-dimensional printer to create the phantom in its entirety without need for user assembly. We have also developed software to automatically segment the three-dimensional printed rods from the ultrasound image by leveraging knowledge about the shape and scale of the phantom. In this work, we present preliminary results from using this phantom to perform ultrasound calibration. To test the efficacy of our method, we match the projection of the points segmented from the image to the known model and calculate a sum squared difference between each point for several combinations of motion generation and filtering methods. The best performing combination of motion and filtering techniques had an error of 1.56 mm and a standard deviation of 1.02 mm.

Nonlocal Total-Variation-Based Speckle Filtering for Ultrasound Images.

PubMed

Wen, Tiexiang; Gu, Jia; Li, Ling; Qin, Wenjian; Wang, Lei; Xie, Yaoqin

2016-07-01

Ultrasound is one of the most important medical imaging modalities for its real-time and portable imaging advantages. However, the contrast resolution and important details are degraded by the speckle in ultrasound images. Many speckle filtering methods have been developed, but they are suffered from several limitations, difficult to reach a balance between speckle reduction and edge preservation. In this paper, an adaptation of the nonlocal total variation (NLTV) filter is proposed for speckle reduction in ultrasound images. The speckle is modeled via a signal-dependent noise distribution for the log-compressed ultrasound images. Instead of the Euclidian distance, the statistical Pearson distance is introduced in this study for the similarity calculation between image patches via the Bayesian framework. And the Split-Bregman fast algorithm is used to solve the adapted NLTV despeckling functional. Experimental results on synthetic and clinical ultrasound images and comparisons with some classical and recent algorithms are used to demonstrate its improvements in both speckle noise reduction and tissue boundary preservation for ultrasound images. © The Author(s) 2015.

Ultrasound Imaging Velocimetry: a review

NASA Astrophysics Data System (ADS)

Poelma, Christian

2017-01-01

Whole-field velocity measurement techniques based on ultrasound imaging (a.k.a. `ultrasound imaging velocimetry' or `echo-PIV') have received significant attention from the fluid mechanics community in the last decade, in particular because of their ability to obtain velocity fields in flows that elude characterisation by conventional optical methods. In this review, an overview is given of the history, typical components and challenges of these techniques. The basic principles of ultrasound image formation are summarised, as well as various techniques to estimate flow velocities; the emphasis is on correlation-based techniques. Examples are given for a wide range of applications, including in vivo cardiovascular flow measurements, the characterisation of sediment transport and the characterisation of complex non-Newtonian fluids. To conclude, future opportunities are identified. These encompass not just optimisation of the accuracy and dynamic range, but also extension to other application areas.

WE-AB-206-01: Diagnostic Ultrasound Imaging Quality Assurance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zagzebski, J.

The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. The goal of this ultrasound hands-on workshop is to demonstrate quality control (QC) testing in diagnostic ultrasound and to provide updates in ACR ultrasound accreditation requirements. The first half of this workshop will include two presentations reviewing diagnostic ultrasound QA/QC and ACR ultrasound accreditation requirements. The second half of the workshop will include live demonstrations of basic QC tests. An array of ultrasound testing phantoms and ultrasound scanners will be available for attendees to learn diagnostic ultrasound QC in a hands-on environmentmore » with live demonstrations and on-site instructors. The targeted attendees are medical physicists in diagnostic imaging. Learning Objectives: Gain familiarity with common elements of a QA/QC program for diagnostic ultrasound imaging dentify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools Learn ACR ultrasound accreditation requirements Jennifer Walter is an employee of American College of Radiology on Ultrasound Accreditation.« less

High-frequency ultrasound imaging for breast cancer biopsy guidance

PubMed Central

Cummins, Thomas; Yoon, Changhan; Choi, Hojong; Eliahoo, Payam; Kim, Hyung Ham; Yamashita, Mary W.; Hovanessian-Larsen, Linda J.; Lang, Julie E.; Sener, Stephen F.; Vallone, John; Martin, Sue E.; Kirk Shung, K.

2015-01-01

Abstract. Image-guided core needle biopsy is the current gold standard for breast cancer diagnosis. Microcalcifications, an important radiographic finding on mammography suggestive of early breast cancer such as ductal carcinoma in situ, are usually biopsied under stereotactic guidance. This procedure, however, is uncomfortable for patients and requires the use of ionizing radiation. It would be preferable to biopsy microcalcifications under ultrasound guidance since it is a faster procedure, more comfortable for the patient, and requires no radiation. However, microcalcifications cannot reliably be detected with the current standard ultrasound imaging systems. This study is motivated by the clinical need for real-time high-resolution ultrasound imaging of microcalcifications, so that biopsies can be accurately performed under ultrasound guidance. We have investigated how high-frequency ultrasound imaging can enable visualization of microstructures in ex vivo breast tissue biopsy samples. We generated B-mode images of breast tissue and applied the Nakagami filtering technique to help refine image output so that microcalcifications could be better assessed during ultrasound-guided core biopsies. We describe the preliminary clinical results of high-frequency ultrasound imaging of ex vivo breast biopsy tissue with microcalcifications and without Nakagami filtering and the correlation of these images with the pathology examination by hematoxylin and eosin stain and whole slide digital scanning. PMID:26693167

Carotid Ultrasound Imaging

MedlinePlus

... the patient. Because ultrasound images are captured in real-time, they can show the structure and movement of ... by a computer, which in turn creates a real-time picture on the monitor. One or more frames ...

Performance evaluation of image segmentation algorithms on microscopic image data.

PubMed

Beneš, Miroslav; Zitová, Barbara

2015-01-01

In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning, there is no universal and 'the best' method yet. Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thus, the issue of selecting suitable method for a given set of image data is of big interest. We carried out a large number of experiments with a variety of segmentation methods to evaluate the behaviour of individual approaches on the testing set of microscopic images (cross-section images taken in three different modalities from the field of art restoration). The segmentation results were assessed by several indices used for measuring the output quality of image segmentation algorithms. In the end, the benefit of segmentation combination approach is studied and applicability of achieved results on another representatives of microscopic data category - biological samples - is shown. © 2014 The Authors Journal of Microscopy © 2014 Royal Microscopical Society.

Hybrid MRI-Ultrasound acquisitions, and scannerless real-time imaging.

PubMed

Preiswerk, Frank; Toews, Matthew; Cheng, Cheng-Chieh; Chiou, Jr-Yuan George; Mei, Chang-Sheng; Schaefer, Lena F; Hoge, W Scott; Schwartz, Benjamin M; Panych, Lawrence P; Madore, Bruno

2017-09-01

To combine MRI, ultrasound, and computer science methodologies toward generating MRI contrast at the high frame rates of ultrasound, inside and even outside the MRI bore. A small transducer, held onto the abdomen with an adhesive bandage, collected ultrasound signals during MRI. Based on these ultrasound signals and their correlations with MRI, a machine-learning algorithm created synthetic MR images at frame rates up to 100 per second. In one particular implementation, volunteers were taken out of the MRI bore with the ultrasound sensor still in place, and MR images were generated on the basis of ultrasound signal and learned correlations alone in a "scannerless" manner. Hybrid ultrasound-MRI data were acquired in eight separate imaging sessions. Locations of liver features, in synthetic images, were compared with those from acquired images: The mean error was 1.0 pixel (2.1 mm), with best case 0.4 and worst case 4.1 pixels (in the presence of heavy coughing). For results from outside the bore, qualitative validation involved optically tracked ultrasound imaging with/without coughing. The proposed setup can generate an accurate stream of high-speed MR images, up to 100 frames per second, inside or even outside the MR bore. Magn Reson Med 78:897-908, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Brain Tumor Image Segmentation in MRI Image

NASA Astrophysics Data System (ADS)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Automated detection and segmentation of follicles in 3D ultrasound for assisted reproduction

NASA Astrophysics Data System (ADS)

Narayan, Nikhil S.; Sivanandan, Srinivasan; Kudavelly, Srinivas; Patwardhan, Kedar A.; Ramaraju, G. A.

2018-02-01

Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper, we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function to perform mean-shift based follicle center detection. Max-flow algorithm is used for segmentation and gray weighted distance transform is employed for post-processing the results. We have obtained state-of-the-art results with a true positive detection rate of >90% on 26 3D volumes with 323 follicles.

Metric Learning to Enhance Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Thompson, David R.; Castano, Rebecca; Bue, Brian; Gilmore, Martha S.

2013-01-01

Unsupervised hyperspectral image segmentation can reveal spatial trends that show the physical structure of the scene to an analyst. They highlight borders and reveal areas of homogeneity and change. Segmentations are independently helpful for object recognition, and assist with automated production of symbolic maps. Additionally, a good segmentation can dramatically reduce the number of effective spectra in an image, enabling analyses that would otherwise be computationally prohibitive. Specifically, using an over-segmentation of the image instead of individual pixels can reduce noise and potentially improve the results of statistical post-analysis. In this innovation, a metric learning approach is presented to improve the performance of unsupervised hyperspectral image segmentation. The prototype demonstrations attempt a superpixel segmentation in which the image is conservatively over-segmented; that is, the single surface features may be split into multiple segments, but each individual segment, or superpixel, is ensured to have homogenous mineralogy.

Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiaofeng, E-mail: xyang43@emory.edu; Rossi, Peter; Ogunleye, Tomi

2014-11-01

Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approachmore » that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7

Prostate CT segmentation method based on nonrigid registration in ultrasound-guided CT-based HDR prostate brachytherapy

PubMed Central

Yang, Xiaofeng; Rossi, Peter; Ogunleye, Tomi; Marcus, David M.; Jani, Ashesh B.; Mao, Hui; Curran, Walter J.; Liu, Tian

2014-01-01

Purpose: The technological advances in real-time ultrasound image guidance for high-dose-rate (HDR) prostate brachytherapy have placed this treatment modality at the forefront of innovation in cancer radiotherapy. Prostate HDR treatment often involves placing the HDR catheters (needles) into the prostate gland under the transrectal ultrasound (TRUS) guidance, then generating a radiation treatment plan based on CT prostate images, and subsequently delivering high dose of radiation through these catheters. The main challenge for this HDR procedure is to accurately segment the prostate volume in the CT images for the radiation treatment planning. In this study, the authors propose a novel approach that integrates the prostate volume from 3D TRUS images into the treatment planning CT images to provide an accurate prostate delineation for prostate HDR treatment. Methods: The authors’ approach requires acquisition of 3D TRUS prostate images in the operating room right after the HDR catheters are inserted, which takes 1–3 min. These TRUS images are used to create prostate contours. The HDR catheters are reconstructed from the intraoperative TRUS and postoperative CT images, and subsequently used as landmarks for the TRUS–CT image fusion. After TRUS–CT fusion, the TRUS-based prostate volume is deformed to the CT images for treatment planning. This method was first validated with a prostate-phantom study. In addition, a pilot study of ten patients undergoing HDR prostate brachytherapy was conducted to test its clinical feasibility. The accuracy of their approach was assessed through the locations of three implanted fiducial (gold) markers, as well as T2-weighted MR prostate images of patients. Results: For the phantom study, the target registration error (TRE) of gold-markers was 0.41 ± 0.11 mm. For the ten patients, the TRE of gold markers was 1.18 ± 0.26 mm; the prostate volume difference between the authors’ approach and the MRI-based volume was 7.28% ± 0

Musculoskeletal ultrasound and other imaging modalities in rheumatoid arthritis.

PubMed

Ohrndorf, Sarah; Werner, Stephanie G; Finzel, Stephanie; Backhaus, Marina

2013-05-01

This review refers to the use of musculoskeletal ultrasound in patients with rheumatoid arthritis (RA) both in clinical practice and research. Furthermore, other novel sensitive imaging modalities (high resolution peripheral quantitative computed tomography and fluorescence optical imaging) are introduced in this article. Recently published ultrasound studies presented power Doppler activity by ultrasound highly predictive for later radiographic erosions in patients with RA. Another study presented synovitis detected by ultrasound being predictive of subsequent structural radiographic destruction irrespective of the ultrasound modality (grayscale ultrasound/power Doppler ultrasound). Further studies are currently under way which prove ultrasound findings as imaging biomarkers in the destructive process of RA. Other introduced novel imaging modalities are in the validation process to prove their impact and significance in inflammatory joint diseases. The introduced imaging modalities show different sensitivities and specificities as well as strength and weakness belonging to the assessment of inflammation, differentiation of the involved structures and radiological progression. The review tries to give an answer regarding how to best integrate them into daily clinical practice with the aim to improve the diagnostic algorithms, the daily patient care and, furthermore, the disease's outcome.

Research on the lesion segmentation of breast tumor MR images based on FCM-DS theory

NASA Astrophysics Data System (ADS)

Zhang, Liangbin; Ma, Wenjun; Shen, Xing; Li, Yuehua; Zhu, Yuemin; Chen, Li; Zhang, Su

2017-03-01

Magnetic resonance imaging (MRI) plays an important role in the treatment of breast tumor by high intensity focused ultrasound (HIFU). The doctors evaluate the scale, distribution and the statement of benign or malignancy of breast tumor by analyzing variety modalities of MRI, such as the T2, DWI and DCE images for making accurate preoperative treatment plan and evaluating the effect of the operation. This paper presents a method of lesion segmentation of breast tumor based on FCM-DS theory. Fuzzy c-means clustering (FCM) algorithm combined with Dempster-Shafer (DS) theory is used to process the uncertainty of information, segmenting the lesion areas on DWI and DCE modalities of MRI and reducing the scale of the uncertain parts. Experiment results show that FCM-DS can fuse the DWI and DCE images to achieve accurate segmentation and display the statement of benign or malignancy of lesion area by Time-Intensity Curve (TIC), which could be beneficial in making preoperative treatment plan and evaluating the effect of the therapy.

High-resolution ultrasonic imaging of the posterior segment.

PubMed

Coleman, D Jackson; Silverman, Ronald H; Chabi, Almira; Rondeau, Mark J; Shung, K Kirk; Cannata, Jon; Lincoff, Harvey

2004-07-01

Conventional ophthalmic ultrasonography is performed using 10-megahertz (MHz) transducers. Our aim was to explore the use of higher frequency ultrasound to provide improved resolution of the posterior pole. Prospective case series. One normal subject and 5 subjects with pathologies affecting the posterior coats, including nevii, small melanomas, and macular hole. We modeled the frequency-dependent attenuation of ultrasound across the eye to develop an understanding of the range of frequencies that might be practically applied for imaging of the posterior pole. We compared images of the posterior coats made at 10, 15, and 20 MHz, and 20-MHz ultrasound images of pathologies with 10-MHz ultrasound and optical coherence tomography (OCT). Ability to resolve normal and pathologic structures affecting posterior coats of the eye. Modeling showed that frequencies of 20 to 25 MHz might be used for posterior pole imaging. Twenty-megahertz images allowed differentiation of the retina, choroid, and sclera. In addition, at 20 MHz the retina showed banding patterns suggesting an internal structure comparable in many respects to that seen in OCT and histology. Images of ocular pathology provided much improved detail relative to 10-MHz images and deeper penetration than OCT. Twenty-megahertz ultrasound can be practically employed for imaging of the posterior pole of the eye, providing a 2-fold improvement in resolution relative to conventional 10-MHz instruments. Although not providing the resolution of OCT, ultrasound can be used in the presence of optical opacities and allows evaluation of deeper tissue structures.

Motion Detection in Ultrasound Image-Sequences Using Tensor Voting

NASA Astrophysics Data System (ADS)

Inba, Masafumi; Yanagida, Hirotaka; Tamura, Yasutaka

2008-05-01

Motion detection in ultrasound image sequences using tensor voting is described. We have been developing an ultrasound imaging system adopting a combination of coded excitation and synthetic aperture focusing techniques. In our method, frame rate of the system at distance of 150 mm reaches 5000 frame/s. Sparse array and short duration coded ultrasound signals are used for high-speed data acquisition. However, many artifacts appear in the reconstructed image sequences because of the incompleteness of the transmitted code. To reduce the artifacts, we have examined the application of tensor voting to the imaging method which adopts both coded excitation and synthetic aperture techniques. In this study, the basis of applying tensor voting and the motion detection method to ultrasound images is derived. It was confirmed that velocity detection and feature enhancement are possible using tensor voting in the time and space of simulated ultrasound three-dimensional image sequences.

Techniques to Improve Ultrasound-Switchable Fluorescence Imaging

NASA Astrophysics Data System (ADS)

Kandukuri, Jayanth

Novel approaches to the improvement of ultrasound-switchable fluorescence (USF) imaging--a relatively new imaging modality that combines ultrasound and optical imaging techniques--have been proposed for early cancer detection. In USF, a high-intensity focused ultrasound (HIFU) beam is used to induce temperature rise within its acoustic focal region due to which a thermo-sensitive USF contrast agent undergoes a switch in its state by increasing the output of fluorescence photons. By using an increase in fluorescence, one can isolate and quantify the fluorescence properties within the ultrasonic focal area. Therefore, USF is able to provide fluorescence contrast while maintaining ultrasound resolution in tissue. The major challenge of the conventional USF technique is its low axial resolution and its sensitivity (i.e. its signal-to-noise ratio (SNR)). This work focuses on investigating and developing a novel USF system design that can improve the resolution and SNR of USF imaging for biological applications. This work can be divided into two major parts: characterizing the performance of a high-intensity focused ultrasound transducer; and improving the axial resolution and sensitivity of the USF technique. Preliminary investigation was conducted by using an IR camera setup to detect temperature variation and thereby study the performance of the high-intensity focused ultrasound transducer to quantify different parameters of ultrasound-induced temperature focal size (UTFS). Investigations are conducted for the purpose of high-resolution imaging with an emphasis on HIFU-induced thermal focus size, short duration of HIFU-induced temperature increase (to avoid thermal diffusion or conduction), and control of HIFU-induced temperature increase within a few degrees Celsius. Next, the focus was shifted to improving the sensitivity of the ultrasound-switchable fluorescence-imaging technique. In this study, the USF signal is encoded with the modulation frequency of the

Image segmentation using fuzzy LVQ clustering networks

NASA Technical Reports Server (NTRS)

Tsao, Eric Chen-Kuo; Bezdek, James C.; Pal, Nikhil R.

1992-01-01

In this note we formulate image segmentation as a clustering problem. Feature vectors extracted from a raw image are clustered into subregions, thereby segmenting the image. A fuzzy generalization of a Kohonen learning vector quantization (LVQ) which integrates the Fuzzy c-Means (FCM) model with the learning rate and updating strategies of the LVQ is used for this task. This network, which segments images in an unsupervised manner, is thus related to the FCM optimization problem. Numerical examples on photographic and magnetic resonance images are given to illustrate this approach to image segmentation.

