A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

On the Relationship between Variational Level Set-Based and SOM-Based Active Contours

PubMed Central

Abdelsamea, Mohammed M.; Gnecco, Giorgio; Gaber, Mohamed Medhat; Elyan, Eyad

2015-01-01

Most Active Contour Models (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an active contour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an active contour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

A visual model for object detection based on active contours and level-set method.

PubMed

Satoh, Shunji

2006-09-01

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation. One drawback involved with initial values of active contours is alleviated by introducing and formulating convexity, which is a visual property. Numerical experiments show that the proposed model detects objects with complex topologies and that it is tolerant of noise. A visual attention model is introduced into the proposed model. Other simulations show that the visual properties of the model are consistent with the results of psychological experiments that disclose the relation between figure-ground reversal and visual attention. We also demonstrate that the model tends to perceive smaller regions as figures, which is a characteristic observed in human visual perception.

Automated breast segmentation in ultrasound computer tomography SAFT images

NASA Astrophysics Data System (ADS)

Hopp, T.; You, W.; Zapf, M.; Tan, W. Y.; Gemmeke, H.; Ruiter, N. V.

2017-03-01

Ultrasound Computer Tomography (USCT) is a promising new imaging system for breast cancer diagnosis. An essential step before further processing is to remove the water background from the reconstructed images. In this paper we present a fully-automated image segmentation method based on three-dimensional active contours. The active contour method is extended by applying gradient vector flow and encoding the USCT aperture characteristics as additional weighting terms. A surface detection algorithm based on a ray model is developed to initialize the active contour, which is iteratively deformed to capture the breast outline in USCT reflection images. The evaluation with synthetic data showed that the method is able to cope with noisy images, and is not influenced by the position of the breast and the presence of scattering objects within the breast. The proposed method was applied to 14 in-vivo images resulting in an average surface deviation from a manual segmentation of 2.7 mm. We conclude that automated segmentation of USCT reflection images is feasible and produces results comparable to a manual segmentation. By applying the proposed method, reproducible segmentation results can be obtained without manual interaction by an expert.

Ingenious Snake: An Adaptive Multi-Class Contours Extraction

NASA Astrophysics Data System (ADS)

Li, Baolin; Zhou, Shoujun

2018-04-01

Active contour model (ACM) plays an important role in computer vision and medical image application. The traditional ACMs were used to extract single-class of object contours. While, simultaneous extraction of multi-class of interesting contours (i.e., various contours with closed- or open-ended) have not been solved so far. Therefore, a novel ACM model named “Ingenious Snake” is proposed to adaptively extract these interesting contours. In the first place, the ridge-points are extracted based on the local phase measurement of gradient vector flow field; the consequential ridgelines initialization are automated with high speed. Secondly, the contours’ deformation and evolvement are implemented with the ingenious snake. In the experiments, the result from initialization, deformation and evolvement are compared with the existing methods. The quantitative evaluation of the structure extraction is satisfying with respect of effectiveness and accuracy.

An adaptive multi-feature segmentation model for infrared image

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Han, Jin; Zhang, Yi; Bai, Lianfa

2016-04-01

Active contour models (ACM) have been extensively applied to image segmentation, conventional region-based active contour models only utilize global or local single feature information to minimize the energy functional to drive the contour evolution. Considering the limitations of original ACMs, an adaptive multi-feature segmentation model is proposed to handle infrared images with blurred boundaries and low contrast. In the proposed model, several essential local statistic features are introduced to construct a multi-feature signed pressure function (MFSPF). In addition, we draw upon the adaptive weight coefficient to modify the level set formulation, which is formed by integrating MFSPF with local statistic features and signed pressure function with global information. Experimental results demonstrate that the proposed method can make up for the inadequacy of the original method and get desirable results in segmenting infrared images.

Active mask segmentation of fluorescence microscope images.

PubMed

Srinivasa, Gowri; Fickus, Matthew C; Guo, Yusong; Linstedt, Adam D; Kovacević, Jelena

2009-08-01

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

Generalized Newton Method for Energy Formulation in Image Processing

DTIC Science & Technology

2008-04-01

A. Brook, N. Sochen, and N. Kiryati. Deblurring of color images corrupted by impulsive noise . IEEE Transactions on Image Processing, 16(4):1101–1111...tive functionals: variational image deblurring and geodesic active contours for image segmentation. We show that in addition to the fast convergence...inner product, active contours, deblurring . AMS subject classifications. 35A15, 65K10, 90C53 1. Introduction. Optimization of a cost functional is a

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.

MRI segmentation by active contours model, 3D reconstruction, and visualization

NASA Astrophysics Data System (ADS)

Lopez-Hernandez, Juan M.; Velasquez-Aguilar, J. Guadalupe

2005-02-01

The advances in 3D data modelling methods are becoming increasingly popular in the areas of biology, chemistry and medical applications. The Nuclear Magnetic Resonance Imaging (NMRI) technique has progressed at a spectacular rate over the past few years, its uses have been spread over many applications throughout the body in both anatomical and functional investigations. In this paper we present the application of Zernike polynomials for 3D mesh model of the head using the contour acquired of cross-sectional slices by active contour model extraction and we propose the visualization with OpenGL 3D Graphics of the 2D-3D (slice-surface) information for the diagnostic aid in medical applications.

Iconic memory-based omnidirectional route panorama navigation.

PubMed

Yagi, Yasushi; Imai, Kousuke; Tsuji, Kentaro; Yachida, Masahiko

2005-01-01

A route navigation method for a mobile robot with an omnidirectional image sensor is described. The route is memorized from a series of consecutive omnidirectional images of the horizon when the robot moves to its goal. While the robot is navigating to the goal point, input is matched against the memorized spatio-temporal route pattern by using dual active contour models and the exact robot position and orientation is estimated from the converged shape of the active contour models.

Gallbladder shape extraction from ultrasound images using active contour models.

PubMed

Ciecholewski, Marcin; Chochołowicz, Jakub

2013-12-01

Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

Dissociable neural correlates of contour completion and contour representation in illusory contour perception.

PubMed

Wu, Xiang; He, Sheng; Bushara, Khalaf; Zeng, Feiyan; Liu, Ying; Zhang, Daren

2012-10-01

Object recognition occurs even when environmental information is incomplete. Illusory contours (ICs), in which a contour is perceived though the contour edges are incomplete, have been extensively studied as an example of such a visual completion phenomenon. Despite the neural activity in response to ICs in visual cortical areas from low (V1 and V2) to high (LOC: the lateral occipital cortex) levels, the details of the neural processing underlying IC perception are largely not clarified. For example, how do the visual areas function in IC perception and how do they interact to archive the coherent contour perception? IC perception involves the process of completing the local discrete contour edges (contour completion) and the process of representing the global completed contour information (contour representation). Here, functional magnetic resonance imaging was used to dissociate contour completion and contour representation by varying each in opposite directions. The results show that the neural activity was stronger to stimuli with more contour completion than to stimuli with more contour representation in V1 and V2, which was the reverse of that in the LOC. When inspecting the neural activity change across the visual pathway, the activation remained high for the stimuli with more contour completion and increased for the stimuli with more contour representation. These results suggest distinct neural correlates of contour completion and contour representation, and the possible collaboration between the two processes during IC perception, indicating a neural connection between the discrete retinal input and the coherent visual percept. Copyright © 2011 Wiley Periodicals, Inc.

Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.

PubMed

Li, Bin; Chen, Kan; Tian, Lianfang; Yeboah, Yao; Ou, Shanxing

2013-01-01

The segmentation and detection of various types of nodules in a Computer-aided detection (CAD) system present various challenges, especially when (1) the nodule is connected to a vessel and they have very similar intensities; (2) the nodule with ground-glass opacity (GGO) characteristic possesses typical weak edges and intensity inhomogeneity, and hence it is difficult to define the boundaries. Traditional segmentation methods may cause problems of boundary leakage and "weak" local minima. This paper deals with the above mentioned problems. An improved detection method which combines a fuzzy integrated active contour model (FIACM)-based segmentation method, a segmentation refinement method based on Parametric Mixture Model (PMM) of juxta-vascular nodules, and a knowledge-based C-SVM (Cost-sensitive Support Vector Machines) classifier, is proposed for detecting various types of pulmonary nodules in computerized tomography (CT) images. Our approach has several novel aspects: (1) In the proposed FIACM model, edge and local region information is incorporated. The fuzzy energy is used as the motivation power for the evolution of the active contour. (2) A hybrid PMM Model of juxta-vascular nodules combining appearance and geometric information is constructed for segmentation refinement of juxta-vascular nodules. Experimental results of detection for pulmonary nodules show desirable performances of the proposed method.

Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

Automatic media-adventitia IVUS image segmentation based on sparse representation framework and dynamic directional active contour model.

PubMed

Zakeri, Fahimeh Sadat; Setarehdan, Seyed Kamaledin; Norouzi, Somayye

2017-10-01

Segmentation of the arterial wall boundaries from intravascular ultrasound images is an important image processing task in order to quantify arterial wall characteristics such as shape, area, thickness and eccentricity. Since manual segmentation of these boundaries is a laborious and time consuming procedure, many researchers attempted to develop (semi-) automatic segmentation techniques as a powerful tool for educational and clinical purposes in the past but as yet there is no any clinically approved method in the market. This paper presents a deterministic-statistical strategy for automatic media-adventitia border detection by a fourfold algorithm. First, a smoothed initial contour is extracted based on the classification in the sparse representation framework which is combined with the dynamic directional convolution vector field. Next, an active contour model is utilized for the propagation of the initial contour toward the interested borders. Finally, the extracted contour is refined in the leakage, side branch openings and calcification regions based on the image texture patterns. The performance of the proposed algorithm is evaluated by comparing the results to those manually traced borders by an expert on 312 different IVUS images obtained from four different patients. The statistical analysis of the results demonstrates the efficiency of the proposed method in the media-adventitia border detection with enough consistency in the leakage and calcification regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Pulmonary parenchyma segmentation in thin CT image sequences with spectral clustering and geodesic active contour model based on similarity

NASA Astrophysics Data System (ADS)

He, Nana; Zhang, Xiaolong; Zhao, Juanjuan; Zhao, Huilan; Qiang, Yan

2017-07-01

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic active contour model that is geodesic active contour model based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

Generic and robust method for automatic segmentation of PET images using an active contour model

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

Zhuang, Mingzan

Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an active contour model, incorporates the histogrammore » fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work with good accuracy, resulting in a mean RE of −13.35% ± 11.87% and −11.15% ± 23.66%, a mean DSC of 0.89 ± 0.05 and 0.71 ± 0.09, and a mean CE of 19.19% ± 7.89% and 53.92% ± 12.65%, for PSs and CSs, respectively. Conclusions: The authors’ results demonstrate that the developed novel PET segmentation algorithm is applicable to various types of lesions in the authors’ study and is capable of producing accurate and consistent target volume delineations, potentially resulting in reduced intraobserver and interobserver variabilities observed when using manual delineation and improved accuracy in treatment planning and outcome evaluation.« less

Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

NASA Astrophysics Data System (ADS)

León, Madeleine; Escalante-Ramirez, Boris

2013-11-01

Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

Significant body point labeling and tracking.

PubMed

Azhar, Faisal; Tjahjadi, Tardi

2014-09-01

In this paper, a method is presented to label and track anatomical landmarks (e.g., head, hand/arm, feet), which are referred to as significant body points (SBPs), using implicit body models. By considering the human body as an inverted pendulum model, ellipse fitting and contour moments are applied to classify it as being in Stand, Sit, or Lie posture. A convex hull of the silhouette contour is used to determine the locations of SBPs. The particle filter or a motion flow-based method is used to predict SBPs in occlusion. Stick figures of various activities are generated by connecting the SBPs. The qualitative and quantitative evaluation show that the proposed method robustly labels and tracks SBPs in various activities of two different (low and high) resolution data sets.

Automatic Contour Extraction of Facial Organs for Frontal Facial Images with Various Facial Expressions

NASA Astrophysics Data System (ADS)

Kobayashi, Hiroshi; Suzuki, Seiji; Takahashi, Hisanori; Tange, Akira; Kikuchi, Kohki

This study deals with a method to realize automatic contour extraction of facial features such as eyebrows, eyes and mouth for the time-wise frontal face with various facial expressions. Because Snakes which is one of the most famous methods used to extract contours, has several disadvantages, we propose a new method to overcome these issues. We define the elastic contour model in order to hold the contour shape and then determine the elastic energy acquired by the amount of modification of the elastic contour model. Also we utilize the image energy obtained by brightness differences of the control points on the elastic contour model. Applying the dynamic programming method, we determine the contour position where the total value of the elastic energy and the image energy becomes minimum. Employing 1/30s time-wise facial frontal images changing from neutral to one of six typical facial expressions obtained from 20 subjects, we have estimated our method and find it enables high accuracy automatic contour extraction of facial features.

Automated segmentation of ultrasonic breast lesions using statistical texture classification and active contour based on probability distance.

PubMed

Liu, Bo; Cheng, H D; Huang, Jianhua; Tian, Jiawei; Liu, Jiafeng; Tang, Xianglong

2009-08-01

Because of its complicated structure, low signal/noise ratio, low contrast and blurry boundaries, fully automated segmentation of a breast ultrasound (BUS) image is a difficult task. In this paper, a novel segmentation method for BUS images without human intervention is proposed. Unlike most published approaches, the proposed method handles the segmentation problem by using a two-step strategy: ROI generation and ROI segmentation. First, a well-trained texture classifier categorizes the tissues into different classes, and the background knowledge rules are used for selecting the regions of interest (ROIs) from them. Second, a novel probability distance-based active contour model is applied for segmenting the ROIs and finding the accurate positions of the breast tumors. The active contour model combines both global statistical information and local edge information, using a level set approach. The proposed segmentation method was performed on 103 BUS images (48 benign and 55 malignant). To validate the performance, the results were compared with the corresponding tumor regions marked by an experienced radiologist. Three error metrics, true-positive ratio (TP), false-negative ratio (FN) and false-positive ratio (FP) were used for measuring the performance of the proposed method. The final results (TP = 91.31%, FN = 8.69% and FP = 7.26%) demonstrate that the proposed method can segment BUS images efficiently, quickly and automatically.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Random walk and graph cut based active contour model for three-dimension interactive pituitary adenoma segmentation from MR images

NASA Astrophysics Data System (ADS)

Sun, Min; Chen, Xinjian; Zhang, Zhiqiang; Ma, Chiyuan

2017-02-01

Accurate volume measurements of pituitary adenoma are important to the diagnosis and treatment for this kind of sellar tumor. The pituitary adenomas have different pathological representations and various shapes. Particularly, in the case of infiltrating to surrounding soft tissues, they present similar intensities and indistinct boundary in T1-weighted (T1W) magnetic resonance (MR) images. Then the extraction of pituitary adenoma from MR images is still a challenging task. In this paper, we propose an interactive method to segment the pituitary adenoma from brain MR data, by combining graph cuts based active contour model (GCACM) and random walk algorithm. By using the GCACM method, the segmentation task is formulated as an energy minimization problem by a hybrid active contour model (ACM), and then the problem is solved by the graph cuts method. The region-based term in the hybrid ACM considers the local image intensities as described by Gaussian distributions with different means and variances, expressed as maximum a posteriori probability (MAP). Random walk is utilized as an initialization tool to provide initialized surface for GCACM. The proposed method is evaluated on the three-dimensional (3-D) T1W MR data of 23 patients and compared with the standard graph cuts method, the random walk method, the hybrid ACM method, a GCACM method which considers global mean intensity in region forces, and a competitive region-growing based GrowCut method planted in 3D Slicer. Based on the experimental results, the proposed method is superior to those methods.

Breast masses in mammography classification with local contour features.

PubMed

Li, Haixia; Meng, Xianjing; Wang, Tingwen; Tang, Yuchun; Yin, Yilong

2017-04-14

Mammography is one of the most popular tools for early detection of breast cancer. Contour of breast mass in mammography is very important information to distinguish benign and malignant mass. Contour of benign mass is smooth and round or oval, while malignant mass has irregular shape and spiculated contour. Several studies have shown that 1D signature translated from 2D contour can describe the contour features well. In this paper, we propose a new method to translate 2D contour of breast mass in mammography into 1D signature. The method can describe not only the contour features but also the regularity of breast mass. Then we segment the whole 1D signature into different subsections. We extract four local features including a new contour descriptor from the subsections. The new contour descriptor is root mean square (RMS) slope. It can describe the roughness of the contour. KNN, SVM and ANN classifier are used to classify benign breast mass and malignant mass. The proposed method is tested on a set with 323 contours including 143 benign masses and 180 malignant ones from digital database of screening mammography (DDSM). The best accuracy of classification is 99.66% using the feature of root mean square slope with SVM classifier. The performance of the proposed method is better than traditional method. In addition, RMS slope is an effective feature comparable to most of the existing features.