Imaging Performance of a Handheld Ultrasound System With Real-Time Computer-Aided Detection of Lumbar Spine Anatomy: A Feasibility Study.

PubMed

Tiouririne, Mohamed; Dixon, Adam J; Mauldin, F William; Scalzo, David; Krishnaraj, Arun

2017-08-01

The aim of this study was to evaluate the imaging performance of a handheld ultrasound system and the accuracy of an automated lumbar spine computer-aided detection (CAD) algorithm in the spines of human subjects. This study was approved by the institutional review board of the University of Virginia. The authors designed a handheld ultrasound system with enhanced bone image quality and fully automated CAD of lumbar spine anatomy. The imaging performance was evaluated by imaging the lumbar spines of 68 volunteers with body mass index between 18.5 and 48 kg/m. The accuracy, sensitivity, and specificity of the lumbar spine CAD algorithm were assessed by comparing the algorithm's results to ground-truth segmentations of neuraxial anatomy provided by radiologists. The lumbar spine CAD algorithm detected the epidural space with a sensitivity of 94.2% (95% confidence interval [CI], 85.1%-98.1%) and a specificity of 85.5% (95% CI, 81.7%-88.6%) and measured its depth with an error of approximately ±0.5 cm compared with measurements obtained manually from the 2-dimensional ultrasound images. The spine midline was detected with a sensitivity of 93.9% (95% CI, 85.8%-97.7%) and specificity of 91.3% (95% CI, 83.6%-96.9%), and its lateral position within the ultrasound image was measured with an error of approximately ±0.3 cm. The bone enhancement imaging mode produced images with 5.1- to 10-fold enhanced bone contrast when compared with a comparable handheld ultrasound imaging system. The results of this study demonstrate the feasibility of CAD for assisting with real-time interpretation of ultrasound images of the lumbar spine at the bedside.

Segmentation of white rat sperm image

NASA Astrophysics Data System (ADS)

Bai, Weiguo; Liu, Jianguo; Chen, Guoyuan

2011-11-01

The segmentation of sperm image exerts a profound influence in the analysis of sperm morphology, which plays a significant role in the research of animals' infertility and reproduction. To overcome the microscope image's properties of low contrast and highly polluted noise, and to get better segmentation results of sperm image, this paper presents a multi-scale gradient operator combined with a multi-structuring element for the micro-spermatozoa image of white rat, as the multi-scale gradient operator can smooth the noise of an image, while the multi-structuring element can retain more shape details of the sperms. Then, we use the Otsu method to segment the modified gradient image whose gray scale processed is strong in sperms and weak in the background, converting it into a binary sperm image. As the obtained binary image owns impurities that are not similar with sperms in the shape, we choose a form factor to filter those objects whose form factor value is larger than the select critical value, and retain those objects whose not. And then, we can get the final binary image of the segmented sperms. The experiment shows this method's great advantage in the segmentation of the micro-spermatozoa image.

Ultrasound: medical imaging and beyond (an invited review).

PubMed

Azhari, Haim

2012-09-01

Medical applications of ultrasound were first investigated about seventy years ago. It has rapidly evolved since then, becoming an essential tool in medical imaging. Ultrasound ability to provide real time images with frame rates exceeding several hundred frames per second allows one to view rapid anatomical changes as well as to guide minimal invasive procedures. By, combining Doppler techniques with anatomical images ultrasound provides real time quantitative flow information as well. It is portable, versatile, cost effective and considered sufficiently hazardless to monitor pregnancy. Moreover, ultrasound has the unique capacity to offer therapeutic capabilities in addition to its outstanding imaging abilities. It can be used for physiotherapy, lithotripsy, and thermal ablation, and recent studies have demonstrated its usefulness in drug delivery, gene therapy and molecular imaging. The purpose of this article is to provide an introductory review of the field covering briefly topics from basic physics through current imaging methods to therapeutic applications.

Extracting cardiac myofiber orientations from high frequency ultrasound images

NASA Astrophysics Data System (ADS)

Qin, Xulei; Cong, Zhibin; Jiang, Rong; Shen, Ming; Wagner, Mary B.; Kirshbom, Paul; Fei, Baowei

2013-03-01

Cardiac myofiber plays an important role in stress mechanism during heart beating periods. The orientation of myofibers decides the effects of the stress distribution and the whole heart deformation. It is important to image and quantitatively extract these orientations for understanding the cardiac physiological and pathological mechanism and for diagnosis of chronic diseases. Ultrasound has been wildly used in cardiac diagnosis because of its ability of performing dynamic and noninvasive imaging and because of its low cost. An extraction method is proposed to automatically detect the cardiac myofiber orientations from high frequency ultrasound images. First, heart walls containing myofibers are imaged by B-mode high frequency (<20 MHz) ultrasound imaging. Second, myofiber orientations are extracted from ultrasound images using the proposed method that combines a nonlinear anisotropic diffusion filter, Canny edge detector, Hough transform, and K-means clustering. This method is validated by the results of ultrasound data from phantoms and pig hearts.

40 MHz high-frequency ultrafast ultrasound imaging.

PubMed

Huang, Chih-Chung; Chen, Pei-Yu; Peng, Po-Hsun; Lee, Po-Yang

2017-06-01

Ultrafast high-frame-rate ultrasound imaging based on coherent-plane-wave compounding has been developed for many biomedical applications. Most coherent-plane-wave compounding systems typically operate at 3-15 MHz, and the image resolution for this frequency range is not sufficient for visualizing microstructure tissues. Therefore, the purpose of this study was to implement a high-frequency ultrafast ultrasound imaging operating at 40 MHz. The plane-wave compounding imaging and conventional multifocus B-mode imaging were performed using the Field II toolbox of MATLAB in simulation study. In experiments, plane-wave compounding images were obtained from a 256 channel ultrasound research platform with a 40 MHz array transducer. All images were produced by point-spread functions and cyst phantoms. The in vivo experiment was performed from zebrafish. Since high-frequency ultrasound exhibits a lower penetration, chirp excitation was applied to increase the imaging depth in simulation. The simulation results showed that a lateral resolution of up to 66.93 μm and a contrast of up to 56.41 dB were achieved when using 75-angles plane waves in compounding imaging. The experimental results showed that a lateral resolution of up to 74.83 μm and a contrast of up to 44.62 dB were achieved when using 75-angles plane waves in compounding imaging. The dead zone and compounding noise are about 1.2 mm and 2.0 mm in depth for experimental compounding imaging, respectively. The structure of zebrafish heart was observed clearly using plane-wave compounding imaging. The use of fewer than 23 angles for compounding allowed a frame rate higher than 1000 frames per second. However, the compounding imaging exhibits a similar lateral resolution of about 72 μm as the angle of plane wave is higher than 10 angles. This study shows the highest operational frequency for ultrafast high-frame-rate ultrasound imaging. © 2017 American Association of Physicists in Medicine.

Medical Imaging with Ultrasound: Some Basic Physics.

ERIC Educational Resources Information Center

Gosling, R.

1989-01-01

Discussed are medical applications of ultrasound. The physics of the wave nature of ultrasound including its propagation and production, return by the body, spatial and contrast resolution, attenuation, image formation using pulsed echo ultrasound techniques, measurement of velocity and duplex scanning are described. (YP)

Determination of optimal ultrasound planes for the initialisation of image registration during endoscopic ultrasound-guided procedures.

PubMed

Bonmati, Ester; Hu, Yipeng; Gibson, Eli; Uribarri, Laura; Keane, Geri; Gurusami, Kurinchi; Davidson, Brian; Pereira, Stephen P; Clarkson, Matthew J; Barratt, Dean C

2018-06-01

Navigation of endoscopic ultrasound (EUS)-guided procedures of the upper gastrointestinal (GI) system can be technically challenging due to the small fields-of-view of ultrasound and optical devices, as well as the anatomical variability and limited number of orienting landmarks during navigation. Co-registration of an EUS device and a pre-procedure 3D image can enhance the ability to navigate. However, the fidelity of this contextual information depends on the accuracy of registration. The purpose of this study was to develop and test the feasibility of a simulation-based planning method for pre-selecting patient-specific EUS-visible anatomical landmark locations to maximise the accuracy and robustness of a feature-based multimodality registration method. A registration approach was adopted in which landmarks are registered to anatomical structures segmented from the pre-procedure volume. The predicted target registration errors (TREs) of EUS-CT registration were estimated using simulated visible anatomical landmarks and a Monte Carlo simulation of landmark localisation error. The optimal planes were selected based on the 90th percentile of TREs, which provide a robust and more accurate EUS-CT registration initialisation. The method was evaluated by comparing the accuracy and robustness of registrations initialised using optimised planes versus non-optimised planes using manually segmented CT images and simulated ([Formula: see text]) or retrospective clinical ([Formula: see text]) EUS landmarks. The results show a lower 90th percentile TRE when registration is initialised using the optimised planes compared with a non-optimised initialisation approach (p value [Formula: see text]). The proposed simulation-based method to find optimised EUS planes and landmarks for EUS-guided procedures may have the potential to improve registration accuracy. Further work will investigate applying the technique in a clinical setting.

Vascular applications of contrast-enhanced ultrasound imaging.

PubMed

Mehta, Kunal S; Lee, Jake J; Taha, Ashraf G; Avgerinos, Efthymios; Chaer, Rabih A

2017-07-01

Contrast-enhanced ultrasound (CEUS) imaging is a powerful noninvasive modality offering numerous potential diagnostic and therapeutic applications in vascular medicine. CEUS imaging uses microbubble contrast agents composed of an encapsulating shell surrounding a gaseous core. These microbubbles act as nearly perfect intravascular reflectors of ultrasound energy and may be used to enhance the overall contrast and quality of ultrasound images. The purpose of this narrative review is to survey the current literature regarding CEUS imaging and discuss its diagnostic and therapeutic roles in current vascular and selected nonvascular applications. The PubMed, MEDLINE, and Embase databases were searched until July 2016 using the PubMed and Ovid Web-based search engines. The search terms used included contrast-enhanced, microbubble, ultrasound, carotid, aneurysm, and arterial. The diagnostic and therapeutic utility of CEUS imaging has grown exponentially, particularly in the realms of extracranial carotid arterial disease, aortic disease, and peripheral arterial disease. Studies have demonstrated that CEUS imaging is diagnostically superior to conventional ultrasound imaging in identifying vessel irregularities and measuring neovascularization to assess plaque vulnerability and end-muscle perfusion. Groups have begun to use microbubbles as agents in therapeutic applications for targeted drug and gene therapy delivery as well as for the enhancement of sonothrombolysis. The emerging technology of microbubbles and CEUS imaging holds considerable promise for cardiovascular medicine and cancer therapy given its diagnostic and therapeutic utility. Overall, with proper training and credentialing of technicians, the clinical implications are innumerable as microbubble technology is rapidly bursting onto the scene of cardiovascular medicine. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

An image registration based ultrasound probe calibration

NASA Astrophysics Data System (ADS)

Li, Xin; Kumar, Dinesh; Sarkar, Saradwata; Narayanan, Ram

2012-02-01

Reconstructed 3D ultrasound of prostate gland finds application in several medical areas such as image guided biopsy, therapy planning and dose delivery. In our application, we use an end-fire probe rotated about its axis to acquire a sequence of rotational slices to reconstruct 3D TRUS (Transrectal Ultrasound) image. The image acquisition system consists of an ultrasound transducer situated on a cradle directly attached to a rotational sensor. However, due to system tolerances, axis of probe does not align exactly with the designed axis of rotation resulting in artifacts in the 3D reconstructed ultrasound volume. We present a rigid registration based automatic probe calibration approach. The method uses a sequence of phantom images, each pair acquired at angular separation of 180 degrees and registers corresponding image pairs to compute the deviation from designed axis. A modified shadow removal algorithm is applied for preprocessing. An attribute vector is constructed from image intensity and a speckle-insensitive information-theoretic feature. We compare registration between the presented method and expert-corrected images in 16 prostate phantom scans. Images were acquired at multiple resolutions, and different misalignment settings from two ultrasound machines. Screenshots from 3D reconstruction are shown before and after misalignment correction. Registration parameters from automatic and manual correction were found to be in good agreement. Average absolute differences of translation and rotation between automatic and manual methods were 0.27 mm and 0.65 degree, respectively. The registration parameters also showed lower variability for automatic registration (pooled standard deviation σtranslation = 0.50 mm, σrotation = 0.52 degree) compared to the manual approach (pooled standard deviation σtranslation = 0.62 mm, σrotation = 0.78 degree).

Medical image segmentation using genetic algorithms.

PubMed

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

Non-Contact Optical Ultrasound Concept for Biomedical Imaging

DTIC Science & Technology

2016-11-03

Non -Contact Optical Ultrasound Concept for Biomedical Imaging Robert Haupt1, Charles Wynn1, Jonathan Fincke2, Shawn Zhang2, Brian Anthony2...results. Lastly, we present imaging capabilities using a non -contact laser ultrasound proof-of-concept system. Two and three dimensional time... non -contact, standoff optical ultrasound has the potential to provide a fixed reference measurement capability that minimizes operator variability as

Imaging By Ultrasound

PubMed Central

Kidney, Maria R.

1986-01-01

Imaging by ultrasound has dramatically changed the investigation and management of many clinical problems. It is useful in many different parts of the body. In this brief discussion, the following topics are considered: hepatic lesions, bleeding in early pregnancy, gynecological pathology (adnexal lesions), aortic aneurysms, thyroid nodules and scrotal masses. The usefulness of duplex carotid sonography, which combines ultrasonic imaging and Doppler studies, is also discussed. Other topics (gallstones, biliary obstruction, renal calculi, hydronephrosis) are discussed in the appropriate sections. ImagesFigure 1Figure 2Figure 3Figure 4 PMID:21267202

3D ultrafast ultrasound imaging in vivo.

PubMed

Provost, Jean; Papadacci, Clement; Arango, Juan Esteban; Imbault, Marion; Fink, Mathias; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

2014-10-07

Very high frame rate ultrasound imaging has recently allowed for the extension of the applications of echography to new fields of study such as the functional imaging of the brain, cardiac electrophysiology, and the quantitative imaging of the intrinsic mechanical properties of tumors, to name a few, non-invasively and in real time. In this study, we present the first implementation of Ultrafast Ultrasound Imaging in 3D based on the use of either diverging or plane waves emanating from a sparse virtual array located behind the probe. It achieves high contrast and resolution while maintaining imaging rates of thousands of volumes per second. A customized portable ultrasound system was developed to sample 1024 independent channels and to drive a 32  ×  32 matrix-array probe. Its ability to track in 3D transient phenomena occurring in the millisecond range within a single ultrafast acquisition was demonstrated for 3D Shear-Wave Imaging, 3D Ultrafast Doppler Imaging, and, finally, 3D Ultrafast combined Tissue and Flow Doppler Imaging. The propagation of shear waves was tracked in a phantom and used to characterize its stiffness. 3D Ultrafast Doppler was used to obtain 3D maps of Pulsed Doppler, Color Doppler, and Power Doppler quantities in a single acquisition and revealed, at thousands of volumes per second, the complex 3D flow patterns occurring in the ventricles of the human heart during an entire cardiac cycle, as well as the 3D in vivo interaction of blood flow and wall motion during the pulse wave in the carotid at the bifurcation. This study demonstrates the potential of 3D Ultrafast Ultrasound Imaging for the 3D mapping of stiffness, tissue motion, and flow in humans in vivo and promises new clinical applications of ultrasound with reduced intra--and inter-observer variability.

Ultrasound Imaging Initiative

DTIC Science & Technology

2003-01-01

texture mapping hardware," IEEE Tranactions on Information Technology in Biomedicine, Submitted. [14] C.R. Castro Pareja , J.M. Jagadeesh and R. Shekhar...modulation in real-time three-dimensional sparse synthetic aperture ultrasound imaging systems "* Carlos R. Castro Pareja , Masters of Science, The Ohio...C.R. Castro Pareja , "An architecture for real-time image registration," M.S. Thesis, The Ohio State University, March 2002. 14. C.R. Castro Pareja , R

Remote sensing image segmentation based on Hadoop cloud platform

NASA Astrophysics Data System (ADS)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning.

PubMed

Looney, Pádraig; Stevenson, Gordon N; Nicolaides, Kypros H; Plasencia, Walter; Molloholli, Malid; Natsis, Stavros; Collins, Sally L

2018-06-07

We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator dependant. Fully automating the segmentation process would potentially allow the use of placental volume to screen for increased risk of pregnancy complications. The placenta was segmented from 2,393 first trimester 3D-US volumes using a semiautomated technique. This was quality controlled by three operators to produce the "ground-truth" data set. A fully convolutional neural network (OxNNet) was trained using this ground-truth data set to automatically segment the placenta. OxNNet delivered state-of-the-art automatic segmentation. The effect of training set size on the performance of OxNNet demonstrated the need for large data sets. The clinical utility of placental volume was tested by looking at predictions of small-for-gestational-age babies at term. The receiver-operating characteristics curves demonstrated almost identical results between OxNNet and the ground-truth). Our results demonstrated good similarity to the ground-truth and almost identical clinical results for the prediction of SGA.

Multimedia systems in ultrasound image boundary detection and measurements

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Chalana, Vikram; Kim, Yongmin

1997-05-01

Ultrasound as a medical imaging modality offers the clinician a real-time of the anatomy of the internal organs/tissues, their movement, and flow noninvasively. One of the applications of ultrasound is to monitor fetal growth by measuring biparietal diameter (BPD) and head circumference (HC). We have been working on automatic detection of fetal head boundaries in ultrasound images. These detected boundaries are used to measure BPD and HC. The boundary detection algorithm is based on active contour models and takes 32 seconds on an external high-end workstation, SUN SparcStation 20/71. Our goal has been to make this tool available within an ultrasound machine and at the same time significantly improve its performance utilizing multimedia technology. With the advent of high- performance programmable digital signal processors (DSP), the software solution within an ultrasound machine instead of the traditional hardwired approach or requiring an external computer is now possible. We have integrated our boundary detection algorithm into a programmable ultrasound image processor (PUIP) that fits into a commercial ultrasound machine. The PUIP provides both the high computing power and flexibility needed to support computationally-intensive image processing algorithms within an ultrasound machine. According to our data analysis, BPD/HC measurements made on PUIP lie within the interobserver variability. Hence, the errors in the automated BPD/HC measurements using the algorithm are on the same order as the average interobserver differences. On PUIP, it takes 360 ms to measure the values of BPD/HC on one head image. When processing multiple head images in sequence, it takes 185 ms per image, thus enabling 5.4 BPD/HC measurements per second. Reduction in the overall execution time from 32 seconds to a fraction of a second and making this multimedia system available within an ultrasound machine will help this image processing algorithm and other computer-intensive imaging

A Targeting Microbubble for Ultrasound Molecular Imaging

PubMed Central

Yeh, James Shue-Min; Sennoga, Charles A.; McConnell, Ellen; Eckersley, Robert; Tang, Meng-Xing; Nourshargh, Sussan; Seddon, John M.; Haskard, Dorian O.; Nihoyannopoulos, Petros

2015-01-01

Rationale Microbubbles conjugated with targeting ligands are used as contrast agents for ultrasound molecular imaging. However, they often contain immunogenic (strept)avidin, which impedes application in humans. Although targeting bubbles not employing the biotin-(strept)avidin conjugation chemistry have been explored, only a few reached the stage of ultrasound imaging in vivo, none were reported/evaluated to show all three of the following properties desired for clinical applications: (i) low degree of non-specific bubble retention in more than one non-reticuloendothelial tissue; (ii) effective for real-time imaging; and (iii) effective for acoustic quantification of molecular targets to a high degree of quantification. Furthermore, disclosures of the compositions and methodologies enabling reproduction of the bubbles are often withheld. Objective To develop and evaluate a targeting microbubble based on maleimide-thiol conjugation chemistry for ultrasound molecular imaging. Methods and Results Microbubbles with a previously unreported generic (non-targeting components) composition were grafted with anti-E-selectin F(ab’)2 using maleimide-thiol conjugation, to produce E-selectin targeting microbubbles. The resulting targeting bubbles showed high specificity to E-selectin in vitro and in vivo. Non-specific bubble retention was minimal in at least three non-reticuloendothelial tissues with inflammation (mouse heart, kidneys, cremaster). The bubbles were effective for real-time ultrasound imaging of E-selectin expression in the inflamed mouse heart and kidneys, using a clinical ultrasound scanner. The acoustic signal intensity of the targeted bubbles retained in the heart correlated strongly with the level of E-selectin expression (|r|≥0.8), demonstrating a high degree of non-invasive molecular quantification. Conclusions Targeting microbubbles for ultrasound molecular imaging, based on maleimide-thiol conjugation chemistry and the generic composition described

MLESAC Based Localization of Needle Insertion Using 2D Ultrasound Images

NASA Astrophysics Data System (ADS)

Xu, Fei; Gao, Dedong; Wang, Shan; Zhanwen, A.

2018-04-01

In the 2D ultrasound image of ultrasound-guided percutaneous needle insertions, it is difficult to determine the positions of needle axis and tip because of the existence of artifacts and other noises. In this work the speckle is regarded as the noise of an ultrasound image, and a novel algorithm is presented to detect the needle in a 2D ultrasound image. Firstly, the wavelet soft thresholding technique based on BayesShrink rule is used to denoise the speckle of ultrasound image. Secondly, we add Otsu’s thresholding method and morphologic operations to pre-process the ultrasound image. Finally, the localization of the needle is identified and positioned in the 2D ultrasound image based on the maximum likelihood estimation sample consensus (MLESAC) algorithm. The experimental results show that it is valid for estimating the position of needle axis and tip in the ultrasound images with the proposed algorithm. The research work is hopeful to be used in the path planning and robot-assisted needle insertion procedures.

SVM Pixel Classification on Colour Image Segmentation

NASA Astrophysics Data System (ADS)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Development of a control algorithm for the ultrasound scanning robot (NCCUSR) using ultrasound image and force feedback.

PubMed

Kim, Yeoun Jae; Seo, Jong Hyun; Kim, Hong Rae; Kim, Kwang Gi

2017-06-01

Clinicians who frequently perform ultrasound scanning procedures often suffer from musculoskeletal disorders, arthritis, and myalgias. To minimize their occurrence and to assist clinicians, ultrasound scanning robots have been developed worldwide. Although, to date, there is still no commercially available ultrasound scanning robot, many control methods have been suggested and researched. These control algorithms are either image based or force based. If the ultrasound scanning robot control algorithm was a combination of the two algorithms, it could benefit from the advantage of each one. However, there are no existing control methods for ultrasound scanning robots that combine force control and image analysis. Therefore, in this work, a control algorithm is developed for an ultrasound scanning robot using force feedback and ultrasound image analysis. A manipulator-type ultrasound scanning robot named 'NCCUSR' is developed and a control algorithm for this robot is suggested and verified. First, conventional hybrid position-force control is implemented for the robot and the hybrid position-force control algorithm is combined with ultrasound image analysis to fully control the robot. The control method is verified using a thyroid phantom. It was found that the proposed algorithm can be applied to control the ultrasound scanning robot and experimental outcomes suggest that the images acquired using the proposed control method can yield a rating score that is equivalent to images acquired directly by the clinicians. The proposed control method can be applied to control the ultrasound scanning robot. However, more work must be completed to verify the proposed control method in order to become clinically feasible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Transfer learning improves supervised image segmentation across imaging protocols.

PubMed

van Opbroek, Annegreet; Ikram, M Arfan; Vernooij, Meike W; de Bruijne, Marleen

2015-05-01

The variation between images obtained with different scanners or different imaging protocols presents a major challenge in automatic segmentation of biomedical images. This variation especially hampers the application of otherwise successful supervised-learning techniques which, in order to perform well, often require a large amount of labeled training data that is exactly representative of the target data. We therefore propose to use transfer learning for image segmentation. Transfer-learning techniques can cope with differences in distributions between training and target data, and therefore may improve performance over supervised learning for segmentation across scanners and scan protocols. We present four transfer classifiers that can train a classification scheme with only a small amount of representative training data, in addition to a larger amount of other training data with slightly different characteristics. The performance of the four transfer classifiers was compared to that of standard supervised classification on two magnetic resonance imaging brain-segmentation tasks with multi-site data: white matter, gray matter, and cerebrospinal fluid segmentation; and white-matter-/MS-lesion segmentation. The experiments showed that when there is only a small amount of representative training data available, transfer learning can greatly outperform common supervised-learning approaches, minimizing classification errors by up to 60%.

Pulsed Magneto-motive Ultrasound Imaging Using Ultrasmall Magnetic Nanoprobes

PubMed Central

Mehrmohammadi, Mohammad; Oh, Junghwan; Mallidi, Srivalleesha; Emelianov, Stanislav Y.

2011-01-01

Nano-sized particles are widely regarded as a tool to study biologic events at the cellular and molecular levels. However, only some imaging modalities can visualize interaction between nanoparticles and living cells. We present a new technique, pulsed magneto-motive ultrasound imaging, which is capable of in vivo imaging of magnetic nanoparticles in real time and at sufficient depth. In pulsed magneto-motive ultrasound imaging, an external high-strength pulsed magnetic field is applied to induce the motion within the magnetically labeled tissue and ultrasound is used to detect the induced internal tissue motion. Our experiments demonstrated a sufficient contrast between normal and iron-laden cells labeled with ultrasmall magnetic nanoparticles. Therefore, pulsed magneto-motive ultrasound imaging could become an imaging tool capable of detecting magnetic nanoparticles and characterizing the cellular and molecular composition of deep-lying structures. PMID:21439255

Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image

NASA Astrophysics Data System (ADS)

He, Xingwu; You, Junchen

2018-03-01

Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.

Spatial Angular Compounding Technique for H-Scan Ultrasound Imaging.

PubMed

Khairalseed, Mawia; Xiong, Fangyuan; Kim, Jung-Whan; Mattrey, Robert F; Parker, Kevin J; Hoyt, Kenneth

2018-01-01

H-Scan is a new ultrasound imaging technique that relies on matching a model of pulse-echo formation to the mathematics of a class of Gaussian-weighted Hermite polynomials. This technique may be beneficial in the measurement of relative scatterer sizes and in cancer therapy, particularly for early response to drug treatment. Because current H-scan techniques use focused ultrasound data acquisitions, spatial resolution degrades away from the focal region and inherently affects relative scatterer size estimation. Although the resolution of ultrasound plane wave imaging can be inferior to that of traditional focused ultrasound approaches, the former exhibits a homogeneous spatial resolution throughout the image plane. The purpose of this study was to implement H-scan using plane wave imaging and investigate the impact of spatial angular compounding on H-scan image quality. Parallel convolution filters using two different Gaussian-weighted Hermite polynomials that describe ultrasound scattering events are applied to the radiofrequency data. The H-scan processing is done on each radiofrequency image plane before averaging to get the angular compounded image. The relative strength from each convolution is color-coded to represent relative scatterer size. Given results from a series of phantom materials, H-scan imaging with spatial angular compounding more accurately reflects the true scatterer size caused by reductions in the system point spread function and improved signal-to-noise ratio. Preliminary in vivo H-scan imaging of tumor-bearing animals suggests this modality may be useful for monitoring early response to chemotherapeutic treatment. Overall, H-scan imaging using ultrasound plane waves and spatial angular compounding is a promising approach for visualizing the relative size and distribution of acoustic scattering sources. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Handheld probe integrating laser diode and ultrasound transducer array for ultrasound/photoacoustic dual modality imaging.

PubMed

Daoudi, K; van den Berg, P J; Rabot, O; Kohl, A; Tisserand, S; Brands, P; Steenbergen, W

2014-10-20

Ultrasound and photoacoustics can be utilized as complementary imaging techniques to improve clinical diagnoses. Photoacoustics provides optical contrast and functional information while ultrasound provides structural and anatomical information. As of yet, photoacoustic imaging uses large and expensive systems, which limits their clinical application and makes the combination costly and impracticable. In this work we present and evaluate a compact and ergonomically designed handheld probe, connected to a portable ultrasound system for inexpensive, real-time dual-modality ultrasound/photoacoustic imaging. The probe integrates an ultrasound transducer array and a highly efficient diode stack laser emitting 130 ns pulses at 805 nm wavelength and a pulse energy of 0.56 mJ, with a high pulse repetition frequency of up to 10 kHz. The diodes are driven by a customized laser driver, which can be triggered externally with a high temporal stability necessary to synchronize the ultrasound detection and laser pulsing. The emitted beam is collimated with cylindrical micro-lenses and shaped using a diffractive optical element, delivering a homogenized rectangular light intensity distribution. The system performance was tested in vitro and in vivo by imaging a human finger joint.

Ultrasound imaging of the anal sphincter complex: a review

PubMed Central

Abdool, Z; Sultan, A H; Thakar, R

2012-01-01

Endoanal ultrasound is now regarded as the gold standard for evaluating anal sphincter pathology in the investigation of anal incontinence. The advent of three-dimensional ultrasound has further improved our understanding of the two-dimensional technique. Endoanal ultrasound requires specialised equipment and its relative invasiveness has prompted clinicians to explore alternative imaging techniques. Transvaginal and transperineal ultrasound have been recently evaluated as alternative imaging modalities. However, the need for technique standardisation, validation and reporting is of paramount importance. We conducted a MEDLINE search (1950 to February 2010) and critically reviewed studies using the three imaging techniques in evaluating anal sphincter integrity. PMID:22374273

Prostate segmentation: an efficient convex optimization approach with axial symmetry using 3-D TRUS and MR images.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2014-04-01

We propose a novel global optimization-based approach to segmentation of 3-D prostate transrectal ultrasound (TRUS) and T2 weighted magnetic resonance (MR) images, enforcing inherent axial symmetry of prostate shapes to simultaneously adjust a series of 2-D slice-wise segmentations in a "global" 3-D sense. We show that the introduced challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. In this regard, we propose a novel coherent continuous max-flow model (CCMFM), which derives a new and efficient duality-based algorithm, leading to a GPU-based implementation to achieve high computational speeds. Experiments with 25 3-D TRUS images and 30 3-D T2w MR images from our dataset, and 50 3-D T2w MR images from a public dataset, demonstrate that the proposed approach can segment a 3-D prostate TRUS/MR image within 5-6 s including 4-5 s for initialization, yielding a mean Dice similarity coefficient of 93.2%±2.0% for 3-D TRUS images and 88.5%±3.5% for 3-D MR images. The proposed method also yields relatively low intra- and inter-observer variability introduced by user manual initialization, suggesting a high reproducibility, independent of observers.

Ultrasound image filtering using the mutiplicative model

NASA Astrophysics Data System (ADS)

Navarrete, Hugo; Frery, Alejandro C.; Sanchez, Fermin; Anto, Joan

2002-04-01

Ultrasound images, as a special case of coherent images, are normally corrupted with multiplicative noise i.e. speckle noise. Speckle noise reduction is a difficult task due to its multiplicative nature, but good statistical models of speckle formation are useful to design adaptive speckle reduction filters. In this article a new statistical model, emerging from the Multiplicative Model framework, is presented and compared to previous models (Rayleigh, Rice and K laws). It is shown that the proposed model gives the best performance when modeling the statistics of ultrasound images. Finally, the parameters of the model can be used to quantify the extent of speckle formation; this quantification is applied to adaptive speckle reduction filter design. The effectiveness of the filter is demonstrated on typical in-vivo log-compressed B-scan images obtained by a clinical ultrasound system.

Ultrasound strain imaging using Barker code

NASA Astrophysics Data System (ADS)

Peng, Hui; Tie, Juhong; Guo, Dequan

2017-01-01

Ultrasound strain imaging is showing promise as a new way of imaging soft tissue elasticity in order to help clinicians detect lesions or cancers in tissues. In this paper, Barker code is applied to strain imaging to improve its quality. Barker code as a coded excitation signal can be used to improve the echo signal-to-noise ratio (eSNR) in ultrasound imaging system. For the Baker code of length 13, the sidelobe level of the matched filter output is -22dB, which is unacceptable for ultrasound strain imaging, because high sidelobe level will cause high decorrelation noise. Instead of using the conventional matched filter, we use the Wiener filter to decode the Barker-coded echo signal to suppress the range sidelobes. We also compare the performance of Barker code and the conventional short pulse in simulation method. The simulation results demonstrate that the performance of the Wiener filter is much better than the matched filter, and Baker code achieves higher elastographic signal-to-noise ratio (SNRe) than the short pulse in low eSNR or great depth conditions due to the increased eSNR with it.

Pocket-sized versus standard ultrasound machines in abdominal imaging.

PubMed

Tse, K H; Luk, W H; Lam, M C

2014-06-01

The pocket-sized ultrasound machine has emerged as an invaluable tool for quick assessment in emergency and general practice settings. It is suitable for instant and quick assessment in cardiac imaging. However, its applicability in the imaging of other body parts has yet to be established. In this pictorial review, we compared the performance of the pocketsized ultrasound machine against the standard ultrasound machine for its image quality in common abdominal pathology.

Colour image segmentation using unsupervised clustering technique for acute leukemia images

NASA Astrophysics Data System (ADS)

Halim, N. H. Abd; Mashor, M. Y.; Nasir, A. S. Abdul; Mustafa, N.; Hassan, R.

2015-05-01

Colour image segmentation has becoming more popular for computer vision due to its important process in most medical analysis tasks. This paper proposes comparison between different colour components of RGB(red, green, blue) and HSI (hue, saturation, intensity) colour models that will be used in order to segment the acute leukemia images. First, partial contrast stretching is applied on leukemia images to increase the visual aspect of the blast cells. Then, an unsupervised moving k-means clustering algorithm is applied on the various colour components of RGB and HSI colour models for the purpose of segmentation of blast cells from the red blood cells and background regions in leukemia image. Different colour components of RGB and HSI colour models have been analyzed in order to identify the colour component that can give the good segmentation performance. The segmented images are then processed using median filter and region growing technique to reduce noise and smooth the images. The results show that segmentation using saturation component of HSI colour model has proven to be the best in segmenting nucleus of the blast cells in acute leukemia image as compared to the other colour components of RGB and HSI colour models.

Multifunctional microbubbles and nanobubbles for photoacoustic and ultrasound imaging

PubMed Central

Kim, Chulhong; Qin, Ruogu; Xu, Jeff S.; Wang, Lihong V.; Xu, Ronald

2010-01-01

We develop a novel dual-modal contrast agent—encapsulated-ink poly(lactic-co-glycolic acid) (PLGA) microbubbles and nanobubbles—for photoacoustic and ultrasound imaging. Soft gelatin phantoms with embedded tumor simulators of encapsulated-ink PLGA microbubbles and nanobubbles in various concentrations are clearly shown in both photoacoustic and ultrasound images. In addition, using photoacoustic imaging, we successfully image the samples positioned below 1.8-cm-thick chicken breast tissues. Potentially, simultaneous photoacoustic and ultrasound imaging enhanced by encapsulated-dye PLGA microbubbles or nanobubbles can be a valuable tool for intraoperative assessment of tumor boundaries and therapeutic margins. PMID:20210423

A summary of image segmentation techniques

NASA Technical Reports Server (NTRS)

Spirkovska, Lilly

1993-01-01

Machine vision systems are often considered to be composed of two subsystems: low-level vision and high-level vision. Low level vision consists primarily of image processing operations performed on the input image to produce another image with more favorable characteristics. These operations may yield images with reduced noise or cause certain features of the image to be emphasized (such as edges). High-level vision includes object recognition and, at the highest level, scene interpretation. The bridge between these two subsystems is the segmentation system. Through segmentation, the enhanced input image is mapped into a description involving regions with common features which can be used by the higher level vision tasks. There is no theory on image segmentation. Instead, image segmentation techniques are basically ad hoc and differ mostly in the way they emphasize one or more of the desired properties of an ideal segmenter and in the way they balance and compromise one desired property against another. These techniques can be categorized in a number of different groups including local vs. global, parallel vs. sequential, contextual vs. noncontextual, interactive vs. automatic. In this paper, we categorize the schemes into three main groups: pixel-based, edge-based, and region-based. Pixel-based segmentation schemes classify pixels based solely on their gray levels. Edge-based schemes first detect local discontinuities (edges) and then use that information to separate the image into regions. Finally, region-based schemes start with a seed pixel (or group of pixels) and then grow or split the seed until the original image is composed of only homogeneous regions. Because there are a number of survey papers available, we will not discuss all segmentation schemes. Rather than a survey, we take the approach of a detailed overview. We focus only on the more common approaches in order to give the reader a flavor for the variety of techniques available yet present enough

Evaluation of multimodality imaging using image fusion with ultrasound tissue elasticity imaging in an experimental animal model.