Segmenting the thoracic, abdominal and pelvic musculature on CT scans combining atlas-based model and active contour model

NASA Astrophysics Data System (ADS)

Zhang, Weidong; Liu, Jiamin; Yao, Jianhua; Summers, Ronald M.

2013-03-01

Segmentation of the musculature is very important for accurate organ segmentation, analysis of body composition, and localization of tumors in the muscle. In research fields of computer assisted surgery and computer-aided diagnosis (CAD), muscle segmentation in CT images is a necessary pre-processing step. This task is particularly challenging due to the large variability in muscle structure and the overlap in intensity between muscle and internal organs. This problem has not been solved completely, especially for all of thoracic, abdominal and pelvic regions. We propose an automated system to segment the musculature on CT scans. The method combines an atlas-based model, an active contour model and prior segmentation of fat and bones. First, body contour, fat and bones are segmented using existing methods. Second, atlas-based models are pre-defined using anatomic knowledge at multiple key positions in the body to handle the large variability in muscle shape. Third, the atlas model is refined using active contour models (ACM) that are constrained using the pre-segmented bone and fat. Before refining using ACM, the initialized atlas model of next slice is updated using previous atlas. The muscle is segmented using threshold and smoothed in 3D volume space. Thoracic, abdominal and pelvic CT scans were used to evaluate our method, and five key position slices for each case were selected and manually labeled as the reference. Compared with the reference ground truth, the overlap ratio of true positives is 91.1%+/-3.5%, and that of false positives is 5.5%+/-4.2%.

Fourier descriptor analysis and unification of voice range profile contours: method and applications.

PubMed

Pabon, Peter; Ternström, Sten; Lamarche, Anick

2011-06-01

To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the contour, is assessed and also is compared to density-based VRP averaging methods that use the overlap count. VRP contours can be usefully described and compared using FDs. The method also permits the visualization of the local covariation along the contour average. For example, the FD-based analysis shows that the population variance for ensembles of VRP contours is usually smallest at the upper left part of the VRP. To illustrate the method's advantages and possible further application, graphs are given that compare the averaged contours from different authors and recording devices--for normal, trained, and untrained male and female voices as well as for child voices. The proposed technique allows any VRP shape to be brought to the same uniform base. On this uniform base, VRP contours or contour elements coming from a variety of sources may be placed within the same graph for comparison and for statistical analysis.

Active Contours for Multispectral Images With Non-Homogeneous Sub-Regions

DTIC Science & Technology

2005-09-16

Marching Methods. Cambridge Monographs on Applied and Computational Mathematics, Cambridge University Press, 2nd ed., 1999. [76] R . Malladi and J. Sethian...F. Dibos, “A geometric model for active contours,” Numerische Mathematik, p. 19, 1993. [80] R . Malladi , J. Sethian, and C. Vemuri, “Shape modeling... Malladi et al. [80, 76] proposed a similar model given by ∂φ(x, y) ∂t = g(I(x, y))(κ(φ(x, y)) + ν)|∇φ(x, y)|, (3.14) where g(·) : Ω → < denotes the

Automated method and system for the alignment and correlation of images from two different modalities

DOEpatents

Giger, Maryellen L.; Chen, Chin-Tu; Armato, Samuel; Doi, Kunio

1999-10-26

A method and system for the computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax. Techniques include contouring the lung regions in each type of chest image, scaling and registration of the contours based on location of lung apices, and superimposition after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lungs scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs. Final output could be the computer-determined contours from each type of image superimposed on any of the original images, or superimposition of the radionuclide image data, which contains high activity, onto the radiographic chest image.

Contour-based image warping

NASA Astrophysics Data System (ADS)

Chan, Kwai H.; Lau, Rynson W.

1996-09-01

Image warping concerns about transforming an image from one spatial coordinate to another. It is widely used for the vidual effect of deforming and morphing images in the film industry. A number of warping techniques have been introduced, which are mainly based on the corresponding pair mapping of feature points, feature vectors or feature patches (mostly triangular or quadrilateral). However, very often warping of an image object with an arbitrary shape is required. This requires a warping technique which is based on boundary contour instead of feature points or feature line-vectors. In addition, when feature point or feature vector based techniques are used, approximation of the object boundary by using point or vectors is required. In this case, the matching process of the corresponding pairs will be very time consuming if a fine approximation is required. In this paper, we propose a contour-based warping technique for warping image objects with arbitrary shapes. The novel idea of the new method is the introduction of mathematical morphology to allow a more flexible control of image warping. Two morphological operators are used as contour determinators. The erosion operator is used to warp image contents which are inside a user specified contour while the dilation operation is used to warp image contents which are outside of the contour. This new method is proposed to assist further development of a semi-automatic motion morphing system when accompanied with robust feature extractors such as deformable template or active contour model.

Interactive 3D segmentation using connected orthogonal contours.

PubMed

de Bruin, P W; Dercksen, V J; Post, F H; Vossepoel, A M; Streekstra, G J; Vos, F M

2005-05-01

This paper describes a new method for interactive segmentation that is based on cross-sectional design and 3D modelling. The method represents a 3D model by a set of connected contours that are planar and orthogonal. Planar contours overlayed on image data are easily manipulated and linked contours reduce the amount of user interaction.1 This method solves the contour-to-contour correspondence problem and can capture extrema of objects in a more flexible way than manual segmentation of a stack of 2D images. The resulting 3D model is guaranteed to be free of geometric and topological errors. We show that manual segmentation using connected orthogonal contours has great advantages over conventional manual segmentation. Furthermore, the method provides effective feedback and control for creating an initial model for, and control and steering of, (semi-)automatic segmentation methods.

Calculation of Lung Cancer Volume of Target Based on Thorax Computed Tomography Images using Active Contour Segmentation Method for Treatment Planning System

NASA Astrophysics Data System (ADS)

Patra Yosandha, Fiet; Adi, Kusworo; Edi Widodo, Catur

2017-06-01

In this research, calculation process of the lung cancer volume of target based on computed tomography (CT) thorax images was done. Volume of the target calculation was done in purpose to treatment planning system in radiotherapy. The calculation of the target volume consists of gross tumor volume (GTV), clinical target volume (CTV), planning target volume (PTV) and organs at risk (OAR). The calculation of the target volume was done by adding the target area on each slices and then multiply the result with the slice thickness. Calculations of area using of digital image processing techniques with active contour segmentation method. This segmentation for contouring to obtain the target volume. The calculation of volume produced on each of the targets is 577.2 cm3 for GTV, 769.9 cm3 for CTV, 877.8 cm3 for PTV, 618.7 cm3 for OAR 1, 1,162 cm3 for OAR 2 right, and 1,597 cm3 for OAR 2 left. These values indicate that the image processing techniques developed can be implemented to calculate the lung cancer target volume based on CT thorax images. This research expected to help doctors and medical physicists in determining and contouring the target volume quickly and precisely.

Active contour-based visual tracking by integrating colors, shapes, and motions.

PubMed

Hu, Weiming; Zhou, Xue; Li, Wei; Luo, Wenhan; Zhang, Xiaoqin; Maybank, Stephen

2013-05-01

In this paper, we present a framework for active contour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Fully automatic registration and segmentation of first-pass myocardial perfusion MR image sequences.