PubMed

Paprottka, P M; Zengel, P; Cyran, C C; Ingrisch, M; Nikolaou, K; Reiser, M F; Clevert, D A

2014-01-01

To evaluate the ultrasound tissue elasticity imaging by comparison to multimodality imaging using image fusion with Magnetic Resonance Imaging (MRI) and conventional grey scale imaging with additional elasticity-ultrasound in an experimental small-animal-squamous-cell carcinoma-model for the assessment of tissue morphology. Human hypopharynx carcinoma cells were subcutaneously injected into the left flank of 12 female athymic nude rats. After 10 days (SD ± 2) of subcutaneous tumor growth, sonographic grey scale including elasticity imaging and MRI measurements were performed using a high-end ultrasound system and a 3T MR. For image fusion the contrast-enhanced MRI DICOM data set was uploaded in the ultrasonic device which has a magnetic field generator, a linear array transducer (6-15 MHz) and a dedicated software package (GE Logic E9), that can detect transducers by means of a positioning system. Conventional grey scale and elasticity imaging were integrated in the image fusion examination. After successful registration and image fusion the registered MR-images were simultaneously shown with the respective ultrasound sectional plane. Data evaluation was performed using the digitally stored video sequence data sets by two experienced radiologist using a modified Tsukuba Elasticity score. The colors "red and green" are assigned for an area of soft tissue, "blue" indicates hard tissue. In all cases a successful image fusion and plan registration with MRI and ultrasound imaging including grey scale and elasticity imaging was possible. The mean tumor volume based on caliper measurements in 3 dimensions was ~323 mm3. 4/12 rats were evaluated with Score I, 5/12 rates were evaluated with Score II, 3/12 rates were evaluated with Score III. There was a close correlation in the fused MRI with existing small necrosis in the tumor. None of the scored II or III lesions was visible by conventional grey scale. The comparison of ultrasound tissue elasticity imaging enables a

Ultrasound Activated Contrast Imaging for Prostate Cancer Detection

DTIC Science & Technology

2007-03-01

SUBTITLE 5a. CONTRACT NUMBER Ultrasound Activated Contrast Imaging for Prostate Cancer Detection 5b. GRANT NUMBER DAMD17-03-1-0119 5c. PROGRAM...ABSTRACT: The current project proposes todevelop a novel ultrasound contrast imaging technique (called EEI) for better visualization of the

Image segmentation evaluation for very-large datasets

NASA Astrophysics Data System (ADS)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Compound image segmentation of published biomedical figures.

PubMed

Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

2018-04-01

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

Robot-assisted ultrasound imaging: overview and development of a parallel telerobotic system.

PubMed

Monfaredi, Reza; Wilson, Emmanuel; Azizi Koutenaei, Bamshad; Labrecque, Brendan; Leroy, Kristen; Goldie, James; Louis, Eric; Swerdlow, Daniel; Cleary, Kevin

2015-02-01

Ultrasound imaging is frequently used in medicine. The quality of ultrasound images is often dependent on the skill of the sonographer. Several researchers have proposed robotic systems to aid in ultrasound image acquisition. In this paper we first provide a short overview of robot-assisted ultrasound imaging (US). We categorize robot-assisted US imaging systems into three approaches: autonomous US imaging, teleoperated US imaging, and human-robot cooperation. For each approach several systems are introduced and briefly discussed. We then describe a compact six degree of freedom parallel mechanism telerobotic system for ultrasound imaging developed by our research team. The long-term goal of this work is to enable remote ultrasound scanning through teleoperation. This parallel mechanism allows for both translation and rotation of an ultrasound probe mounted on the top plate along with force control. Our experimental results confirmed good mechanical system performance with a positioning error of < 1 mm. Phantom experiments by a radiologist showed promising results with good image quality.

Brain MR image segmentation using NAMS in pseudo-color.

PubMed

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Aptamer-conjugated nanobubbles for targeted ultrasound molecular imaging.

PubMed

Wang, Chung-Hsin; Huang, Yu-Fen; Yeh, Chih-Kuang

2011-06-07

Targeted ultrasound contrast agents can be prepared by some specific bioconjugation techniques. The biotin-avidin complex is an extremely useful noncovalent binding system, but the system might induce immunogenic side effects in human bodies. Previous proposed covalently conjugated systems suffered from low conjugation efficiency and complex procedures. In this study, we propose a covalently conjugated nanobubble coupling with nucleic acid ligands, aptamers, for providing a higher specific affinity for ultrasound targeting studies. The sgc8c aptamer was linked with nanobubbles through thiol-maleimide coupling chemistry for specific targeting to CCRF-CEM cells. Further improvements to reduce the required time and avoid the degradation of nanobubbles during conjugation procedures were also made. Several investigations were used to discuss the performance and consistency of the prepared nanobubbles, such as size distribution, conjugation efficiency analysis, and flow cytometry assay. Further, we applied our conjugated nanobubbles to ex vivo ultrasound targeted imaging and compared the resulting images with optical images. The results indicated the availability of aptamer-conjugated nanobubbles in targeted ultrasound imaging and the practicability of using a highly sensitive ultrasound system in noninvasive biological research.

Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey

PubMed Central

Zhang, Fan; Li, Xuelong

2018-01-01

The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system. PMID:29687000

Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.

PubMed

Huang, Qinghua; Zhang, Fan; Li, Xuelong

2018-01-01

The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system.

Ultrafast Ultrasound Imaging With Cascaded Dual-Polarity Waves.

PubMed

Zhang, Yang; Guo, Yuexin; Lee, Wei-Ning

2018-04-01

Ultrafast ultrasound imaging using plane or diverging waves, instead of focused beams, has advanced greatly the development of novel ultrasound imaging methods for evaluating tissue functions beyond anatomical information. However, the sonographic signal-to-noise ratio (SNR) of ultrafast imaging remains limited due to the lack of transmission focusing, and thus insufficient acoustic energy delivery. We hereby propose a new ultrafast ultrasound imaging methodology with cascaded dual-polarity waves (CDWs), which consists of a pulse train with positive and negative polarities. A new coding scheme and a corresponding linear decoding process were thereby designed to obtain the recovered signals with increased amplitude, thus increasing the SNR without sacrificing the frame rate. The newly designed CDW ultrafast ultrasound imaging technique achieved higher quality B-mode images than coherent plane-wave compounding (CPWC) and multiplane wave (MW) imaging in a calibration phantom, ex vivo pork belly, and in vivo human back muscle. CDW imaging shows a significant improvement in the SNR (10.71 dB versus CPWC and 7.62 dB versus MW), penetration depth (36.94% versus CPWC and 35.14% versus MW), and contrast ratio in deep regions (5.97 dB versus CPWC and 5.05 dB versus MW) without compromising other image quality metrics, such as spatial resolution and frame rate. The enhanced image qualities and ultrafast frame rates offered by CDW imaging beget great potential for various novel imaging applications.

Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

High-resolution vascular tissue characterization in mice using 55MHz ultrasound hybrid imaging.

PubMed

Mahmoud, Ahmed M; Sandoval, Cesar; Teng, Bunyen; Schnermann, Jurgen B; Martin, Karen H; Mustafa, S Jamal; Mukdadi, Osama M

2013-03-01

Ultrasound and Duplex ultrasonography in particular are routinely used to diagnose cardiovascular disease (CVD), which is the leading cause of morbidity and mortality worldwide. However, these techniques may not be able to characterize vascular tissue compositional changes due to CVD. This work describes an ultrasound-based hybrid imaging technique that can be used for vascular tissue characterization and the diagnosis of atherosclerosis. Ultrasound radiofrequency (RF) data were acquired and processed in time, frequency, and wavelet domains to extract six parameters including time integrated backscatter (T(IB)), time variance (T(var)), time entropy (T(E)), frequency integrated backscatter (F(IB)), wavelet root mean square value (W(rms)), and wavelet integrated backscatter (W(IB)). Each parameter was used to reconstruct an image co-registered to morphological B-scan. The combined set of hybrid images were used to characterize vascular tissue in vitro and in vivo using three mouse models including control (C57BL/6), and atherosclerotic apolipoprotein E-knockout (APOE-KO) and APOE/A(1) adenosine receptor double knockout (DKO) mice. The technique was tested using high-frequency ultrasound including single-element (center frequency=55 MHz) and commercial array (center frequency=40 MHz) systems providing superior spatial resolutions of 24 μm and 40 μm, respectively. Atherosclerotic vascular lesions in the APOE-KO mouse exhibited the highest values (contrast) of -10.11±1.92 dB, -12.13±2.13 dB, -7.54±1.45 dB, -5.10±1.06 dB, -5.25±0.94 dB, and -10.23±2.12 dB in T(IB), T(var), T(E), F(IB), W(rms), W(IB) hybrid images (n=10, p<0.05), respectively. Control segments of normal vascular tissue showed the lowest values of -20.20±2.71 dB, -22.54±4.54 dB, -14.94±2.05 dB, -9.64±1.34 dB, -10.20±1.27 dB, and -19.36±3.24 dB in same hybrid images (n=6, p<0.05). Results from both histology and optical images showed good agreement with ultrasound findings within a maximum

High-resolution vascular tissue characterization in mice using 55 MHz ultrasound hybrid imaging

PubMed Central

Mahmoud, Ahmed M.; Sandoval, Cesar; Teng, Bunyen; Schnermann, Jurgen B.; Martin, Karen H.; Mustafa, S. Jamal; Mukdadi, Osama M.

2012-01-01

Ultrasound and Duplex ultrasonography in particular are routinely used to diagnose cardiovascular disease (CVD), which is the leading cause of morbidity and mortality worldwide. However, these techniques may not be able to characterize vascular tissue compositional changes due to CVD. This work describes an ultrasound-based hybrid imaging technique that can be used for vascular tissue characterization and the diagnosis of atherosclerosis. Ultrasound radiofrequency (RF) data were acquired and processed in time, frequency, and wavelet domains to extract six parameters including time integrated backscatter (TIB), time variance (Tvar), time entropy (TE), frequency integrated backscatter (FIB), wavelet root mean square value (Wrms), and wavelet integrated backscatter (WIB). Each parameter was used to reconstruct an image co-registered to morphological B-scan. The combined set of hybrid images were used to characterize vascular tissue in vitro and in vivo using three mouse models including control (C57BL/6), and atherosclerotic apolipoprotein E-knockout (APOE-KO) and APOE/A1 adenosine receptor double knockout (DKO) mice. The technique was tested using high-frequency ultrasound including single-element (center frequency = 55 MHz) and commercial array (center frequency = 40 MHz) systems providing superior spatial resolutions of 24 μm and 40 μm, respectively. Atherosclerotic vascular lesions in the APOE-KO mouse exhibited the highest values (contrast) of −10.11 ± 1.92 dB, −12.13 ± 2.13 dB, −7.54 ± 1.45 dB, −5.10 ± 1.06 dB, −5.25 ± 0.94 dB, and −10.23 ± 2.12 dB in TIB, Tvar, TE, FIB, Wrms, WIB hybrid images (n = 10, p < 0.05), respectively. Control segments of normal vascular tissue showed the lowest values of −20.20 ± 2.71 dB, −22.54 ± 4.54 dB, −14.94 ± 2.05 dB, −9.64 ± 1.34 dB, −10.20 ± 1.27 dB, and −19.36 ± 3.24 dB in same hybrid images (n = 6, p < 0.05). Results from both histology and optical images showed good agreement with

Automatic segmentation of the puborectalis muscle in 3D transperineal ultrasound.

PubMed

van den Noort, Frieda; Grob, Anique T M; Slump, Cornelis H; van der Vaart, Carl H; van Stralen, Marijn

2017-10-11

The introduction of 3D analysis of the puborectalis muscle, for diagnostic purposes, into daily practice is hindered by the need for appropriate training of the observers. Automatic 3D segmentation of the puborectalis muscle in 3D transperineal ultrasound may aid to its adaption in clinical practice. A manual 3D segmentation protocol was developed to segment the puborectalis muscle. The data of 20 women, in their first trimester of pregnancy, was used to validate the reproducibility of this protocol. For automatic segmentation, active appearance models of the puborectalis muscle were developed. Those models were trained using manual segmentation data of 50 women. The performance of both manual and automatic segmentation was analyzed by measuring the overlap and distance between the segmentations. Also, the interclass correlation coefficients and their 95% confidence intervals were determined for mean echogenicity and volume of the puborectalis muscle. The ICC values of mean echogenicity (0.968-0.991) and volume (0.626-0.910) are good to very good for both automatic and manual segmentation. The results of overlap and distance for manual segmentation are as expected, showing only few pixels (2-3) mismatch on average and a reasonable overlap. Based on overlap and distance 5 mismatches in automatic segmentation were detected, resulting in an automatic segmentation a success rate of 90%. In conclusion, this study presents a reliable manual and automatic 3D segmentation of the puborectalis muscle. This will facilitate future investigation of the puborectalis muscle. It also allows for reliable measurements of clinically potentially valuable parameters like mean echogenicity. This article is protected by copyright. All rights reserved.

Virtual angioscopic visualization and analysis of coronary aneurysms using intravascular ultrasound images

NASA Astrophysics Data System (ADS)

Ayeni, Tina A.; Holmes, David R., III; Robb, Richard A.

2001-05-01

Kawasaki Disease is an inflammatory illness of young children that can seriously affect the cardiovascular system. The disease may cause coronary artery aneurysms, a thinning and dilation of the arterial wall when the wall is weakened by disease. Such aneurysms significantly increase the risk of rupture of the arterial wall, an event from which few patients survive. Due to the largely asymptotic nature of coronary aneurysms, diagnosis must be timely and accurate in order for treatment to be effective. Currently, aneurysms are detected primarily using X-ray angiography, MRI, and CT images. Increased insight into the disease and its effects on the arterial wall can be gained by multi-dimensional computerized visualization and quantitative analysis of diagnostic images made possible by the techniques of intravascular imaging and virtual endoscopy. Intravascular ultrasound images (IVUS) of a coronary artery exhibiting aneurysms were acquired from a patient with Kawasaki Disease. The disease is characterized by low luminescent in the IVUS images. Image segmentation of the abnormal, prominent anechoic regions branching from the lumen and originating within other layers of the arterial wall was performed and each region defined as a separate object. An object segmentation map was generated and used in perspective rendering of the original image volume set at successive locations along the length of the arterial segment, producing a 'fly-through' of the interior of the artery. The diseased region (aneurysm) of the wall was well defined by the differences in luminal size and by differences in appearance of the arterial wall shape observed during virtual angioscopic fly-throughs. Erosions of the endovascular surface caused pronounced horizontal and vertical ballooning of the lumen. Minute cracks within the unaffected luminal areas revealed possible early development of an aneurysm on the contralateral wall, originating in the medial section of the artery and spreading

WE-B-210-02: The Advent of Ultrafast Imaging in Biomedical Ultrasound

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanter, M.

In the last fifteen years, the introduction of plane or diverging wave transmissions rather than line by line scanning focused beams has broken the conventional barriers of ultrasound imaging. By using such large field of view transmissions, the frame rate reaches the theoretical limit of physics dictated by the ultrasound speed and an ultrasonic map can be provided typically in tens of micro-seconds (several thousands of frames per second). Interestingly, this leap in frame rate is not only a technological breakthrough but it permits the advent of completely new ultrasound imaging modes, including shear wave elastography, electromechanical wave imaging, ultrafastmore » doppler, ultrafast contrast imaging, and even functional ultrasound imaging of brain activity (fUltrasound) introducing Ultrasound as an emerging full-fledged neuroimaging modality. At ultrafast frame rates, it becomes possible to track in real time the transient vibrations – known as shear waves – propagating through organs. Such “human body seismology” provides quantitative maps of local tissue stiffness whose added value for diagnosis has been recently demonstrated in many fields of radiology (breast, prostate and liver cancer, cardiovascular imaging, …). Today, Supersonic Imagine company is commercializing the first clinical ultrafast ultrasound scanner, Aixplorer with real time Shear Wave Elastography. This is the first example of an ultrafast Ultrasound approach surpassing the research phase and now widely spread in the clinical medical ultrasound community with an installed base of more than 1000 Aixplorer systems in 54 countries worldwide. For blood flow imaging, ultrafast Doppler permits high-precision characterization of complex vascular and cardiac flows. It also gives ultrasound the ability to detect very subtle blood flow in very small vessels. In the brain, such ultrasensitive Doppler paves the way for fUltrasound (functional ultrasound imaging) of brain activity with

Acoustic Radiation Force Elasticity Imaging in Diagnostic Ultrasound

PubMed Central

Doherty, Joshua R.; Trahey, Gregg E.; Nightingale, Kathryn R.; Palmeri, Mark L.

2013-01-01

The development of ultrasound-based elasticity imaging methods has been the focus of intense research activity since the mid-1990s. In characterizing the mechanical properties of soft tissues, these techniques image an entirely new subset of tissue properties that cannot be derived with conventional ultrasound techniques. Clinically, tissue elasticity is known to be associated with pathological condition and with the ability to image these features in vivo, elasticity imaging methods may prove to be invaluable tools for the diagnosis and/or monitoring of disease. This review focuses on ultrasound-based elasticity imaging methods that generate an acoustic radiation force to induce tissue displacements. These methods can be performed non-invasively during routine exams to provide either qualitative or quantitative metrics of tissue elasticity. A brief overview of soft tissue mechanics relevant to elasticity imaging is provided, including a derivation of acoustic radiation force, and an overview of the various acoustic radiation force elasticity imaging methods. PMID:23549529

Acoustic radiation force elasticity imaging in diagnostic ultrasound.

PubMed

Doherty, Joshua R; Trahey, Gregg E; Nightingale, Kathryn R; Palmeri, Mark L

2013-04-01

The development of ultrasound-based elasticity imaging methods has been the focus of intense research activity since the mid-1990s. In characterizing the mechanical properties of soft tissues, these techniques image an entirely new subset of tissue properties that cannot be derived with conventional ultrasound techniques. Clinically, tissue elasticity is known to be associated with pathological condition and with the ability to image these features in vivo; elasticity imaging methods may prove to be invaluable tools for the diagnosis and/or monitoring of disease. This review focuses on ultrasound-based elasticity imaging methods that generate an acoustic radiation force to induce tissue displacements. These methods can be performed noninvasively during routine exams to provide either qualitative or quantitative metrics of tissue elasticity. A brief overview of soft tissue mechanics relevant to elasticity imaging is provided, including a derivation of acoustic radiation force, and an overview of the various acoustic radiation force elasticity imaging methods.

Coupled dictionary learning for joint MR image restoration and segmentation

NASA Astrophysics Data System (ADS)

Yang, Xuesong; Fan, Yong

2018-03-01

To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.

Windowed time-reversal music technique for super-resolution ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Labyed, Yassin

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements.

High frequency ultrasound: a new frontier for ultrasound.

PubMed

Shung, K; Cannata, Jonathan; Qifa Zhou, Member; Lee, Jungwoo

2009-01-01

High frequency ultrasonic imaging is considered by many to be the next frontier in ultrasonic imaging because higher frequencies yield much improved spatial resolution by sacrificing the depth of penetration. It has many clinical applications including visualizing blood vessel wall, anterior segments of the eye and skin. Another application is small animal imaging. Ultrasound is especially attractive in imaging the heart of a small animal like mouse which has a size in the mm range and a heart beat rate faster than 600 BPM. A majority of current commercial high frequency scanners often termed "ultrasonic backscatter microscope or UBM" acquire images by scanning single element transducers at frequencies between 50 to 80 MHz with a frame rate lower than 40 frames/s, making them less suitable for this application. High frequency linear arrays and linear array based ultrasonic imaging systems at frequencies higher than 30 MHz are being developed. The engineering of such arrays and development of high frequency imaging systems has been proven to be highly challenging. High frequency ultrasound may find other significant biomedical applications. The development of acoustic tweezers for manipulating microparticles is such an example.

An interactive medical image segmentation framework using iterative refinement.

PubMed

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rayleigh-maximum-likelihood bilateral filter for ultrasound image enhancement.

PubMed

Li, Haiyan; Wu, Jun; Miao, Aimin; Yu, Pengfei; Chen, Jianhua; Zhang, Yufeng

2017-04-17

Ultrasound imaging plays an important role in computer diagnosis since it is non-invasive and cost-effective. However, ultrasound images are inevitably contaminated by noise and speckle during acquisition. Noise and speckle directly impact the physician to interpret the images and decrease the accuracy in clinical diagnosis. Denoising method is an important component to enhance the quality of ultrasound images; however, several limitations discourage the results because current denoising methods can remove noise while ignoring the statistical characteristics of speckle and thus undermining the effectiveness of despeckling, or vice versa. In addition, most existing algorithms do not identify noise, speckle or edge before removing noise or speckle, and thus they reduce noise and speckle while blurring edge details. Therefore, it is a challenging issue for the traditional methods to effectively remove noise and speckle in ultrasound images while preserving edge details. To overcome the above-mentioned limitations, a novel method, called Rayleigh-maximum-likelihood switching bilateral filter (RSBF) is proposed to enhance ultrasound images by two steps: noise, speckle and edge detection followed by filtering. Firstly, a sorted quadrant median vector scheme is utilized to calculate the reference median in a filtering window in comparison with the central pixel to classify the target pixel as noise, speckle or noise-free. Subsequently, the noise is removed by a bilateral filter and the speckle is suppressed by a Rayleigh-maximum-likelihood filter while the noise-free pixels are kept unchanged. To quantitatively evaluate the performance of the proposed method, synthetic ultrasound images contaminated by speckle are simulated by using the speckle model that is subjected to Rayleigh distribution. Thereafter, the corrupted synthetic images are generated by the original image multiplied with the Rayleigh distributed speckle of various signal to noise ratio (SNR) levels and

Automated skin segmentation in ultrasonic evaluation of skin toxicity in breast cancer radiotherapy.

PubMed

Gao, Yi; Tannenbaum, Allen; Chen, Hao; Torres, Mylin; Yoshida, Emi; Yang, Xiaofeng; Wang, Yuefeng; Curran, Walter; Liu, Tian

2013-11-01

Skin toxicity is the most common side effect of breast cancer radiotherapy and impairs the quality of life of many breast cancer survivors. We, along with other researchers, have recently found quantitative ultrasound to be effective as a skin toxicity assessment tool. Although more reliable than standard clinical evaluations (visual observation and palpation), the current procedure for ultrasound-based skin toxicity measurements requires manual delineation of the skin layers (i.e., epidermis-dermis and dermis-hypodermis interfaces) on each ultrasound B-mode image. Manual skin segmentation is time consuming and subjective. Moreover, radiation-induced skin injury may decrease image contrast between the dermis and hypodermis, which increases the difficulty of delineation. Therefore, we have developed an automatic skin segmentation tool (ASST) based on the active contour model with two significant modifications: (i) The proposed algorithm introduces a novel dual-curve scheme for the double skin layer extraction, as opposed to the original single active contour method. (ii) The proposed algorithm is based on a geometric contour framework as opposed to the previous parametric algorithm. This ASST algorithm was tested on a breast cancer image database of 730 ultrasound breast images (73 ultrasound studies of 23 patients). We compared skin segmentation results obtained with the ASST with manual contours performed by two physicians. The average percentage differences in skin thickness between the ASST measurement and that of each physician were less than 5% (4.8 ± 17.8% and -3.8 ± 21.1%, respectively). In summary, we have developed an automatic skin segmentation method that ensures objective assessment of radiation-induced changes in skin thickness. Our ultrasound technology offers a unique opportunity to quantify tissue injury in a more meaningful and reproducible manner than the subjective assessments currently employed in the clinic. Copyright © 2013 World

Needle tip visibility in 3D ultrasound images

NASA Astrophysics Data System (ADS)

Arif, Muhammad; Moelker, Adriaan; van Walsum, Theo

2017-03-01

Needle visibility is of crucial importance for ultrasound guided interventional procedures. However, several factors, such as shadowing by bone or gas and tissue echogenic properties similar to needles, may compromise needle visibility. Additionally, small angle between the ultrasound beam and the needle, as well as small gauged needles may reduce visibility. Variety in needle tips design may also affect needle visibility. Whereas several studies have investigated needle visibility in 2D ultrasound imaging, no data is available for 3D ultrasound imaging, a modality that has great potential for image guidance interventions1. In this study, we evaluated needle visibility using a 3D ultrasound transducer. We examined different needles in a tissue mimicking liver phantom at three angles (200, 550 and 900) and quantify their visibility. The liver phantom was made by 5% polyvinyl alcohol solution containing 1% Silica gel particles to act as ultrasound scattering particles. We used four needles; two biopsy needles (Quick core 14G and 18G), one Ablation needle (Radiofrequency Ablation 17G), and Initial puncture needle (IP needle 17G). The needle visibility was quantified by calculating contrast to noise ratio. The results showed that the visibility for all needles were almost similar at large angles. However the difference in visibility at lower angles is more prominent. Furthermore, the visibility increases with the increase in angle of ultrasound beam with needles.

All-optical pulse-echo ultrasound probe for intravascular imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Colchester, Richard J.; Noimark, Sacha; Mosse, Charles A.; Zhang, Edward Z.; Beard, Paul C.; Parkin, Ivan P.; Papakonstantinou, Ioannis; Desjardins, Adrien E.

2016-02-01

High frequency ultrasound probes such as intravascular ultrasound (IVUS) and intracardiac echocardiography (ICE) catheters can be invaluable for guiding minimally invasive medical procedures in cardiology such as coronary stent placement and ablation. With current-generation ultrasound probes, ultrasound is generated and received electrically. The complexities involved with fabricating these electrical probes can result in high costs that limit their clinical applicability. Additionally, it can be challenging to achieve wide transmission bandwidths and adequate wideband reception sensitivity with small piezoelectric elements. Optical methods for transmitting and receiving ultrasound are emerging as alternatives to their electrical counterparts. They offer several distinguishing advantages, including the potential to generate and detect the broadband ultrasound fields (tens of MHz) required for high resolution imaging. In this study, we developed a miniature, side-looking, pulse-echo ultrasound probe for intravascular imaging, with fibre-optic transmission and reception. The axial resolution was better than 70 microns, and the imaging depth in tissue was greater than 1 cm. Ultrasound transmission was performed by photoacoustic excitation of a carbon nanotube/polydimethylsiloxane composite material; ultrasound reception, with a fibre-optic Fabry-Perot cavity. Ex vivo tissue studies, which included healthy swine tissue and diseased human tissue, demonstrated the strong potential of this technique. To our knowledge, this is the first study to achieve an all-optical pulse-echo ultrasound probe for intravascular imaging. The potential for performing all-optical B-mode imaging (2D and 3D) with virtual arrays of transmit/receive elements, and hybrid imaging with pulse-echo ultrasound and photoacoustic sensing are discussed.

A fully convolutional networks (FCN) based image segmentation algorithm in binocular imaging system

NASA Astrophysics Data System (ADS)

Long, Zourong; Wei, Biao; Feng, Peng; Yu, Pengwei; Liu, Yuanyuan

2018-01-01

This paper proposes an image segmentation algorithm with fully convolutional networks (FCN) in binocular imaging system under various circumstance. Image segmentation is perfectly solved by semantic segmentation. FCN classifies the pixels, so as to achieve the level of image semantic segmentation. Different from the classical convolutional neural networks (CNN), FCN uses convolution layers instead of the fully connected layers. So it can accept image of arbitrary size. In this paper, we combine the convolutional neural network and scale invariant feature matching to solve the problem of visual positioning under different scenarios. All high-resolution images are captured with our calibrated binocular imaging system and several groups of test data are collected to verify this method. The experimental results show that the binocular images are effectively segmented without over-segmentation. With these segmented images, feature matching via SURF method is implemented to obtain regional information for further image processing. The final positioning procedure shows that the results are acceptable in the range of 1.4 1.6 m, the distance error is less than 10mm.

Automatic tissue image segmentation based on image processing and deep learning

NASA Astrophysics Data System (ADS)

Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting

2018-02-01

Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies or other novel imaging technologies. Plus, image segmentation also provides detailed structure description for quantitative visualization of treating light distribution in the human body when incorporated with 3D light transport simulation method. Here we used image enhancement, operators, and morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in a deep learning way. We also introduced parallel computing. Such approaches greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. Our results can be used as a criteria when diagnosing diseases such as cerebral atrophy, which is caused by pathological changes in gray matter or white matter. We demonstrated the great potential of such image processing and deep leaning combined automatic tissue image segmentation in personalized medicine, especially in monitoring, and treatments.

Improved Contrast-Enhanced Ultrasound Imaging With Multiplane-Wave Imaging.

PubMed

Gong, Ping; Song, Pengfei; Chen, Shigao

2018-02-01

Contrast-enhanced ultrasound (CEUS) imaging has great potential for use in new ultrasound clinical applications such as myocardial perfusion imaging and abdominal lesion characterization. In CEUS imaging, contrast agents (i.e., microbubbles) are used to improve contrast between blood and tissue because of their high nonlinearity under low ultrasound pressure. However, the quality of CEUS imaging sometimes suffers from a low signal-to-noise ratio (SNR) in deeper imaging regions when a low mechanical index (MI) is used to avoid microbubble disruption, especially for imaging at off-resonance transmit frequencies. In this paper, we propose a new strategy of combining CEUS sequences with the recently proposed multiplane-wave (MW) compounding method to improve the SNR of CEUS in deeper imaging regions without increasing MI or sacrificing frame rate. The MW-CEUS method emits multiple Hadamard-coded CEUS pulses in each transmission event (i.e., pulse-echo event). The received echo signals first undergo fundamental bandpass filtering (i.e., the filter is centered on the transmit frequency) to eliminate the microbubble's second-harmonic signals because they cannot be encoded by pulse inversion. The filtered signals are then Hadamard decoded and realigned in fast time to recover the signals as they would have been obtained using classic CEUS pulses, followed by designed recombination to cancel the linear tissue responses. The MW-CEUS method significantly improved contrast-to-tissue ratio and SNR of CEUS imaging by transmitting longer coded pulses. The image resolution was also preserved. The microbubble disruption ratio and motion artifacts in MW-CEUS were similar to those of classic CEUS imaging. In addition, the MW-CEUS sequence can be adapted to other transmission coding formats. These properties of MW-CEUS can potentially facilitate CEUS imaging for many clinical applications, especially assessing deep abdominal organs or the heart.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Human placental vasculature imaging using an LED-based photoacoustic/ultrasound imaging system

NASA Astrophysics Data System (ADS)

Maneas, Efthymios; Xia, Wenfeng; Kuniyil Ajith Singh, Mithun; Sato, Naoto; Agano, Toshitaka; Ourselin, Sebastien; West, Simeon J.; David, Anna L.; Vercauteren, Tom; Desjardins, Adrien E.

2018-02-01

Minimally invasive fetal interventions, such as those used for therapy of twin-to-twin transfusion syndrome (TTTS), require accurate image guidance to optimise patient outcomes. Currently, TTTS can be treated fetoscopically by identifying anastomosing vessels on the chorionic (fetal) placental surface, and then performing photocoagulation. Incomplete photocoagulation increases the risk of procedure failure. Photoacoustic imaging can provide contrast for both haemoglobin concentration and oxygenation, and in this study, it was hypothesised that it can resolve chorionic placental vessels. We imaged a term human placenta that was collected after caesarean section delivery using a photoacoustic/ultrasound system (AcousticX) that included light emitting diode (LED) arrays for excitation light and a linear-array ultrasound imaging probe. Two-dimensional (2D) co-registered photoacoustic and B-mode pulse-echo ultrasound images were acquired and displayed in real-time. Translation of the imaging probe enabled 3D imaging. This feasibility study demonstrated that photoacoustic imaging can be used to visualise chorionic placental vasculature, and that it has strong potential to guide minimally invasive fetal interventions.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong

2011-01-01

Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.

[Liver segment anatomy in ultrasound--examinations to define the frontier between segment II/III and literature review].

PubMed

Wolf, H; Gross, F; Merz, A; Schuler, A

2013-03-01

Liver segment definition due to Couinaud is the basis for localisation of focal liver lesions in imaging, in the follow-up or for planning operations. A literature review shows variety in segment definition and the frontier between segment II and III in the left liver lobe, in the course of the portal vein level and in variations of liver veins. The aim of this study is to demonstrate liver segment anatomy in sonography compared to anatomic preparations and the literature. This leads to a proposal for a unique nomenclature and illustration. 152 liver healthy persons (77 F, 75 M, mean age 63.3 years (18 - 91 years) were examined with standardised abdominal ultrasound in longitudinal, transversal and axis planes. (Angle) measurements were taken to define the left hepatic vein (Fissura sinistra), the Ramus umbilicalis of the portal vein (Fissura umbilicalis), the portal vein level and the amount and variations of the liver veins. The left hepatic vein was found with a mean angle of 24° (0 - 70°) left to the median axis, the Pars umbilicalis of the portal vein wasalmost strictly in the mid axis. The portal vein level was located with a mean angle of 61° (5 - 110°) right to the median with no variations of the two main branches. 27 (18 %) out of the remaining 151 patients showed variations of the liver veins: 7 × (4.6 %) a doubled mid hepatic vein, 12 × (8 %) a doubled left hepatic vein, 4 × (2.7 %) 3 left liver veins were found with a short (≤ 1 cm) common trunk, 1 × each (0.7 %) four left liver veins with a short common trunk, one trifurcation of the mid hepatic vein, one doubled right liver vein and one common trunk (2 cm) of all 3 main liver veins leading to the inferior V. cava. The surgical functional liver segment definition by Couinaud is the basis for localisation of focal liver lesions. The frontier between segment II and III is mainly described as a horizontal plane in the literature. The course of the left liver vein (fissura sinistra) has a mean

Medical image segmentation using 3D MRI data

NASA Astrophysics Data System (ADS)

Voronin, V.; Marchuk, V.; Semenishchev, E.; Cen, Yigang; Agaian, S.

2017-05-01

Precise segmentation of three-dimensional (3D) magnetic resonance imaging (MRI) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Accurate automatic extraction a 3D component from images obtained by magnetic resonance imaging (MRI) is a challenging segmentation problem due to the small size objects of interest (e.g., blood vessels, bones) in each 2D MRA slice and complex surrounding anatomical structures. Our objective is to develop a specific segmentation scheme for accurately extracting parts of bones from MRI images. In this paper, we use a segmentation algorithm to extract the parts of bones from Magnetic Resonance Imaging (MRI) data sets based on modified active contour method. As a result, the proposed method demonstrates good accuracy in a comparison between the existing segmentation approaches on real MRI data.

Multiplane wave imaging increases signal-to-noise ratio in ultrafast ultrasound imaging.

PubMed

Tiran, Elodie; Deffieux, Thomas; Correia, Mafalda; Maresca, David; Osmanski, Bruno-Felix; Sieu, Lim-Anna; Bergel, Antoine; Cohen, Ivan; Pernot, Mathieu; Tanter, Mickael

2015-11-07

Ultrafast imaging using plane or diverging waves has recently enabled new ultrasound imaging modes with improved sensitivity and very high frame rates. Some of these new imaging modalities include shear wave elastography, ultrafast Doppler, ultrafast contrast-enhanced imaging and functional ultrasound imaging. Even though ultrafast imaging already encounters clinical success, increasing even more its penetration depth and signal-to-noise ratio for dedicated applications would be valuable. Ultrafast imaging relies on the coherent compounding of backscattered echoes resulting from successive tilted plane waves emissions; this produces high-resolution ultrasound images with a trade-off between final frame rate, contrast and resolution. In this work, we introduce multiplane wave imaging, a new method that strongly improves ultrafast images signal-to-noise ratio by virtually increasing the emission signal amplitude without compromising the frame rate. This method relies on the successive transmissions of multiple plane waves with differently coded amplitudes and emission angles in a single transmit event. Data from each single plane wave of increased amplitude can then be obtained, by recombining the received data of successive events with the proper coefficients. The benefits of multiplane wave for B-mode, shear wave elastography and ultrafast Doppler imaging are experimentally demonstrated. Multiplane wave with 4 plane waves emissions yields a 5.8  ±  0.5 dB increase in signal-to-noise ratio and approximately 10 mm in penetration in a calibrated ultrasound phantom (0.7 d MHz(-1) cm(-1)). In shear wave elastography, the same multiplane wave configuration yields a 2.07  ±  0.05 fold reduction of the particle velocity standard deviation and a two-fold reduction of the shear wave velocity maps standard deviation. In functional ultrasound imaging, the mapping of cerebral blood volume results in a 3 to 6 dB increase of the contrast-to-noise ratio in deep

Comparison of longitudinal excursion of a nerve-phantom model using quantitative ultrasound imaging and motion analysis system methods: A convergent validity study.

PubMed

Paquette, Philippe; El Khamlichi, Youssef; Lamontagne, Martin; Higgins, Johanne; Gagnon, Dany H

2017-08-01

Quantitative ultrasound imaging is gaining popularity in research and clinical settings to measure the neuromechanical properties of the peripheral nerves such as their capability to glide in response to body segment movement. Increasing evidence suggests that impaired median nerve longitudinal excursion is associated with carpal tunnel syndrome. To date, psychometric properties of longitudinal nerve excursion measurements using quantitative ultrasound imaging have not been extensively investigated. This study investigates the convergent validity of the longitudinal nerve excursion by comparing measures obtained using quantitative ultrasound imaging with those determined with a motion analysis system. A 38-cm long rigid nerve-phantom model was used to assess the longitudinal excursion in a laboratory environment. The nerve-phantom model, immersed in a 20-cm deep container filled with a gelatin-based solution, was moved 20 times using a linear forward and backward motion. Three light-emitting diodes were used to record nerve-phantom excursion with a motion analysis system, while a 5-cm linear transducer allowed simultaneous recording via ultrasound imaging. Both measurement techniques yielded excellent association ( r  = 0.99) and agreement (mean absolute difference between methods = 0.85 mm; mean relative difference between methods = 7.48 %). Small discrepancies were largely found when larger excursions (i.e. > 10 mm) were performed, revealing slight underestimation of the excursion by the ultrasound imaging analysis software. Quantitative ultrasound imaging is an accurate method to assess the longitudinal excursion of an in vitro nerve-phantom model and appears relevant for future research protocols investigating the neuromechanical properties of the peripheral nerves.