PubMed

Gupta, Vikas; Hendriks, Emile A; Milles, Julien; van der Geest, Rob J; Jerosch-Herold, Michael; Reiber, Johan H C; Lelieveldt, Boudewijn P F

2010-11-01

Derivation of diagnostically relevant parameters from first-pass myocardial perfusion magnetic resonance images involves the tedious and time-consuming manual segmentation of the myocardium in a large number of images. To reduce the manual interaction and expedite the perfusion analysis, we propose an automatic registration and segmentation method for the derivation of perfusion linked parameters. A complete automation was accomplished by first registering misaligned images using a method based on independent component analysis, and then using the registered data to automatically segment the myocardium with active appearance models. We used 18 perfusion studies (100 images per study) for validation in which the automatically obtained (AO) contours were compared with expert drawn contours on the basis of point-to-curve error, Dice index, and relative perfusion upslope in the myocardium. Visual inspection revealed successful segmentation in 15 out of 18 studies. Comparison of the AO contours with expert drawn contours yielded 2.23 ± 0.53 mm and 0.91 ± 0.02 as point-to-curve error and Dice index, respectively. The average difference between manually and automatically obtained relative upslope parameters was found to be statistically insignificant (P = .37). Moreover, the analysis time per slice was reduced from 20 minutes (manual) to 1.5 minutes (automatic). We proposed an automatic method that significantly reduced the time required for analysis of first-pass cardiac magnetic resonance perfusion images. The robustness and accuracy of the proposed method were demonstrated by the high spatial correspondence and statistically insignificant difference in perfusion parameters, when AO contours were compared with expert drawn contours. Copyright © 2010 AUR. Published by Elsevier Inc. All rights reserved.

Anatomical contouring variability in thoracic organs at risk

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

McCall, Ross, E-mail: rmccall86@gmail.com; MacLennan, Grayden; Taylor, Matthew

2016-01-01

The purpose of this study was to determine whether contouring thoracic organs at risk was consistent among medical dosimetrists and to identify how trends in dosimetrist's education and experience affected contouring accuracy. Qualitative and quantitative methods were used to contextualize the raw data that were obtained. A total of 3 different computed tomography (CT) data sets were provided to medical dosimetrists (N = 13) across 5 different institutions. The medical dosimetrists were directed to contour the lungs, heart, spinal cord, and esophagus. The medical dosimetrists were instructed to contour in line with their institutional standards and were allowed to usemore » any contouring tool or technique that they would traditionally use. The contours from each medical dosimetrist were evaluated against “gold standard” contours drawn and validated by 2 radiation oncology physicians. The dosimetrist-derived contours were evaluated against the gold standard using both a Dice coefficient method and a penalty-based metric scoring system. A short survey was also completed by each medical dosimetrist to evaluate their individual contouring experience. There was no significant variation in the contouring consistency of the lungs and spinal cord. Intradosimetrist contouring was consistent for those who contoured the esophagus and heart correctly; however, medical dosimetrists with a poor metric score showed erratic and inconsistent methods of contouring.« less

A variational approach to multi-phase motion of gas, liquid and solid based on the level set method

NASA Astrophysics Data System (ADS)

Yokoi, Kensuke

2009-07-01

We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.

A Voronoi interior adjacency-based approach for generating a contour tree

NASA Astrophysics Data System (ADS)

Chen, Jun; Qiao, Chaofei; Zhao, Renliang

2004-05-01

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model.

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering

PubMed Central

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research. PMID:28489867

A shape-based inter-layer contours correspondence method for ICT-based reverse engineering.

PubMed

Duan, Liming; Yang, Shangpeng; Zhang, Gui; Feng, Fei; Gu, Minghui

2017-01-01

The correspondence of a stack of planar contours in ICT (industrial computed tomography)-based reverse engineering, a key step in surface reconstruction, is difficult when the contours or topology of the object are complex. Given the regularity of industrial parts and similarity of the inter-layer contours, a specialized shape-based inter-layer contours correspondence method for ICT-based reverse engineering was presented to solve the above problem based on the vectorized contours. In this paper, the vectorized contours extracted from the slices consist of three graphical primitives: circles, arcs and segments. First, the correspondence of the inter-layer primitives is conducted based on the characteristics of the primitives. Second, based on the corresponded primitives, the inter-layer contours correspond with each other using the proximity rules and exhaustive search. The proposed method can make full use of the shape information to handle industrial parts with complex structures. The feasibility and superiority of this method have been demonstrated via the related experiments. This method can play an instructive role in practice and provide a reference for the related research.

An Active Contour Model Based on Adaptive Threshold for Extraction of Cerebral Vascular Structures.

PubMed

Wang, Jiaxin; Zhao, Shifeng; Liu, Zifeng; Tian, Yun; Duan, Fuqing; Pan, Yutong

2016-01-01

Cerebral vessel segmentation is essential and helpful for the clinical diagnosis and the related research. However, automatic segmentation of brain vessels remains challenging because of the variable vessel shape and high complex of vessel geometry. This study proposes a new active contour model (ACM) implemented by the level-set method for segmenting vessels from TOF-MRA data. The energy function of the new model, combining both region intensity and boundary information, is composed of two region terms, one boundary term and one penalty term. The global threshold representing the lower gray boundary of the target object by maximum intensity projection (MIP) is defined in the first-region term, and it is used to guide the segmentation of the thick vessels. In the second term, a dynamic intensity threshold is employed to extract the tiny vessels. The boundary term is used to drive the contours to evolve towards the boundaries with high gradients. The penalty term is used to avoid reinitialization of the level-set function. Experimental results on 10 clinical brain data sets demonstrate that our method is not only able to achieve better Dice Similarity Coefficient than the global threshold based method and localized hybrid level-set method but also able to extract whole cerebral vessel trees, including the thin vessels.

Contour propagation for lung tumor delineation in 4D-CT using tensor-product surface of uniform and non-uniform closed cubic B-splines

NASA Astrophysics Data System (ADS)

Jin, Renchao; Liu, Yongchuan; Chen, Mi; Zhang, Sheng; Song, Enmin

2018-01-01

A robust contour propagation method is proposed to help physicians delineate lung tumors on all phase images of four-dimensional computed tomography (4D-CT) by only manually delineating the contours on a reference phase. The proposed method models the trajectory surface swept by a contour in a respiratory cycle as a tensor-product surface of two closed cubic B-spline curves: a non-uniform B-spline curve which models the contour and a uniform B-spline curve which models the trajectory of a point on the contour. The surface is treated as a deformable entity, and is optimized from an initial surface by moving its control vertices such that the sum of the intensity similarities between the sampling points on the manually delineated contour and their corresponding ones on different phases is maximized. The initial surface is constructed by fitting the manually delineated contour on the reference phase with a closed B-spline curve. In this way, the proposed method can focus the registration on the contour instead of the entire image to prevent the deformation of the contour from being smoothed by its surrounding tissues, and greatly reduce the time consumption while keeping the accuracy of the contour propagation as well as the temporal consistency of the estimated respiratory motions across all phases in 4D-CT. Eighteen 4D-CT cases with 235 gross tumor volume (GTV) contours on the maximal inhale phase and 209 GTV contours on the maximal exhale phase are manually delineated slice by slice. The maximal inhale phase is used as the reference phase, which provides the initial contours. On the maximal exhale phase, the Jaccard similarity coefficient between the propagated GTV and the manually delineated GTV is 0.881 +/- 0.026, and the Hausdorff distance is 3.07 +/- 1.08 mm. The time for propagating the GTV to all phases is 5.55 +/- 6.21 min. The results are better than those of the fast adaptive stochastic gradient descent B-spline method, the 3D  +  t B-spline method and the diffeomorphic demons method. The proposed method is useful for helping physicians delineate target volumes efficiently and accurately.

Multiresolution multiscale active mask segmentation of fluorescence microscope images

NASA Astrophysics Data System (ADS)

Srinivasa, Gowri; Fickus, Matthew; Kovačević, Jelena

2009-08-01

We propose an active mask segmentation framework that combines the advantages of statistical modeling, smoothing, speed and flexibility offered by the traditional methods of region-growing, multiscale, multiresolution and active contours respectively. At the crux of this framework is a paradigm shift from evolving contours in the continuous domain to evolving multiple masks in the discrete domain. Thus, the active mask framework is particularly suited to segment digital images. We demonstrate the use of the framework in practice through the segmentation of punctate patterns in fluorescence microscope images. Experiments reveal that statistical modeling helps the multiple masks converge from a random initial configuration to a meaningful one. This obviates the need for an involved initialization procedure germane to most of the traditional methods used to segment fluorescence microscope images. While we provide the mathematical details of the functions used to segment fluorescence microscope images, this is only an instantiation of the active mask framework. We suggest some other instantiations of the framework to segment different types of images.