A high-resolution 3D ultrasonic system for rapid evaluation of the anterior and posterior segment.

PubMed

Peyman, Gholam A; Ingram, Charles P; Montilla, Leonardo G; Witte, Russell S

2012-01-01

Traditional ultrasound imaging systems for ophthalmology employ slow, mechanical scanning of a single-element ultrasound transducer. The goal was to demonstrate rapid examination of the anterior and posterior segment with a three-dimensional (3D) commercial ultrasound system incorporating high-resolution linear probe arrays. The 3D images of the porcine eye were generated in approximately 10 seconds by scanning one of two commercial linear arrays (25- and 50-MHz). Healthy enucleated pig eyes were compared with those with induced injury or placement of a foreign material (eg, metal). Rapid, volumetric imaging was also demonstrated in one human eye in vivo. The 50-MHz probe provided exquisite volumetric images of the anterior segment at a depth up to 15 mm and axial resolution of 30 μm. The 25-MHz probe provided a larger field of view (lateral X depth: 20 × 30 mm), sufficient for capturing the entire anterior and posterior segments of the pig eye, at a resolution of 60 μm. A 50-MHz scan through the human eyelid illustrated detailed structures of the Meibomian glands, cilia, cornea, and anterior segment back to the posterior capsule. The 3D system with its high-frequency ultrasound arrays, fast data acquisition, and volume rendering capability shows promise for investigating anterior and posterior structures of the eye. Copyright 2012, SLACK Incorporated.

Monitoring radiofrequency ablation with ultrasound Nakagami imaging.

PubMed

Wang, Chiao-Yin; Geng, Xiaonan; Yeh, Ta-Sen; Liu, Hao-Li; Tsui, Po-Hsiang

2013-07-01

Radiofrequency ablation (RFA) is a widely used alternative modality in the treatment of liver tumors. Ultrasound B-mode imaging is an important tool to guide the insertion of the RFA electrode into the tissue. However, it is difficult to visualize the ablation zone because RFA induces the shadow effect in a B-scan. Based on the randomness of ultrasonic backscattering, this study proposes ultrasound Nakagami imaging, which is a well-established method for backscattered statistics analysis, as an approach to complement the conventional B-scan for evaluating the ablation region. Porcine liver samples (n = 6) were ablated using a RFA system and monitored by employing an ultrasound scanner equipped with a 7.5 MHz linear array transducer. During the stages of ablation (0-12 min) and postablation (12-24 min), the raw backscattered data were acquired at a sampling rate of 30 MHz for B-mode, Nakagami imaging, and polynomial approximation of Nakagami imaging. The contrast-to-noise ratio (CNR) was also calculated to compare the image contrasts of the B-mode and Nakagami images. The results demonstrated that the Nakagami image has the ability to visualize changes in the backscattered statistics in the ablation zone, including the shadow region during RFA. The average Nakagami parameter increased from 0.2 to 0.6 in the ablation stage, and then decreased to approximately 0.3 at the end of the postablation stage. Moreover, the CNR of the Nakagami image was threefold that of the B-mode image, showing that the Nakagami image has a better image contrast for monitoring RFA. Specifically, the use of the polynomial approximation equips the Nakagami image with an enhanced ability to estimate the range of the ablation region. This study demonstrated that ultrasound Nakagami imaging based on the analysis of backscattered statistics has the ability to visualize the RFA-induced ablation zone, even if the shadow effect exists in the B-scan.

Building Roof Segmentation from Aerial Images Using a Line-and Region-Based Watershed Segmentation Technique

PubMed Central

Merabet, Youssef El; Meurie, Cyril; Ruichek, Yassine; Sbihi, Abderrahmane; Touahni, Raja

2015-01-01

In this paper, we present a novel strategy for roof segmentation from aerial images (orthophotoplans) based on the cooperation of edge- and region-based segmentation methods. The proposed strategy is composed of three major steps. The first one, called the pre-processing step, consists of simplifying the acquired image with an appropriate couple of invariant and gradient, optimized for the application, in order to limit illumination changes (shadows, brightness, etc.) affecting the images. The second step is composed of two main parallel treatments: on the one hand, the simplified image is segmented by watershed regions. Even if the first segmentation of this step provides good results in general, the image is often over-segmented. To alleviate this problem, an efficient region merging strategy adapted to the orthophotoplan particularities, with a 2D modeling of roof ridges technique, is applied. On the other hand, the simplified image is segmented by watershed lines. The third step consists of integrating both watershed segmentation strategies into a single cooperative segmentation scheme in order to achieve satisfactory segmentation results. Tests have been performed on orthophotoplans containing 100 roofs with varying complexity, and the results are evaluated with the VINETcriterion using ground-truth image segmentation. A comparison with five popular segmentation techniques of the literature demonstrates the effectiveness and the reliability of the proposed approach. Indeed, we obtain a good segmentation rate of 96% with the proposed method compared to 87.5% with statistical region merging (SRM), 84% with mean shift, 82% with color structure code (CSC), 80% with efficient graph-based segmentation algorithm (EGBIS) and 71% with JSEG. PMID:25648706

MO-AB-210-00: Diagnostic Ultrasound Imaging Quality Control and High Intensity Focused Ultrasound Therapy Hands-On Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrationsmore » with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant

Segmentation of medical images using explicit anatomical knowledge

NASA Astrophysics Data System (ADS)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Intravascular ultrasound in coronary atherosclerosis: a new approach to clinical assessment.

PubMed

Liebson, P R; Klein, L W

1992-06-01

Intravascular ultrasound evaluation of the coronary arteries by means of a selective coronary catheter attached to an ultrasound unit has afforded precise depiction of coronary lumen diameter and area at the level of the catheter tip. The arterial wall at this level can be evaluated for lipid, fibrous tissue, calcification, wall dissections, and intraluminal thrombi. The technique has the advantage over coronary angioscopy and angiography in that it does not require infusions or injections to allow visualization, and it has the ability to depict the inside of the arterial wall. The current disadvantages include the inability to visualize the vessel segments distal to the catheter tip. Three-dimensional reconstruction techniques allow depiction of the segment of the artery traversed by the catheter tip. The use of Doppler ultrasound imaging provides information on coronary flow velocities through coronary obstructions. Intravascular ultrasound images may provide information that complements the coronary arteriogram and may have an impact on patient care and clinical investigation strategies.

Ultrasound in Radiology: from Anatomic, Functional, Molecular Imaging to Drug Delivery and Image-Guided Therapy

PubMed Central

Klibanov, Alexander L.; Hossack, John A.

2015-01-01

During the past decade, ultrasound has expanded medical imaging well beyond the “traditional” radiology setting - a combination of portability, low cost and ease of use makes ultrasound imaging an indispensable tool for radiologists as well as for other medical professionals who need to obtain imaging diagnosis or guide a therapeutic intervention quickly and efficiently. Ultrasound combines excellent ability for deep penetration into soft tissues with very good spatial resolution, with only a few exceptions (i.e. those involving overlying bone or gas). Real-time imaging (up to hundreds and thousands frames per second) enables guidance of therapeutic procedures and biopsies; characterization of the mechanical properties of the tissues greatly aids with the accuracy of the procedures. The ability of ultrasound to deposit energy locally brings about the potential for localized intervention encompassing: tissue ablation, enhancing penetration through the natural barriers to drug delivery in the body and triggering drug release from carrier micro- and nanoparticles. The use of microbubble contrast agents brings the ability to monitor and quantify tissue perfusion, and microbubble targeting with ligand-decorated microbubbles brings the ability to obtain molecular biomarker information, i.e., ultrasound molecular imaging. Overall, ultrasound has become the most widely used imaging modality in modern medicine; it will continue to grow and expand. PMID:26200224

An algorithm for calculi segmentation on ureteroscopic images.

PubMed

Rosa, Benoît; Mozer, Pierre; Szewczyk, Jérôme

2011-03-01

The purpose of the study is to develop an algorithm for the segmentation of renal calculi on ureteroscopic images. In fact, renal calculi are common source of urological obstruction, and laser lithotripsy during ureteroscopy is a possible therapy. A laser-based system to sweep the calculus surface and vaporize it was developed to automate a very tedious manual task. The distal tip of the ureteroscope is directed using image guidance, and this operation is not possible without an efficient segmentation of renal calculi on the ureteroscopic images. We proposed and developed a region growing algorithm to segment renal calculi on ureteroscopic images. Using real video images to compute ground truth and compare our segmentation with a reference segmentation, we computed statistics on different image metrics, such as Precision, Recall, and Yasnoff Measure, for comparison with ground truth. The algorithm and its parameters were established for the most likely clinical scenarii. The segmentation results are encouraging: the developed algorithm was able to correctly detect more than 90% of the surface of the calculi, according to an expert observer. Implementation of an algorithm for the segmentation of calculi on ureteroscopic images is feasible. The next step is the integration of our algorithm in the command scheme of a motorized system to build a complete operating prototype.

Imaging nonmelanoma skin cancers with combined ultrasound-photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Sunar, Ulas; Rohrbach, Daniel J.; Morgan, Janet; Zeitouni, Natalie

2013-03-01

PDT has become a treatment of choice especially for the cases with multiple sites and large areas. However, the efficacy of PDT is limited for thicker and deeper tumors. Depth and size information as well as vascularity can provide useful information to clinicians for planning and evaluating PDT. High-resolution ultrasound and photoacoustic imaging can provide information regarding skin structure and vascularity. We utilized combined ultrasound-photoacoustic microscopy for imaging a basal cell carcinoma (BCC) tumor pre-PDT and the results indicate that combined ultrasound-photoacoustic imaging can be useful tool for PDT planning by providing both structural and functional contrasts.

Ultrasound elastographic imaging of thermal lesions and temperature profiles during radiofrequency ablation

NASA Astrophysics Data System (ADS)

Techavipoo, Udomchai

Manual palpation to sense variations in tissue stiffness for disease diagnosis has been regularly performed by clinicians for centuries. However, it is generally limited to large and superficial structures and the ability of the physician performing the palpation. Imaging of tissue stiffness or elastic properties via the aid of modern imaging such as ultrasound and magnetic resonance imaging, referred to as elastography, enhances the capability for disease diagnosis. In addition, elastography could be used for monitoring tissue response to minimally invasive ablative therapies, which are performed percutaneously to destruct tumors with minimum damage to surrounding tissue. Monitoring tissue temperature during ablation is another approach to estimate tissue damage. The ultimate goal of this dissertation is to improve the image quality of elastograms and temperature profiles for visualizing thermal lesions during and after ablative therapies. Elastographic imaging of thermal lesions is evaluated by comparison of sizes, shapes, and volumes with the results obtained using gross pathology. Semiautomated segmentation of lesion boundaries on elastograms is also developed. It provides comparable results to those with manual segmentation. Elastograms imaged during radiofrequency ablation in vitro show that the impact of gas bubbles during ablation on the ability to delineate the thermal lesion is small. Two novel methods to reduce noise artifacts in elastograms, and an accurate estimation of displacement vectors are proposed. The first method applies wavelet-denoising algorithms to the displacement estimates. The second method utilizes angular compounding of the elastograms generated using ultrasound signal frames acquired from different insonification angles. These angular frames are also utilized to estimate all tissue displacement vector components in response to a deformation. These enable the generation of normal and shear strain elastograms and Poisson's ratio

Ultrasound coefficient of nonlinearity imaging.

PubMed

van Sloun, Ruud; Demi, Libertario; Shan, Caifeng; Mischi, Massimo

2015-07-01

Imaging the acoustical coefficient of nonlinearity, β, is of interest in several healthcare interventional applications. It is an important feature that can be used for discriminating tissues. In this paper, we propose a nonlinearity characterization method with the goal of locally estimating the coefficient of nonlinearity. The proposed method is based on a 1-D solution of the nonlinear lossy Westerfelt equation, thereby deriving a local relation between β and the pressure wave field. Based on several assumptions, a β imaging method is then presented that is based on the ratio between the harmonic and fundamental fields, thereby reducing the effect of spatial amplitude variations of the speckle pattern. By testing the method on simulated ultrasound pressure fields and an in vitro B-mode ultrasound acquisition, we show that the designed algorithm is able to estimate the coefficient of nonlinearity, and that the tissue types of interest are well discriminable. The proposed imaging method provides a new approach to β estimation, not requiring a special measurement setup or transducer, that seems particularly promising for in vivo imaging.

Micro-ultrasound for preclinical imaging

PubMed Central

Foster, F. Stuart; Hossack, John; Adamson, S. Lee

2011-01-01

Over the past decade, non-invasive preclinical imaging has emerged as an important tool to facilitate biomedical discovery. Not only have the markets for these tools accelerated, but the numbers of peer-reviewed papers in which imaging end points and biomarkers have been used have grown dramatically. High frequency ‘micro-ultrasound’ has steadily evolved in the post-genomic era as a rapid, comparatively inexpensive imaging tool for studying normal development and models of human disease in small animals. One of the fundamental barriers to this development was the technological hurdle associated with high-frequency array transducers. Recently, new approaches have enabled the upper limits of linear and phased arrays to be pushed from about 20 to over 50 MHz enabling a broad range of new applications. The innovations leading to the new transducer technology and scanner architecture are reviewed. Applications of preclinical micro-ultrasound are explored for developmental biology, cancer, and cardiovascular disease. With respect to the future, the latest developments in high-frequency ultrasound imaging are described. PMID:22866232

Geometric reconstruction using tracked ultrasound strain imaging

NASA Astrophysics Data System (ADS)

Pheiffer, Thomas S.; Simpson, Amber L.; Ondrake, Janet E.; Miga, Michael I.

2013-03-01

The accurate identification of tumor margins during neurosurgery is a primary concern for the surgeon in order to maximize resection of malignant tissue while preserving normal function. The use of preoperative imaging for guidance is standard of care, but tumor margins are not always clear even when contrast agents are used, and so margins are often determined intraoperatively by visual and tactile feedback. Ultrasound strain imaging creates a quantitative representation of tissue stiffness which can be used in real-time. The information offered by strain imaging can be placed within a conventional image-guidance workflow by tracking the ultrasound probe and calibrating the image plane, which facilitates interpretation of the data by placing it within a common coordinate space with preoperative imaging. Tumor geometry in strain imaging is then directly comparable to the geometry in preoperative imaging. This paper presents a tracked ultrasound strain imaging system capable of co-registering with preoperative tomograms and also of reconstructing a 3D surface using the border of the strain lesion. In a preliminary study using four phantoms with subsurface tumors, tracked strain imaging was registered to preoperative image volumes and then tumor surfaces were reconstructed using contours extracted from strain image slices. The volumes of the phantom tumors reconstructed from tracked strain imaging were approximately between 1.5 to 2.4 cm3, which was similar to the CT volumes of 1.0 to 2.3 cm3. Future work will be done to robustly characterize the reconstruction accuracy of the system.

Anatomy-aware measurement of segmentation accuracy

NASA Astrophysics Data System (ADS)

Tizhoosh, H. R.; Othman, A. A.

2016-03-01

Quantifying the accuracy of segmentation and manual delineation of organs, tissue types and tumors in medical images is a necessary measurement that suffers from multiple problems. One major shortcoming of all accuracy measures is that they neglect the anatomical significance or relevance of different zones within a given segment. Hence, existing accuracy metrics measure the overlap of a given segment with a ground-truth without any anatomical discrimination inside the segment. For instance, if we understand the rectal wall or urethral sphincter as anatomical zones, then current accuracy measures ignore their significance when they are applied to assess the quality of the prostate gland segments. In this paper, we propose an anatomy-aware measurement scheme for segmentation accuracy of medical images. The idea is to create a "master gold" based on a consensus shape containing not just the outline of the segment but also the outlines of the internal zones if existent or relevant. To apply this new approach to accuracy measurement, we introduce the anatomy-aware extensions of both Dice coefficient and Jaccard index and investigate their effect using 500 synthetic prostate ultrasound images with 20 different segments for each image. We show that through anatomy-sensitive calculation of segmentation accuracy, namely by considering relevant anatomical zones, not only the measurement of individual users can change but also the ranking of users' segmentation skills may require reordering.

Opto-acoustic breast imaging with co-registered ultrasound

NASA Astrophysics Data System (ADS)

Zalev, Jason; Clingman, Bryan; Herzog, Don; Miller, Tom; Stavros, A. Thomas; Oraevsky, Alexander; Kist, Kenneth; Dornbluth, N. Carol; Otto, Pamela

2014-03-01

We present results from a recent study involving the ImagioTM breast imaging system, which produces fused real-time two-dimensional color-coded opto-acoustic (OA) images that are co-registered and temporally inter- leaved with real-time gray scale ultrasound using a specialized duplex handheld probe. The use of dual optical wavelengths provides functional blood map images of breast tissue and tumors displayed with high contrast based on total hemoglobin and oxygen saturation of the blood. This provides functional diagnostic information pertaining to tumor metabolism. OA also shows morphologic information about tumor neo-vascularity that is complementary to the morphological information obtained with conventional gray scale ultrasound. This fusion technology conveniently enables real-time analysis of the functional opto-acoustic features of lesions detected by readers familiar with anatomical gray scale ultrasound. We demonstrate co-registered opto-acoustic and ultrasonic images of malignant and benign tumors from a recent clinical study that provide new insight into the function of tumors in-vivo. Results from the Feasibility Study show preliminary evidence that the technology may have the capability to improve characterization of benign and malignant breast masses over conventional diagnostic breast ultrasound alone and to improve overall accuracy of breast mass diagnosis. In particular, OA improved speci city over that of conventional diagnostic ultrasound, which could potentially reduce the number of negative biopsies performed without missing cancers.

Patient-specific CFD simulation of intraventricular haemodynamics based on 3D ultrasound imaging.