A new background distribution-based active contour model for three-dimensional lesion segmentation in breast DCE-MRI

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

Liu, Hui; Liu, Yiping; Qiu, Tianshuang

2014-08-15

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based active contour model using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure functionmore » which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new active contour model method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.« less

Lung segmentation from HRCT using united geometric active contours

NASA Astrophysics Data System (ADS)

Liu, Junwei; Li, Chuanfu; Xiong, Jin; Feng, Huanqing

2007-12-01

Accurate lung segmentation from high resolution CT images is a challenging task due to various detail tracheal structures, missing boundary segments and complex lung anatomy. One popular method is based on gray-level threshold, however its results are usually rough. A united geometric active contours model based on level set is proposed for lung segmentation in this paper. Particularly, this method combines local boundary information and region statistical-based model synchronously: 1) Boundary term ensures the integrality of lung tissue.2) Region term makes the level set function evolve with global characteristic and independent on initial settings. A penalizing energy term is introduced into the model, which forces the level set function evolving without re-initialization. The method is found to be much more efficient in lung segmentation than other methods that are only based on boundary or region. Results are shown by 3D lung surface reconstruction, which indicates that the method will play an important role in the design of computer-aided diagnostic (CAD) system.

Evaluation of the pulse-contour method of determining stroke volume in man.

NASA Technical Reports Server (NTRS)

Alderman, E. L.; Branzi, A.; Sanders, W.; Brown, B. W.; Harrison, D. C.

1972-01-01

The pulse-contour method for determining stroke volume has been employed as a continuous rapid method of monitoring the cardiovascular status of patients. Twenty-one patients with ischemic heart disease and 21 patients with mitral valve disease were subjected to a variety of hemodynamic interventions. The pulse-contour estimations, using three different formulas derived by Warner, Kouchoukos, and Herd, were compared with indicator-dilution outputs. A comparison of the results of the two methods for determining stroke volume yielded correlation coefficients ranging from 0.59 to 0.84. The better performing Warner formula yielded a coefficient of variation of about 20%. The type of hemodynamic interventions employed did not significantly affect the results using the pulse-contour method. Although the correlation of the pulse-contour and indicator-dilution stroke volumes is high, the coefficient of variation is such that small changes in stroke volume cannot be accurately assessed by the pulse-contour method. However, the simplicity and rapidity of this method compared to determination of cardiac output by Fick or indicator-dilution methods makes it a potentially useful adjunct for monitoring critically ill patients.

Breast mass segmentation in mammograms combining fuzzy c-means and active contours

NASA Astrophysics Data System (ADS)

Hmida, Marwa; Hamrouni, Kamel; Solaiman, Basel; Boussetta, Sana

2018-04-01

Segmentation of breast masses in mammograms is a challenging issue due to the nature of mammography and the characteristics of masses. In fact, mammographic images are poor in contrast and breast masses have various shapes and densities with fuzzy and ill-defined borders. In this paper, we propose a method based on a modified Chan-Vese active contour model for mass segmentation in mammograms. We conduct the experiment on mass Regions of Interest (ROI) extracted from the MIAS database. The proposed method consists of mainly three stages: Firstly, the ROI is preprocessed to enhance the contrast. Next, two fuzzy membership maps are generated from the preprocessed ROI based on fuzzy C-Means algorithm. These fuzzy membership maps are finally used to modify the energy of the Chan-Vese model and to perform the final segmentation. Experimental results indicate that the proposed method yields good mass segmentation results.

Automatic selection of localized region-based active contour models using image content analysis applied to brain tumor segmentation.

PubMed

Ilunga-Mbuyamba, Elisee; Avina-Cervantes, Juan Gabriel; Cepeda-Negrete, Jonathan; Ibarra-Manzano, Mario Alberto; Chalopin, Claire

2017-12-01

Brain tumor segmentation is a routine process in a clinical setting and provides useful information for diagnosis and treatment planning. Manual segmentation, performed by physicians or radiologists, is a time-consuming task due to the large quantity of medical data generated presently. Hence, automatic segmentation methods are needed, and several approaches have been introduced in recent years including the Localized Region-based Active Contour Model (LRACM). There are many popular LRACM, but each of them presents strong and weak points. In this paper, the automatic selection of LRACM based on image content and its application on brain tumor segmentation is presented. Thereby, a framework to select one of three LRACM, i.e., Local Gaussian Distribution Fitting (LGDF), localized Chan-Vese (C-V) and Localized Active Contour Model with Background Intensity Compensation (LACM-BIC), is proposed. Twelve visual features are extracted to properly select the method that may process a given input image. The system is based on a supervised approach. Applied specifically to Magnetic Resonance Imaging (MRI) images, the experiments showed that the proposed system is able to correctly select the suitable LRACM to handle a specific image. Consequently, the selection framework achieves better accuracy performance than the three LRACM separately. Copyright © 2017 Elsevier Ltd. All rights reserved.

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images.

PubMed

Hamoud Al-Tamimi, Mohammed Sabbih; Sulong, Ghazali; Shuaib, Ibrahim Lutfi

2015-07-01

Resection of brain tumors is a tricky task in surgery due to its direct influence on the patients' survival rate. Determining the tumor resection extent for its complete information via-à-vis volume and dimensions in pre- and post-operative Magnetic Resonance Images (MRI) requires accurate estimation and comparison. The active contour segmentation technique is used to segment brain tumors on pre-operative MR images using self-developed software. Tumor volume is acquired from its contours via alpha shape theory. The graphical user interface is developed for rendering, visualizing and estimating the volume of a brain tumor. Internet Brain Segmentation Repository dataset (IBSR) is employed to analyze and determine the repeatability and reproducibility of tumor volume. Accuracy of the method is validated by comparing the estimated volume using the proposed method with that of gold-standard. Segmentation by active contour technique is found to be capable of detecting the brain tumor boundaries. Furthermore, the volume description and visualization enable an interactive examination of tumor tissue and its surrounding. Admirable features of our results demonstrate that alpha shape theory in comparison to other existing standard methods is superior for precise volumetric measurement of tumor. Copyright © 2015 Elsevier Inc. All rights reserved.

Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT

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

Yuan, Yading, E-mail: yading.yuan@mssm.edu; Chao, Ming; Sheu, Ren-Dih

Purpose: This work aims to develop a robust and efficient method to track the fuzzy borders between liver and the abutted organs where automatic liver segmentation usually suffers, and to investigate its applications in automatic liver segmentation on noncontrast-enhanced planning computed tomography (CT) images. Methods: In order to track the fuzzy liver–chestwall and liver–heart borders where oversegmentation is often found, a starting point and an ending point were first identified on the coronal view images; the fuzzy border was then determined as a geodesic curve constructed by minimizing the gradient-weighted path length between these two points near the fuzzy border.more » The minimization of path length was numerically solved by fast-marching method. The resultant fuzzy borders were incorporated into the authors’ automatic segmentation scheme, in which the liver was initially estimated by a patient-specific adaptive thresholding and then refined by a geodesic active contour model. By using planning CT images of 15 liver patients treated with stereotactic body radiation therapy, the liver contours extracted by the proposed computerized scheme were compared with those manually delineated by a radiation oncologist. Results: The proposed automatic liver segmentation method yielded an average Dice similarity coefficient of 0.930 ± 0.015, whereas it was 0.912 ± 0.020 if the fuzzy border tracking was not used. The application of fuzzy border tracking was found to significantly improve the segmentation performance. The mean liver volume obtained by the proposed method was 1727 cm{sup 3}, whereas it was 1719 cm{sup 3} for manual-outlined volumes. The computer-generated liver volumes achieved excellent agreement with manual-outlined volumes with correlation coefficient of 0.98. Conclusions: The proposed method was shown to provide accurate segmentation for liver in the planning CT images where contrast agent is not applied. The authors’ results also clearly demonstrated that the application of tracking the fuzzy borders could significantly reduce contour leakage during active contour evolution.« less

Method for contour extraction for object representation

DOEpatents

Skourikhine, Alexei N.; Prasad, Lakshman

2005-08-30

Contours are extracted for representing a pixelated object in a background pixel field. An object pixel is located that is the start of a new contour for the object and identifying that pixel as the first pixel of the new contour. A first contour point is then located on the mid-point of a transition edge of the first pixel. A tracing direction from the first contour point is determined for tracing the new contour. Contour points on mid-points of pixel transition edges are sequentially located along the tracing direction until the first contour point is again encountered to complete tracing the new contour. The new contour is then added to a list of extracted contours that represent the object. The contour extraction process associates regions and contours by labeling all the contours belonging to the same object with the same label.

Fast Virtual Stenting with Active Contour Models in Intracranical Aneurysm

PubMed Central

Zhong, Jingru; Long, Yunling; Yan, Huagang; Meng, Qianqian; Zhao, Jing; Zhang, Ying; Yang, Xinjian; Li, Haiyun

2016-01-01

Intracranial stents are becoming increasingly a useful option in the treatment of intracranial aneurysms (IAs). Image simulation of the releasing stent configuration together with computational fluid dynamics (CFD) simulation prior to intervention will help surgeons optimize intervention scheme. This paper proposed a fast virtual stenting of IAs based on active contour model (ACM) which was able to virtually release stents within any patient-specific shaped vessel and aneurysm models built on real medical image data. In this method, an initial stent mesh was generated along the centerline of the parent artery without the need for registration between the stent contour and the vessel. Additionally, the diameter of the initial stent volumetric mesh was set to the maximum inscribed sphere diameter of the parent artery to improve the stenting accuracy and save computational cost. At last, a novel criterion for terminating virtual stent expanding that was based on the collision detection of the axis aligned bounding boxes was applied, making the stent expansion free of edge effect. The experiment results of the virtual stenting and the corresponding CFD simulations exhibited the efficacy and accuracy of the ACM based method, which are valuable to intervention scheme selection and therapy plan confirmation. PMID:26876026

Interactive outlining: an improved approach using active contours

NASA Astrophysics Data System (ADS)

Daneels, Dirk; van Campenhout, David; Niblack, Carlton W.; Equitz, Will; Barber, Ron; Fierens, Freddy

1993-04-01

The purpose of our work is to outline objects on images in an interactive environment. We use an improved method based on energy minimizing active contours or `snakes.' Kass et al., proposed a variational technique; Amini used dynamic programming; and Williams and Shah introduced a fast, greedy algorithm. We combine the advantages of the latter two methods in a two-stage algorithm. The first stage is a greedy procedure that provides fast initial convergence. It is enhanced with a cost term that extends over a large number of points to avoid oscillations. The second stage, when accuracy becomes important, uses dynamic programming. This step is accelerated by the use of alternating search neighborhoods and by dropping stable points from the iterations. We have also added several features for user interaction. First, the user can define points of high confidence. Mathematically, this results in an extra cost term and, in that way, the robustness in difficult areas (e.g., noisy edges, sharp corners) is improved. We also give the user the possibility of incremental contour tracking, thus providing feedback on the refinement process. The algorithm has been tested on numerous photographic clip art images and extensive tests on medical images are in progress.

Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

NASA Astrophysics Data System (ADS)

Nabizadeh, Nooshin; John, Nigel

2014-03-01

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

An Automatic Segmentation Method Combining an Active Contour Model and a Classification Technique for Detecting Polycomb-group Proteinsin High-Throughput Microscopy Images.

PubMed

Gregoretti, Francesco; Cesarini, Elisa; Lanzuolo, Chiara; Oliva, Gennaro; Antonelli, Laura

2016-01-01

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an active contour model and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

The research of multi-frame target recognition based on laser active imaging

NASA Astrophysics Data System (ADS)

Wang, Can-jin; Sun, Tao; Wang, Tin-feng; Chen, Juan

2013-09-01

Laser active imaging is fit to conditions such as no difference in temperature between target and background, pitch-black night, bad visibility. Also it can be used to detect a faint target in long range or small target in deep space, which has advantage of high definition and good contrast. In one word, it is immune to environment. However, due to the affect of long distance, limited laser energy and atmospheric backscatter, it is impossible to illuminate the whole scene at the same time. It means that the target in every single frame is unevenly or partly illuminated, which make the recognition more difficult. At the same time the speckle noise which is common in laser active imaging blurs the images . In this paper we do some research on laser active imaging and propose a new target recognition method based on multi-frame images . Firstly, multi pulses of laser is used to obtain sub-images for different parts of scene. A denoising method combined homomorphic filter with wavelet domain SURE is used to suppress speckle noise. And blind deconvolution is introduced to obtain low-noise and clear sub-images. Then these sub-images are registered and stitched to combine a completely and uniformly illuminated scene image. After that, a new target recognition method based on contour moments is proposed. Firstly, canny operator is used to obtain contours. For each contour, seven invariant Hu moments are calculated to generate the feature vectors. At last the feature vectors are input into double hidden layers BP neural network for classification . Experiments results indicate that the proposed algorithm could achieve a high recognition rate and satisfactory real-time performance for laser active imaging.

Automatic classification of canine PRG neuronal discharge patterns using K-means clustering.

PubMed

Zuperku, Edward J; Prkic, Ivana; Stucke, Astrid G; Miller, Justin R; Hopp, Francis A; Stuth, Eckehard A

2015-02-01

Respiratory-related neurons in the parabrachial-Kölliker-Fuse (PB-KF) region of the pons play a key role in the control of breathing. The neuronal activities of these pontine respiratory group (PRG) neurons exhibit a variety of inspiratory (I), expiratory (E), phase spanning and non-respiratory related (NRM) discharge patterns. Due to the variety of patterns, it can be difficult to classify them into distinct subgroups according to their discharge contours. This report presents a method that automatically classifies neurons according to their discharge patterns and derives an average subgroup contour of each class. It is based on the K-means clustering technique and it is implemented via SigmaPlot User-Defined transform scripts. The discharge patterns of 135 canine PRG neurons were classified into seven distinct subgroups. Additional methods for choosing the optimal number of clusters are described. Analysis of the results suggests that the K-means clustering method offers a robust objective means of both automatically categorizing neuron patterns and establishing the underlying archetypical contours of subtypes based on the discharge patterns of group of neurons. Published by Elsevier B.V.

Semi-automated extraction of longitudinal subglacial bedforms from digital terrain models - Two new methods

NASA Astrophysics Data System (ADS)

Jorge, Marco G.; Brennand, Tracy A.

2017-07-01

Relict drumlin and mega-scale glacial lineation (positive relief, longitudinal subglacial bedforms - LSBs) morphometry has been used as a proxy for paleo ice-sheet dynamics. LSB morphometric inventories have relied on manual mapping, which is slow and subjective and thus potentially difficult to reproduce. Automated methods are faster and reproducible, but previous methods for LSB semi-automated mapping have not been highly successful. Here, two new object-based methods for the semi-automated extraction of LSBs (footprints) from digital terrain models are compared in a test area in the Puget Lowland, Washington, USA. As segmentation procedures to create LSB-candidate objects, the normalized closed contour method relies on the contouring of a normalized local relief model addressing LSBs on slopes, and the landform elements mask method relies on the classification of landform elements derived from the digital terrain model. For identifying which LSB-candidate objects correspond to LSBs, both methods use the same LSB operational definition: a ruleset encapsulating expert knowledge, published morphometric data, and the morphometric range of LSBs in the study area. The normalized closed contour method was separately applied to four different local relief models, two computed in moving windows and two hydrology-based. Overall, the normalized closed contour method outperformed the landform elements mask method. The normalized closed contour method performed on a hydrological relief model from a multiple direction flow routing algorithm performed best. For an assessment of its transferability, the normalized closed contour method was evaluated on a second area, the Chautauqua drumlin field, Pennsylvania and New York, USA where it performed better than in the Puget Lowland. A broad comparison to previous methods suggests that the normalized relief closed contour method may be the most capable method to date, but more development is required.

Development of a semi-automated combined PET and CT lung lesion segmentation framework

NASA Astrophysics Data System (ADS)

Rossi, Farli; Mokri, Siti Salasiah; Rahni, Ashrani Aizzuddin Abd.

2017-03-01

Segmentation is one of the most important steps in automated medical diagnosis applications, which affects the accuracy of the overall system. In this paper, we propose a semi-automated segmentation method for extracting lung lesions from thoracic PET/CT images by combining low level processing and active contour techniques. The lesions are first segmented in PET images which are first converted to standardised uptake values (SUVs). The segmented PET images then serve as an initial contour for subsequent active contour segmentation of corresponding CT images. To evaluate its accuracy, the Jaccard Index (JI) was used as a measure of the accuracy of the segmented lesion compared to alternative segmentations from the QIN lung CT segmentation challenge, which is possible by registering the whole body PET/CT images to the corresponding thoracic CT images. The results show that our proposed technique has acceptable accuracy in lung lesion segmentation with JI values of around 0.8, especially when considering the variability of the alternative segmentations.