PubMed

Bavo, A M; Pouch, A M; Degroote, J; Vierendeels, J; Gorman, J H; Gorman, R C; Segers, P

2016-09-09

The goal of this paper is to present a computational fluid dynamic (CFD) model with moving boundaries to study the intraventricular flows in a patient-specific framework. Starting from the segmentation of real-time transesophageal echocardiographic images, a CFD model including the complete left ventricle and the moving 3D mitral valve was realized. Their motion, known as a function of time from the segmented ultrasound images, was imposed as a boundary condition in an Arbitrary Lagrangian-Eulerian framework. The model allowed for a realistic description of the displacement of the structures of interest and for an effective analysis of the intraventricular flows throughout the cardiac cycle. The model provides detailed intraventricular flow features, and highlights the importance of the 3D valve apparatus for the vortex dynamics and apical flow. The proposed method could describe the haemodynamics of the left ventricle during the cardiac cycle. The methodology might therefore be of particular importance in patient treatment planning to assess the impact of mitral valve treatment on intraventricular flow dynamics.

A geometric level set model for ultrasounds analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sarti, A.; Malladi, R.

We propose a partial differential equation (PDE) for filtering and segmentation of echocardiographic images based on a geometric-driven scheme. The method allows edge-preserving image smoothing and a semi-automatic segmentation of the heart chambers, that regularizes the shapes and improves edge fidelity especially in presence of distinct gaps in the edge map as is common in ultrasound imagery. A numerical scheme for solving the proposed PDE is borrowed from level set methods. Results on human in vivo acquired 2D, 2D+time,3D, 3D+time echocardiographic images are shown.

Combined photothermal therapy and magneto-motive ultrasound imaging using multifunctional nanoparticles

NASA Astrophysics Data System (ADS)

Mehrmohammadi, Mohammad; Ma, Li L.; Chen, Yun-Sheng; Qu, Min; Joshi, Pratixa; Chen, Raeanna M.; Johnston, Keith P.; Emelianov, Stanislav

2010-02-01

Photothermal therapy is a laser-based non-invasive technique for cancer treatment. Photothermal therapy can be enhanced by employing metal nanoparticles that absorb the radiant energy from the laser leading to localized thermal damages. Targeting of nanoparticles leads to more efficient uptake and localization of photoabsorbers thus increasing the effectiveness of the treatment. Moreover, efficient targeting can reduce the required dosage of photoabsorbers; thereby reducing the side effects associated with general systematic administration of nanoparticles. Magnetic nanoparticles, due to their small size and response to an external magnetic field gradient have been proposed for targeted drug delivery. In this study, we investigate the applicability of multifunctional nanoparticles (e.g., magneto-plasmonic nanoparticles) and magneto-motive ultrasound imaging for image-guided photothermal therapy. Magneto-motive ultrasound imaging is an ultrasound based imaging technique capable of detecting magnetic nanoparticles indirectly by utilizing a high strength magnetic field to induce motion within the magnetically labeled tissue. The ultrasound imaging is used to detect the internal tissue motion. Due to presence of the magnetic component, the proposed multifunctional nanoparticles along with magneto-motive ultrasound imaging can be used to detect the presence of the photo absorbers. Clearly the higher concentration of magnetic carriers leads to a monotonic increase in magneto-motive ultrasound signal. Thus, magnetomotive ultrasound can determine the presence of the hybrid agents and provide information about their location and concentration. Furthermore, the magneto-motive ultrasound signal can indicate the change in tissue elasticity - a parameter that is expected to change significantly during the photothermal therapy. Therefore, a comprehensive guidance and assessment of the photothermal therapy may be feasible through magneto-motive ultrasound imaging and

Image segmentation on adaptive edge-preserving smoothing

NASA Astrophysics Data System (ADS)

He, Kun; Wang, Dan; Zheng, Xiuqing

2016-09-01

Nowadays, typical active contour models are widely applied in image segmentation. However, they perform badly on real images with inhomogeneous subregions. In order to overcome the drawback, this paper proposes an edge-preserving smoothing image segmentation algorithm. At first, this paper analyzes the edge-preserving smoothing conditions for image segmentation and constructs an edge-preserving smoothing model inspired by total variation. The proposed model has the ability to smooth inhomogeneous subregions and preserve edges. Then, a kind of clustering algorithm, which reasonably trades off edge-preserving and subregion-smoothing according to the local information, is employed to learn the edge-preserving parameter adaptively. At last, according to the confidence level of segmentation subregions, this paper constructs a smoothing convergence condition to avoid oversmoothing. Experiments indicate that the proposed algorithm has superior performance in precision, recall, and F-measure compared with other segmentation algorithms, and it is insensitive to noise and inhomogeneous-regions.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Programmable Real-time Clinical Photoacoustic and Ultrasound Imaging System

PubMed Central

Kim, Jeesu; Park, Sara; Jung, Yuhan; Chang, Sunyeob; Park, Jinyong; Zhang, Yumiao; Lovell, Jonathan F.; Kim, Chulhong

2016-01-01

Photoacoustic imaging has attracted interest for its capacity to capture functional spectral information with high spatial and temporal resolution in biological tissues. Several photoacoustic imaging systems have been commercialized recently, but they are variously limited by non-clinically relevant designs, immobility, single anatomical utility (e.g., breast only), or non-programmable interfaces. Here, we present a real-time clinical photoacoustic and ultrasound imaging system which consists of an FDA-approved clinical ultrasound system integrated with a portable laser. The system is completely programmable, has an intuitive user interface, and can be adapted for different applications by switching handheld imaging probes with various transducer types. The customizable photoacoustic and ultrasound imaging system is intended to meet the diverse needs of medical researchers performing both clinical and preclinical photoacoustic studies. PMID:27731357

Programmable Real-time Clinical Photoacoustic and Ultrasound Imaging System.

PubMed

Kim, Jeesu; Park, Sara; Jung, Yuhan; Chang, Sunyeob; Park, Jinyong; Zhang, Yumiao; Lovell, Jonathan F; Kim, Chulhong

2016-10-12

Photoacoustic imaging has attracted interest for its capacity to capture functional spectral information with high spatial and temporal resolution in biological tissues. Several photoacoustic imaging systems have been commercialized recently, but they are variously limited by non-clinically relevant designs, immobility, single anatomical utility (e.g., breast only), or non-programmable interfaces. Here, we present a real-time clinical photoacoustic and ultrasound imaging system which consists of an FDA-approved clinical ultrasound system integrated with a portable laser. The system is completely programmable, has an intuitive user interface, and can be adapted for different applications by switching handheld imaging probes with various transducer types. The customizable photoacoustic and ultrasound imaging system is intended to meet the diverse needs of medical researchers performing both clinical and preclinical photoacoustic studies.

Time reversal and phase coherent music techniques for super-resolution ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Labyed, Yassin

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

Standardized ultrasound templates for diagnosing appendicitis reduce annual imaging costs.

PubMed

Nordin, Andrew B; Sales, Stephen; Nielsen, Jason W; Adler, Brent; Bates, David Gregory; Kenney, Brian

2018-01-01

Ultrasound is preferred over computed tomography (CT) for diagnosing appendicitis in children to avoid undue radiation exposure. We previously reported our experience in instituting a standardized appendicitis ultrasound template, which decreased CT rates by 67.3%. In this analysis, we demonstrate the ongoing cost savings associated with using this template. Retrospective chart review for the time period preceding template implementation (June 2012-September 2012) was combined with prospective review through December 2015 for all patients in the emergency department receiving diagnostic imaging for appendicitis. The type of imaging was recorded, and imaging rates and ultrasound test statistics were calculated. Estimated annual imaging costs based on pretemplate ultrasound and CT utilization rates were compared with post-template annual costs to calculate annual and cumulative savings. In the pretemplate period, ultrasound and CT rates were 80.2% and 44.3%, respectively, resulting in a combined annual cost of $300,527.70. Similar calculations were performed for each succeeding year, accounting for changes in patient volume. Using pretemplate rates, our projected 2015 imaging cost was $371,402.86; however, our ultrasound rate had increased to 98.3%, whereas the CT rate declined to 9.6%, yielding an annual estimated cost of $224,853.00 and a savings of $146,549.86. Since implementation, annual savings have steadily increased for a cumulative cost savings of $336,683.83. Standardizing ultrasound reports for appendicitis not only reduces the use of CT scans and the associated radiation exposure but also decreases annual imaging costs despite increased numbers of imaging studies. Continued cost reduction may be possible by using diagnostic algorithms. Copyright © 2017 Elsevier Inc. All rights reserved.

Experience With Intravascular Ultrasound Imaging Of Human Atherosclerotic Arteries

NASA Astrophysics Data System (ADS)

Mallery, John A.; Gessert, James M.; Maciel, Mario; Tobis, John M.; Griffith, James M.; Berns, Michael W.; Henry, Walter L.

1989-08-01

Normal human arteries have a well-defined structure on intravascular images. The intima appears very thin and is most likely represented by a bright reflection arising from the internal elastic lamina. The smooth muscle tunica media is echo-lucent on the ultrasound image and appears as a dark band separating the intima from the adventitia. The adventitia is a brightly reflective layer of variable thickness. The thickness of the intima, and therefore of the atherosclerotic plaque can be accurately measured from the ultrasound images and correlates well with histology. Calcification within the wall of arteries is seen as bright echo reflection with shadowing of the peripheral wall. Fibrotic regions are highly reflective but do not shadow. Necrotic liquid regions within advanced atherosclerotic plaques are seen on ultrasound images as large lucent zones surrounded by echogenic tissue. Imaging can be performed before and after interventional procedures, such as laser angioplasty, balloon angioplasty and atherectomy. Intravascular ultrasound appears to provide an imaging modality for identifying the histologic characteristics of diseased arteries and for quantifying plaque thickness. It might be possible to perform such quantification to evaluate the results of interventional procedures.

Diaphragm breathing movement measurement using ultrasound and radiographic imaging: a concurrent validity.

PubMed

Noh, Dong K; Lee, Jae J; You, Joshua H

2014-01-01

Recent ultrasound imaging evidence asserts that the diaphragm is an important multifunctional muscle to control breathing as well as stabilize the core and posture in humans. However, the validity and accuracy of ultrasound for the measurement of dynamic diaphragm movements during breathing and functional core activities have not been determined. The specific aim of this study was to validate the accuracy of ultrasound imaging measurements of diaphragm movements by concurrently comparing these measurements to the gold standard of radiographic imaging measurements. A total of 14 asymptomatic adults (9 males, 5 females; mean age =28.4 ± 3.0 years) were recruited to participate in the study. Ultrasound and radiographic images were used concurrently to determine diaphragm movement (inspiration, expiration, and excursion) during tidal breathing. Pearson correlation analysis showed strong correlations, ranging from r=0.78 to r=0.83, between ultrasound and radiographic imaging measurements of the diaphragm during inhalation, exhalation, and excursion. These findings suggest that ultrasound imaging measurement is useful to accurately evaluate diaphragm movements during tidal breathing. Clinically, ultrasound imaging measurements can be used to diagnose and treat diaphragm movement impairments in individuals with neuromuscular disorders including spinal cord injuries, stroke, and multiple sclerosis.

The semiotics of medical image Segmentation.

PubMed

Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M

2018-02-01

As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.

Semantic Image Segmentation with Contextual Hierarchical Models.

PubMed

Seyedhosseini, Mojtaba; Tasdizen, Tolga

2016-05-01

Semantic segmentation is the problem of assigning an object label to each pixel. It unifies the image segmentation and object recognition problems. The importance of using contextual information in semantic segmentation frameworks has been widely realized in the field. We propose a contextual framework, called contextual hierarchical model (CHM), which learns contextual information in a hierarchical framework for semantic segmentation. At each level of the hierarchy, a classifier is trained based on downsampled input images and outputs of previous levels. Our model then incorporates the resulting multi-resolution contextual information into a classifier to segment the input image at original resolution. This training strategy allows for optimization of a joint posterior probability at multiple resolutions through the hierarchy. Contextual hierarchical model is purely based on the input image patches and does not make use of any fragments or shape examples. Hence, it is applicable to a variety of problems such as object segmentation and edge detection. We demonstrate that CHM performs at par with state-of-the-art on Stanford background and Weizmann horse datasets. It also outperforms state-of-the-art edge detection methods on NYU depth dataset and achieves state-of-the-art on Berkeley segmentation dataset (BSDS 500).

Dual-Modality PET/Ultrasound imaging of the Prostate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huber, Jennifer S.; Moses, William W.; Pouliot, Jean

2005-11-11

Functional imaging with positron emission tomography (PET)will detect malignant tumors in the prostate and/or prostate bed, as well as possibly help determine tumor ''aggressiveness''. However, the relative uptake in a prostate tumor can be so great that few other anatomical landmarks are visible in a PET image. Ultrasound imaging with a transrectal probe provides anatomical detail in the prostate region that can be co-registered with the sensitive functional information from the PET imaging. Imaging the prostate with both PET and transrectal ultrasound (TRUS) will help determine the location of any cancer within the prostate region. This dual-modality imaging should helpmore » provide better detection and treatment of prostate cancer. LBNL has built a high performance positron emission tomograph optimized to image the prostate.Compared to a standard whole-body PET camera, our prostate-optimized PET camera has the same sensitivity and resolution, less backgrounds and lower cost. We plan to develop the hardware and software tools needed for a validated dual PET/TRUS prostate imaging system. We also plan to develop dual prostate imaging with PET and external transabdominal ultrasound, in case the TRUS system is too uncomfortable for some patients. We present the design and intended clinical uses for these dual imaging systems.« less

Review of Quantitative Ultrasound: Envelope Statistics and Backscatter Coefficient Imaging and Contributions to Diagnostic Ultrasound.

PubMed

Oelze, Michael L; Mamou, Jonathan

2016-02-01

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation, and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years, QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient (BSC), estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter (ESD) and the effective acoustic concentration (EAC) of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on

Review of quantitative ultrasound: envelope statistics and backscatter coefficient imaging and contributions to diagnostic ultrasound

PubMed Central

Oelze, Michael L.; Mamou, Jonathan

2017-01-01

Conventional medical imaging technologies, including ultrasound, have continued to improve over the years. For example, in oncology, medical imaging is characterized by high sensitivity, i.e., the ability to detect anomalous tissue features, but the ability to classify these tissue features from images often lacks specificity. As a result, a large number of biopsies of tissues with suspicious image findings are performed each year with a vast majority of these biopsies resulting in a negative finding. To improve specificity of cancer imaging, quantitative imaging techniques can play an important role. Conventional ultrasound B-mode imaging is mainly qualitative in nature. However, quantitative ultrasound (QUS) imaging can provide specific numbers related to tissue features that can increase the specificity of image findings leading to improvements in diagnostic ultrasound. QUS imaging techniques can encompass a wide variety of techniques including spectral-based parameterization, elastography, shear wave imaging, flow estimation and envelope statistics. Currently, spectral-based parameterization and envelope statistics are not available on most conventional clinical ultrasound machines. However, in recent years QUS techniques involving spectral-based parameterization and envelope statistics have demonstrated success in many applications, providing additional diagnostic capabilities. Spectral-based techniques include the estimation of the backscatter coefficient, estimation of attenuation, and estimation of scatterer properties such as the correlation length associated with an effective scatterer diameter and the effective acoustic concentration of scatterers. Envelope statistics include the estimation of the number density of scatterers and quantification of coherent to incoherent signals produced from the tissue. Challenges for clinical application include correctly accounting for attenuation effects and transmission losses and implementation of QUS on clinical

Video-based noncooperative iris image segmentation.

PubMed

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

Multispectral photoacoustic imaging of nerves with a clinical ultrasound system

NASA Astrophysics Data System (ADS)

Mari, Jean Martial; West, Simeon; Beard, Paul C.; Desjardins, Adrien E.

2014-03-01

Accurate and efficient identification of nerves is of great importance during many ultrasound-guided clinical procedures, including nerve blocks and prostate biopsies. It can be challenging to visualise nerves with conventional ultrasound imaging, however. One of the challenges is that nerves can have very similar appearances to nearby structures such as tendons. Several recent studies have highlighted the potential of near-infrared optical spectroscopy for differentiating nerves and adjacent tissues, as this modality can be sensitive to optical absorption of lipids that are present in intra- and extra-neural adipose tissue and in the myelin sheaths. These studies were limited to point measurements, however. In this pilot study, a custom photoacoustic system with a clinical ultrasound imaging probe was used to acquire multi-spectral photoacoustic images of nerves and tendons from swine ex vivo, across the wavelength range of 1100 to 1300 nm. Photoacoustic images were processed and overlaid in colour onto co-registered conventional ultrasound images that were acquired with the same imaging probe. A pronounced optical absorption peak centred at 1210 nm was observed in the photoacoustic signals obtained from nerves, and it was absent in those obtained from tendons. This absorption peak, which is consistent with the presence of lipids, provides a novel image contrast mechanism to significantly enhance the visualization of nerves. In particular, image contrast for nerves was up to 5.5 times greater with photoacoustic imaging (0.82 +/- 0.15) than with conventional ultrasound imaging (0.148 +/- 0.002), with a maximum contrast of 0.95 +/- 0.02 obtained in photoacoustic mode. This pilot study demonstrates the potential of photoacoustic imaging to improve clinical outcomes in ultrasound-guided interventions in regional anaesthesia and interventional oncology.

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

Fiber-Laser-Based Ultrasound Sensor for Photoacoustic Imaging

PubMed Central

Liang, Yizhi; Jin, Long; Wang, Lidai; Bai, Xue; Cheng, Linghao; Guan, Bai-Ou

2017-01-01

Photoacoustic imaging, especially for intravascular and endoscopic applications, requires ultrasound probes with miniature size and high sensitivity. In this paper, we present a new photoacoustic sensor based on a small-sized fiber laser. Incident ultrasound waves exert pressures on the optical fiber laser and induce harmonic vibrations of the fiber, which is detected by the frequency shift of the beating signal between the two orthogonal polarization modes in the fiber laser. This ultrasound sensor presents a noise-equivalent pressure of 40 Pa over a 50-MHz bandwidth. We demonstrate this new ultrasound sensor on an optical-resolution photoacoustic microscope. The axial and lateral resolutions are 48 μm and 3.3 μm. The field of view is up to 1.57 mm2. The sensor exhibits strong resistance to environmental perturbations, such as temperature changes, due to common-mode cancellation between the two orthogonal modes. The present fiber laser ultrasound sensor offers a new tool for all-optical photoacoustic imaging. PMID:28098201

Super-Resolution Image Reconstruction Applied to Medical Ultrasound

NASA Astrophysics Data System (ADS)

Ellis, Michael

Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in

Enhanced ultrasound for advanced diagnostics, ultrasound tomography for volume limb imaging and prosthetic fitting

NASA Astrophysics Data System (ADS)

Anthony, Brian W.