Fourier Descriptor Analysis and Unification of Voice Range Profile Contours: Method and Applications

ERIC Educational Resources Information Center

Pabon, Peter; Ternstrom, Sten; Lamarche, Anick

2011-01-01

Purpose: To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. Method: A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the…

Entropy reduction via simplified image contourization

NASA Technical Reports Server (NTRS)

Turner, Martin J.

1993-01-01

The process of contourization is presented which converts a raster image into a set of plateaux or contours. These contours can be grouped into a hierarchical structure, defining total spatial inclusion, called a contour tree. A contour coder has been developed which fully describes these contours in a compact and efficient manner and is the basis for an image compression method. Simplification of the contour tree has been undertaken by merging contour tree nodes thus lowering the contour tree's entropy. This can be exploited by the contour coder to increase the image compression ratio. By applying general and simple rules derived from physiological experiments on the human vision system, lossy image compression can be achieved which minimizes noticeable artifacts in the simplified image.

TU-H-CAMPUS-JeP1-02: Fully Automatic Verification of Automatically Contoured Normal Tissues in the Head and Neck

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

McCarroll, R; UT Health Science Center, Graduate School of Biomedical Sciences, Houston, TX; Beadle, B

Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrectmore » contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to flag auto-contours for special review or used with safety margins in a fully automatic treatment planning system.« less

Left ventricle segmentation via two-layer level sets with circular shape constraint.

PubMed

Yang, Cong; Wu, Weiguo; Su, Yuanqi; Zhang, Shaoxiang

2017-05-01

This paper proposes a circular shape constraint and a novel two-layer level set method for the segmentation of the left ventricle (LV) from short-axis magnetic resonance images without training any shape models. Since the shape of LV throughout the apex-base axis is close to a ring shape, we propose a circle fitting term in the level set framework to detect the endocardium. The circle fitting term imposes a penalty on the evolving contour from its fitting circle, and thereby handles quite well with issues in LV segmentation, especially the presence of outflow track in basal slices and the intensity overlap between TPM and the myocardium. To extract the whole myocardium, the circle fitting term is incorporated into two-layer level set method. The endocardium and epicardium are respectively represented by two specified level contours of the level set function, which are evolved by an edge-based and a region-based active contour model. The proposed method has been quantitatively validated on the public data set from MICCAI 2009 challenge on the LV segmentation. Experimental results and comparisons with state-of-the-art demonstrate the accuracy and robustness of our method. Copyright © 2017 Elsevier Inc. All rights reserved.

DEM generation from contours and a low-resolution DEM

NASA Astrophysics Data System (ADS)

Li, Xinghua; Shen, Huanfeng; Feng, Ruitao; Li, Jie; Zhang, Liangpei

2017-12-01

A digital elevation model (DEM) is a virtual representation of topography, where the terrain is established by the three-dimensional co-ordinates. In the framework of sparse representation, this paper investigates DEM generation from contours. Since contours are usually sparsely distributed and closely related in space, sparse spatial regularization (SSR) is enforced on them. In order to make up for the lack of spatial information, another lower spatial resolution DEM from the same geographical area is introduced. In this way, the sparse representation implements the spatial constraints in the contours and extracts the complementary information from the auxiliary DEM. Furthermore, the proposed method integrates the advantage of the unbiased estimation of kriging. For brevity, the proposed method is called the kriging and sparse spatial regularization (KSSR) method. The performance of the proposed KSSR method is demonstrated by experiments in Shuttle Radar Topography Mission (SRTM) 30 m DEM and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) 30 m global digital elevation model (GDEM) generation from the corresponding contours and a 90 m DEM. The experiments confirm that the proposed KSSR method outperforms the traditional kriging and SSR methods, and it can be successfully used for DEM generation from contours.

SU-C-BRA-03: An Automated and Quick Contour Errordetection for Auto Segmentation in Online Adaptive Radiotherapy

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

Zhang, J; Ates, O; Li, X

Purpose: To develop a tool that can quickly and automatically assess contour quality generated from auto segmentation during online adaptive replanning. Methods: Due to the strict time requirement of online replanning and lack of ‘ground truth’ contours in daily images, our method starts with assessing image registration accuracy focusing on the surface of the organ in question. Several metrics tightly related to registration accuracy including Jacobian maps, contours shell deformation, and voxel-based root mean square (RMS) analysis were computed. To identify correct contours, additional metrics and an adaptive decision tree are introduced. To approve in principle, tests were performed withmore » CT sets, planned and daily CTs acquired using a CT-on-rails during routine CT-guided RT delivery for 20 prostate cancer patients. The contours generated on daily CTs using an auto-segmentation tool (ADMIRE, Elekta, MIM) based on deformable image registration of the planning CT and daily CT were tested. Results: The deformed contours of 20 patients with total of 60 structures were manually checked as baselines. The incorrect rate of total contours is 49%. To evaluate the quality of local deformation, the Jacobian determinant (1.047±0.045) on contours has been analyzed. In an analysis of rectum contour shell deformed, the higher rate (0.41) of error contours detection was obtained compared to 0.32 with manual check. All automated detections took less than 5 seconds. Conclusion: The proposed method can effectively detect contour errors in micro and macro scope by evaluating multiple deformable registration metrics in a parallel computing process. Future work will focus on improving practicability and optimizing calculation algorithms and metric selection.« less

Orthosis-Shaped Sandals Are as Efficacious as In-Shoe Orthoses and Better than Flat Sandals for Plantar Heel Pain: A Randomized Control Trial

PubMed Central

Vicenzino, Bill; McPoil, Thomas G.; Stephenson, Aoife; Paul, Sanjoy K.

2015-01-01

Objective To investigate efficacy of a contoured sandal being marketed for plantar heel pain with comparison to a flat flip-flop and contoured in-shoe insert/orthosis. Method 150 volunteers aged 50 (SD: 12) years with plantar heel pain (>4 weeks) were enrolled after responding to advertisements and eligibility determined by telephone and at first visit. Participants were randomly allocated to receive commercially available contoured sandals (n = 49), flat flip-flops (n = 50) or over the counter, pre-fabricated full-length foot orthotics (n = 51). Primary outcomes were a 15-point Global Rating of Change scale (GROC: 1 = a very great deal worse, 15 = a very great deal better), 13 to 15 representing an improvement and the 20-item Lower Extremity Function Scale (LEFS) on which participants rate 20 common weight bearing activities and activities of daily living on a 5-point scale (0 = extreme difficulty, 4 = no difficulty). Secondary outcomes were worst level of heel pain in the preceding week, and the foot and ankle ability measure. Outcomes were collected blind to allocation. Analyses were done on an intention to treat basis with 12 weeks being the primary outcome time of interest. Results The contoured sandal was 68% more likely to report improvement in terms of GROC compared to flat flip-flop. On the LEFS the contoured sandal was 61% more likely than flat flip-flop to report improvement. The secondary outcomes in the main reflected the primary outcomes, and there were no differences between contoured sandal and shoe insert. Conclusions and Relevance Physicians can have confidence in supporting a patient's decision to wear contoured sandals or in-shoe orthoses as one of the first and simple strategies to manage their heel pain. Trial Registration The Australian New Zealand Clinical Trials Registry ACTRN12612000463875 PMID:26669302

A new template matching method based on contour information

NASA Astrophysics Data System (ADS)

Cai, Huiying; Zhu, Feng; Wu, Qingxiao; Li, Sicong

2014-11-01

Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can't be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process, the initial RST parameters are discrete to obtain the final accurate pose of the object. Experimental results show that the proposed method is reasonable and efficient, and can be used in many real time applications.

An improved spatial contour tree constructed method

NASA Astrophysics Data System (ADS)

Zheng, Yi; Zhang, Ling; Guilbert, Eric; Long, Yi

2018-05-01

Contours are important data to delineate the landform on a map. A contour tree provides an object-oriented description of landforms and can be used to enrich the topological information. The traditional contour tree is used to store topological relationships between contours in a hierarchical structure and allows for the identification of eminences and depressions as sets of nested contours. This research proposes an improved contour tree so-called spatial contour tree that contains not only the topological but also the geometric information. It can be regarded as a terrain skeleton in 3-dimention, and it is established based on the spatial nodes of contours which have the latitude, longitude and elevation information. The spatial contour tree is built by connecting spatial nodes from low to high elevation for a positive landform, and from high to low elevation for a negative landform to form a hierarchical structure. The connection between two spatial nodes can provide the real distance and direction as a Euclidean vector in 3-dimention. In this paper, the construction method is tested in the experiment, and the results are discussed. The proposed hierarchical structure is in 3-demintion and can show the skeleton inside a terrain. The structure, where all nodes have geo-information, can be used to distinguish different landforms and applied for contour generalization with consideration of geographic characteristics.