2016-04-01

Ultrasound imaging methods hold the potential to deliver low-cost, high-resolution, operator-independent and nonionizing imaging systems - such systems couple appropriate algorithms with imaging devices and techniques. The increasing demands on general practitioners motivate us to develop more usable and productive diagnostic imaging equipment. Ultrasound, specifically freehand ultrasound, is a low cost and safe medical imaging technique. It doesn't expose a patient to ionizing radiation. Its safety and versatility make it very well suited for the increasing demands on general practitioners, or for providing improved medical care in rural regions or the developing world. However it typically suffers from sonographer variability; we will discuss techniques to address user variability. We also discuss our work to combine cylindrical scanning systems with state of the art inversion algorithms to deliver ultrasound systems for imaging and quantifying limbs in 3-D in vivo. Such systems have the potential to track the progression of limb health at a low cost and without radiation exposure, as well as, improve prosthetic socket fitting. Current methods of prosthetic socket fabrication remain subjective and ineffective at creating an interface to the human body that is both comfortable and functional. Though there has been recent success using methods like magnetic resonance imaging and biomechanical modeling, a low-cost, streamlined, and quantitative process for prosthetic cup design and fabrication has not been fully demonstrated. Medical ultrasonography may inform the design process of prosthetic sockets in a more objective manner. This keynote talk presents the results of progress in this area.

Composite ultrasound imaging apparatus and method

DOEpatents

Morimoto, Alan K.; Bow, Jr., Wallace J.; Strong, David Scott; Dickey, Fred M.

1998-01-01

An imaging apparatus and method for use in presenting composite two dimensional and three dimensional images from individual ultrasonic frames. A cross-sectional reconstruction is applied by using digital ultrasound frames, transducer orientation and a known center. Motion compensation, rank value filtering, noise suppression and tissue classification are utilized to optimize the composite image.

Towards Automatic Image Segmentation Using Optimised Region Growing Technique

NASA Astrophysics Data System (ADS)

Alazab, Mamoun; Islam, Mofakharul; Venkatraman, Sitalakshmi

Image analysis is being adopted extensively in many applications such as digital forensics, medical treatment, industrial inspection, etc. primarily for diagnostic purposes. Hence, there is a growing interest among researches in developing new segmentation techniques to aid the diagnosis process. Manual segmentation of images is labour intensive, extremely time consuming and prone to human errors and hence an automated real-time technique is warranted in such applications. There is no universally applicable automated segmentation technique that will work for all images as the image segmentation is quite complex and unique depending upon the domain application. Hence, to fill the gap, this paper presents an efficient segmentation algorithm that can segment a digital image of interest into a more meaningful arrangement of regions and objects. Our algorithm combines region growing approach with optimised elimination of false boundaries to arrive at more meaningful segments automatically. We demonstrate this using X-ray teeth images that were taken for real-life dental diagnosis.

A Review on Segmentation of Positron Emission Tomography Images

PubMed Central

Foster, Brent; Bagci, Ulas; Mansoor, Awais; Xu, Ziyue; Mollura, Daniel J.

2014-01-01

Positron Emission Tomography (PET), a non-invasive functional imaging method at the molecular level, images the distribution of biologically targeted radiotracers with high sensitivity. PET imaging provides detailed quantitative information about many diseases and is often used to evaluate inflammation, infection, and cancer by detecting emitted photons from a radiotracer localized to abnormal cells. In order to differentiate abnormal tissue from surrounding areas in PET images, image segmentation methods play a vital role; therefore, accurate image segmentation is often necessary for proper disease detection, diagnosis, treatment planning, and follow-ups. In this review paper, we present state-of-the-art PET image segmentation methods, as well as the recent advances in image segmentation techniques. In order to make this manuscript self-contained, we also briefly explain the fundamentals of PET imaging, the challenges of diagnostic PET image analysis, and the effects of these challenges on the segmentation results. PMID:24845019

Imaging of Groin Pain: Magnetic Resonance and Ultrasound Imaging Features.

PubMed

Lee, Susan C; Endo, Yoshimi; Potter, Hollis G

Evaluation of groin pain in athletes may be challenging as pain is typically poorly localized and the pubic symphyseal region comprises closely approximated tendons and muscles. As such, magnetic resonance imaging (MRI) and ultrasound (US) may help determine the etiology of groin pain. A PubMed search was performed using the following search terms: ultrasound, magnetic resonance imaging, sports hernia, athletic pubalgia, and groin pain. Date restrictions were not placed on the literature search. Clinical review. Level 4. MRI is sensitive in diagnosing pathology in groin pain. Not only can MRI be used to image rectus abdominis/adductor longus aponeurosis and pubic bone pathology, but it can also evaluate other pathology within the hip and pelvis. MRI is especially helpful when groin pain is poorly localized. Real-time capability makes ultrasound useful in evaluating the pubic symphyseal region, as it can be used for evaluation and treatment. MRI and US are valuable in diagnosing pathology in athletes with groin pain, with the added utility of treatment using US-guided intervention. Strength-of Recommendation Taxonomy: C.

Multifractal-based nuclei segmentation in fish images.

PubMed

Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

2017-09-01

The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

Nonlocal means-based speckle filtering for ultrasound images

PubMed Central

Coupé, Pierrick; Hellier, Pierre; Kervrann, Charles; Barillot, Christian

2009-01-01

In image processing, restoration is expected to improve the qualitative inspection of the image and the performance of quantitative image analysis techniques. In this paper, an adaptation of the Non Local (NL-) means filter is proposed for speckle reduction in ultrasound (US) images. Originally developed for additive white Gaussian noise, we propose to use a Bayesian framework to derive a NL-means filter adapted to a relevant ultrasound noise model. Quantitative results on synthetic data show the performances of the proposed method compared to well-established and state-of-the-art methods. Results on real images demonstrate that the proposed method is able to preserve accurately edges and structural details of the image. PMID:19482578

Graph run-length matrices for histopathological image segmentation.

PubMed

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

The histopathological examination of tissue specimens is essential for cancer diagnosis and grading. However, this examination is subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run-length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from "graph run-length matrices" lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more effective in histopathological image segmentation.

Limited angle breast ultrasound tomography with a priori information and artifact removal

NASA Astrophysics Data System (ADS)

Jintamethasawat, Rungroj; Zhu, Yunhao; Kripfgans, Oliver D.; Yuan, Jie; Goodsitt, Mitchell M.; Carson, Paul L.

2017-03-01

In B-mode images from dual-sided ultrasound, it has been shown that by delineating structures suspected of being relatively homogeneous, one can enhance limited angle tomography to produce speed of sound images in the same view as X-ray Digital Breast Tomography (DBT). This could allow better breast cancer detection and discrimination, as well as improved registration of the ultrasound and X-ray images, because of the similarity of SOS and X-ray contrast in the breast. However, this speed of sound reconstruction method relies strongly on B-mode or other reflection mode segmentation. If that information is limited or incorrect, artifacts will appear in the reconstructed images. Therefore, the iterative speed of sound reconstruction algorithm has been modified in a manner of simultaneously utilizing the image segmentations and removing most artifacts. The first step of incorporating a priori information is solved by any nonlinearnonconvex optimization method while artifact removal is accomplished by employing the fast split Bregman method to perform total-variation (TV) regularization for image denoising. The proposed method was demonstrated in simplified simulations of our dual-sided ultrasound scanner. To speed these computations two opposed 40-element ultrasound linear arrays with 0.5 MHz center frequency were simulated for imaging objects in a uniform background. The proposed speed of sound reconstruction method worked well with both bent-ray and full-wave inversion methods. This is also the first demonstration of successful full-wave medical ultrasound tomography in the limited angle geometry. Presented results lend credibility to a possible translation of this method to clinical breast imaging.

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

MO-AB-210-02: Ultrasound Imaging and Therapy-Hands On Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sammet, S.

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrationsmore » with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant

MO-AB-210-01: Ultrasound Imaging and Therapy-Hands On Workshop

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Z.

The goal of this ultrasound hands-on workshop is to demonstrate advancements in high intensity focused ultrasound (HIFU) and to demonstrate quality control (QC) testing in diagnostic ultrasound. HIFU is a therapeutic modality that uses ultrasound waves as carriers of energy. HIFU is used to focus a beam of ultrasound energy into a small volume at specific target locations within the body. The focused beam causes localized high temperatures and produces a well-defined regions of necrosis. This completely non-invasive technology has great potential for tumor ablation and targeted drug delivery. At the workshop, attendees will see configurations, applications, and hands-on demonstrationsmore » with on-site instructors at separate stations. The involvement of medical physicists in diagnostic ultrasound imaging service is increasing due to QC and accreditation requirements. At the workshop, an array of ultrasound testing phantoms and ultrasound scanners will be provided for attendees to learn diagnostic ultrasound QC in a hands-on environment with live demonstrations of the techniques. Target audience: Medical physicists and other medical professionals in diagnostic imaging and radiation oncology with interest in high-intensity focused ultrasound and in diagnostic ultrasound QC. Learning Objectives: Learn ultrasound physics and safety for HIFU applications through live demonstrations Get an overview of the state-of-the art in HIFU technologies and equipment Gain familiarity with common elements of a quality control program for diagnostic ultrasound imaging Identify QC tools available for testing diagnostic ultrasound systems and learn how to use these tools List of supporting vendors for HIFU and diagnostic ultrasound QC hands-on workshop: Philips Healthcare Alpinion Medical Systems Verasonics, Inc Zonare Medical Systems, Inc Computerized Imaging Reference Systems (CIRS), Inc. GAMMEX, Inc., Cablon Medical BV Steffen Sammet: NIH/NCI grant 5R25CA132822, NIH/NINDS grant

Composite ultrasound imaging apparatus and method

DOEpatents

Morimoto, A.K.; Bow, W.J. Jr.; Strong, D.S.; Dickey, F.M.

1998-09-15

An imaging apparatus and method for use in presenting composite two dimensional and three dimensional images from individual ultrasonic frames. A cross-sectional reconstruction is applied by using digital ultrasound frames, transducer orientation and a known center. Motion compensation, rank value filtering, noise suppression and tissue classification are utilized to optimize the composite image. 37 figs.

Real-time evaluation of diffusion of the local anesthetic solution during peribulbar block using ultrasound imaging and clinical correlates of diffusion.

PubMed

Luyet, Cédric; Eng, Kenneth T; Kertes, Peter J; Avila, Arsenio; Muni, Rajeev H; McHardy, Paul

2012-01-01

The aims of this prospective observational study were to assess the incidence of intraconal spread during peribulbar (extraconal) anesthesia by real-time ultrasound imaging of the retro-orbital compartment and to determine whether a complete sensory and motor block (with akinesia) of the eye is directly related to the intraconal spread. Ultrasound imaging was performed in 100 patients who underwent a surgical procedure on the posterior segment of the eye. All patients received a peribulbar block using the inferolateral approach. Once the needle was in place, a linear ultrasound transducer was placed over the eyelid and the spread of local anesthetics was assessed during the injection (real time). Akinesia was assessed by a blinded observer 10 minutes after block placement. The incidence of intraconal spread and its correlation with a complete akinesia was measured. The overall block failure rate was 28% in terms of akinesia, and the rate of rescue blocks was 20%. Clear intraconal spread during injection of the local anesthetic mixture could be detected with ultrasound imaging in 61 of 100 patients. The positive predictive value for successful block when intraconal spread was detected was 98% (95% confidence interval, 91%-100%). The association between clear and no evidence of intraconal spread and effective block was statistically significant (χ test, P < 0.001). Ultrasound imaging provides information of local anesthetic spread within the retro-orbital space, which might assist in the prediction of block success.

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Segmentation Fusion Techniques with Application to Plenoptic Images: A Survey.

NASA Astrophysics Data System (ADS)

Evin, D.; Hadad, A.; Solano, A.; Drozdowicz, B.

2016-04-01

The segmentation of anatomical and pathological structures plays a key role in the characterization of clinically relevant evidence from digital images. Recently, plenoptic imaging has emerged as a new promise to enrich the diagnostic potential of conventional photography. Since the plenoptic images comprises a set of slightly different versions of the target scene, we propose to make use of those images to improve the segmentation quality in relation to the scenario of a single image segmentation. The problem of finding a segmentation solution from multiple images of a single scene, is called segmentation fusion. This paper reviews the issue of segmentation fusion in order to find solutions that can be applied to plenoptic images, particularly images from the ophthalmological domain.

Cumulative phase delay imaging - A new contrast enhanced ultrasound modality

NASA Astrophysics Data System (ADS)

Demi, Libertario; van Sloun, Ruud J. G.; Wijkstra, Hessel; Mischi, Massimo

2015-10-01

Recently, a new acoustic marker for ultrasound contrast agents (UCAs) has been introduced. A cumulative phase delay (CPD) between the second harmonic and fundamental pressure wave field components is in fact observable for ultrasound propagating through UCAs. This phenomenon is absent in the case of tissue nonlinearity and is dependent on insonating pressure and frequency, UCA concentration, and propagation path length through UCAs. In this paper, ultrasound images based on this marker are presented. The ULA-OP research platform, in combination with a LA332 linear array probe (Esaote, Firenze Italy), were used to image a gelatin phantom containing a PVC plate (used as a reflector) and a cylindrical cavity measuring 7 mm in diameter (placed in between the observation point and the PVC plate). The cavity contained a 240 µL/L SonoVueO® UCA concentration. Two insonating frequencies (3 MHz and 2.5 MHz) were used to scan the gelatine phantom. A mechanical index MI = 0.07, measured in water at the cavity location with a HGL-0400 hydrophone (Onda, Sunnyvale, CA), was utilized. Processing the ultrasound signals backscattered from the plate, ultrasound images were generated in a tomographic fashion using the filtered back-projection method. As already observed in previous studies, significantly higher CPD values are measured when imaging at a frequency of 2.5 MHz, as compared to imaging at 3 MHz. In conclusion, these results confirm the applicability of the discussed CPD as a marker for contrast imaging. Comparison with standard contrast-enhanced ultrasound imaging modalities will be the focus of future work.

A Guide to Analysing Tongue Motion from Ultrasound Images

ERIC Educational Resources Information Center

Stone, Maureen

2005-01-01

This paper is meant to be an introduction to and general reference for ultrasound imaging for new and moderately experienced users of the instrument. The paper consists of eight sections. The first explains how ultrasound works, including beam properties, scan types and machine features. The second section discusses image quality, including the…

Handheld probe for portable high frame photoacoustic/ultrasound imaging system

NASA Astrophysics Data System (ADS)

Daoudi, K.; van den Berg, P. J.; Rabot, O.; Kohl, A.; Tisserand, S.; Brands, P.; Steenbergen, W.

2013-03-01

Photoacoustics is a hybrid imaging modality that is based on the detection of acoustic waves generated by absorption of pulsed light by tissue chromophors. In current research, this technique uses large and costly photoacoustic systems with a low frame rate imaging. To open the door for widespread clinical use, a compact, cost effective and fast system is required. In this paper we report on the development of a small compact handset pulsed laser probe which will be connected to a portable ultrasound system for real-time photoacoustic imaging and ultrasound imaging. The probe integrates diode lasers driven by an electrical driver developed for very short high power pulses. It uses specifically developed highly efficient diode stacks with high frequency repetition rate up to 10 kHz, emitting at 800nm wavelength. The emitted beam is collimated and shaped with compact micro optics beam shaping system delivering a homogenized rectangular laser beam intensity distribution. The laser block is integrated with an ultrasound transducer in an ergonomically designed handset probe. This handset is a building block enabling for a low cost high frame rate photoacoustic and ultrasound imaging system. The probe was used with a modified ultrasound scanner and was tested by imaging a tissue mimicking phantom.

Nanobubble-Affibody: Novel ultrasound contrast agents for targeted molecular ultrasound imaging of tumor.

PubMed

Yang, Hengli; Cai, Wenbin; Xu, Lei; Lv, Xiuhua; Qiao, Youbei; Li, Pan; Wu, Hong; Yang, Yilin; Zhang, Li; Duan, Yunyou

2015-01-01

Nanobubbles (NBs), as novel ultrasound contrast agents (UCAs), have attracted increasing attention in the field of molecular ultrasound imaging for tumors. However, the preparation of uniform-sized NBs is considered to be controversial, and poor tumor selectivity in in vivo imaging has been reported. In this study, we fabricated uniform nano-sized NBs (478.2 ± 29.7 nm with polydispersity index of 0.164 ± 0.044, n = 3) using a thin-film hydration method by controlling the thickness of phospholipid films; we then conjugated the NBs with Affibody molecules to produce nano-sized UCAs referred to as NB-Affibody with specific affinity to human epidermal growth factor receptor type 2 (HER2)-overexpressing tumors. NB-Affibody presented good ultrasound enhancement, demonstrating a peak intensity of 104.5 ± 2.1 dB under ultrasound contrast scanning. Ex vivo experiments further confirmed that the NB-Affibody conjugates were capable of targeting HER2-expressing tumor cells in vivo with high affinity. The newly prepared nano-sized NB-Affibody conjugates were observed to be novel targeted UCAs for efficient and safe specific molecular imaging and may have potential applications in early cancer quantitative diagnosis and targeted therapy in the future. Copyright © 2014 Elsevier Ltd. All rights reserved.

Comparison of portable and conventional ultrasound imaging in spinal curvature measurement

NASA Astrophysics Data System (ADS)

Yan, Christina; Tabanfar, Reza; Kempston, Michael; Borschneck, Daniel; Ungi, Tamas; Fichtinger, Gabor

2016-03-01

PURPOSE: In scoliosis monitoring, tracked ultrasound has been explored as a safer imaging alternative to traditional radiography. The use of ultrasound in spinal curvature measurement requires identification of vertebral landmarks, but bones have reduced visibility in ultrasound imaging and high quality ultrasound machines are often expensive and not portable. In this work, we investigate the image quality and measurement accuracy of a low cost and portable ultrasound machine in comparison to a standard ultrasound machine in scoliosis monitoring. METHODS: Two different kinds of ultrasound machines were tested on three human subjects, using the same position tracker and software. Spinal curves were measured in the same reference coordinate system using both ultrasound machines. Lines were defined by connecting two symmetric landmarks identified on the left and right transverse process of the same vertebrae, and spinal curvature was defined as the transverse process angle between two such lines, projected on the coronal plane. RESULTS: Three healthy volunteers were scanned by both ultrasound configurations. Three experienced observers localized transverse processes as skeletal landmarks and obtained transverse process angles in images obtained from both ultrasounds. The mean difference per transverse process angle measured was 3.00 +/-2.1°. 94% of transverse processes visualized in the Sonix Touch were also visible in the Telemed. Inter-observer error in the Telemed was 4.5° and 4.3° in the Sonix Touch. CONCLUSION: Price, convenience and accessibility suggest the Telemed to be a viable alternative in scoliosis monitoring, however further improvements in measurement protocol and image noise reduction must be completed before implementing the Telemed in the clinical setting.