Automatic correction of dental artifacts in PET/MRI

PubMed Central

Ladefoged, Claes N.; Andersen, Flemming L.; Keller, Sune. H.; Beyer, Thomas; Law, Ian; Højgaard, Liselotte; Darkner, Sune; Lauze, Francois

2015-01-01

Abstract. A challenge when using current magnetic resonance (MR)-based attenuation correction in positron emission tomography/MR imaging (PET/MRI) is that the MRIs can have a signal void around the dental fillings that is segmented as artificial air-regions in the attenuation map. For artifacts connected to the background, we propose an extension to an existing active contour algorithm to delineate the outer contour using the nonattenuation corrected PET image and the original attenuation map. We propose a combination of two different methods for differentiating the artifacts within the body from the anatomical air-regions by first using a template of artifact regions, and second, representing the artifact regions with a combination of active shape models and k-nearest-neighbors. The accuracy of the combined method has been evaluated using 25 F18-fluorodeoxyglucose PET/MR patients. Results showed that the approach was able to correct an average of 97±3% of the artifact areas. PMID:26158104

Phase retrieval in digital speckle pattern interferometry by application of two-dimensional active contours called snakes.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2006-03-20

We propose a novel approach to retrieving the phase map coded by a single closed-fringe pattern in digital speckle pattern interferometry, which is based on the estimation of the local sign of the quadrature component. We obtain the estimate by calculating the local orientation of the fringes that have previously been denoised by a weighted smoothing spline method. We carry out the procedure of sign estimation by determining the local abrupt jumps of size pi in the orientation field of the fringes and by segmenting the regions defined by these jumps. The segmentation method is based on the application of two-dimensional active contours (snakes), with which one can also estimate absent jumps, i.e., those that cannot be detected from the local orientation of the fringes. The performance of the proposed phase-retrieval technique is evaluated for synthetic and experimental fringes and compared with the results obtained with the spiral-phase- and Fourier-transform methods.

Superpixel guided active contour segmentation of retinal layers in OCT volumes

NASA Astrophysics Data System (ADS)

Bai, Fangliang; Gibson, Stuart J.; Marques, Manuel J.; Podoleanu, Adrian

2018-03-01

Retinal OCT image segmentation is a precursor to subsequent medical diagnosis by a clinician or machine learning algorithm. In the last decade, many algorithms have been proposed to detect retinal layer boundaries and simplify the image representation. Inspired by the recent success of superpixel methods for pre-processing natural images, we present a novel framework for segmentation of retinal layers in OCT volume data. In our framework, the region of interest (e.g. the fovea) is located using an adaptive-curve method. The cell layer boundaries are then robustly detected firstly using 1D superpixels, applied to A-scans, and then fitting active contours in B-scan images. Thereafter the 3D cell layer surfaces are efficiently segmented from the volume data. The framework was tested on healthy eye data and we show that it is capable of segmenting up to 12 layers. The experimental results imply the effectiveness of proposed method and indicate its robustness to low image resolution and intrinsic speckle noise.

Welding deviation detection algorithm based on extremum of molten pool image contour

NASA Astrophysics Data System (ADS)

Zou, Yong; Jiang, Lipei; Li, Yunhua; Xue, Long; Huang, Junfen; Huang, Jiqiang

2016-01-01

The welding deviation detection is the basis of robotic tracking welding, but the on-line real-time measurement of welding deviation is still not well solved by the existing methods. There is plenty of information in the gas metal arc welding(GMAW) molten pool images that is very important for the control of welding seam tracking. The physical meaning for the curvature extremum of molten pool contour is revealed by researching the molten pool images, that is, the deviation information points of welding wire center and the molten tip center are the maxima and the local maxima of the contour curvature, and the horizontal welding deviation is the position difference of these two extremum points. A new method of weld deviation detection is presented, including the process of preprocessing molten pool images, extracting and segmenting the contours, obtaining the contour extremum points, and calculating the welding deviation, etc. Extracting the contours is the premise, segmenting the contour lines is the foundation, and obtaining the contour extremum points is the key. The contour images can be extracted with the method of discrete dyadic wavelet transform, which is divided into two sub contours including welding wire and molten tip separately. The curvature value of each point of the two sub contour lines is calculated based on the approximate curvature formula of multi-points for plane curve, and the two points of the curvature extremum are the characteristics needed for the welding deviation calculation. The results of the tests and analyses show that the maximum error of the obtained on-line welding deviation is 2 pixels(0.16 mm), and the algorithm is stable enough to meet the requirements of the pipeline in real-time control at a speed of less than 500 mm/min. The method can be applied to the on-line automatic welding deviation detection.

A method for calculating a real-gas two-dimensional nozzle contour including the effects of gamma

NASA Technical Reports Server (NTRS)

Johnson, C. B.; Boney, L. R.

1975-01-01

A method for calculating two-dimensional inviscid nozzle contours for a real gas or an ideal gas by the method of characteristics is described. The method consists of a modification of an existing nozzle computer program. The ideal-gas nozzle contour can be calculated for any constant value of gamma. Two methods of calculating the center-line boundary values of the Mach number in the throat region are also presented. The use of these three methods of calculating the center-line Mach number distribution in the throat region can change the distance from the throat to the inflection point by a factor of 2.5. A user's guide is presented for input to the computer program for both the two-dimensional and axisymmetric nozzle contours.

GPU based contouring method on grid DEM data

NASA Astrophysics Data System (ADS)

Tan, Liheng; Wan, Gang; Li, Feng; Chen, Xiaohui; Du, Wenlong

2017-08-01

This paper presents a novel method to generate contour lines from grid DEM data based on the programmable GPU pipeline. The previous contouring approaches often use CPU to construct a finite element mesh from the raw DEM data, and then extract contour segments from the elements. They also need a tracing or sorting strategy to generate the final continuous contours. These approaches can be heavily CPU-costing and time-consuming. Meanwhile the generated contours would be unsmooth if the raw data is sparsely distributed. Unlike the CPU approaches, we employ the GPU's vertex shader to generate a triangular mesh with arbitrary user-defined density, in which the height of each vertex is calculated through a third-order Cardinal spline function. Then in the same frame, segments are extracted from the triangles by the geometry shader, and translated to the CPU-side with an internal order in the GPU's transform feedback stage. Finally we propose a "Grid Sorting" algorithm to achieve the continuous contour lines by travelling the segments only once. Our method makes use of multiple stages of GPU pipeline for computation, which can generate smooth contour lines, and is significantly faster than the previous CPU approaches. The algorithm can be easily implemented with OpenGL 3.3 API or higher on consumer-level PCs.

Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement.

PubMed

Kamoi, Shun; Pretty, Christopher; Balmer, Joel; Davidson, Shaun; Pironet, Antoine; Desaive, Thomas; Shaw, Geoffrey M; Chase, J Geoffrey

2017-04-24

Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir-wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20-24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. Bland-Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of ±26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV.

Contour metrology using critical dimension atomic force microscopy

NASA Astrophysics Data System (ADS)

Orji, Ndubuisi G.; Dixson, Ronald G.; Vladár, András E.; Ming, Bin; Postek, Michael T.

2012-03-01

The critical dimension atomic force microscope (CD-AFM), which is used as a reference instrument in lithography metrology, has been proposed as a complementary instrument for contour measurement and verification. Although data from CD-AFM is inherently three dimensional, the planar two-dimensional data required for contour metrology is not easily extracted from the top-down CD-AFM data. This is largely due to the limitations of the CD-AFM method for controlling the tip position and scanning. We describe scanning techniques and profile extraction methods to obtain contours from CD-AFM data. We also describe how we validated our technique, and explain some of its limitations. Potential sources of error for this approach are described, and a rigorous uncertainty model is presented. Our objective is to show which data acquisition and analysis methods could yield optimum contour information while preserving some of the strengths of CD-AFM metrology. We present comparison of contours extracted using our technique to those obtained from the scanning electron microscope (SEM), and the helium ion microscope (HIM).

Prostate segmentation in MRI using fused T2-weighted and elastography images

NASA Astrophysics Data System (ADS)

Nir, Guy; Sahebjavaher, Ramin S.; Baghani, Ali; Sinkus, Ralph; Salcudean, Septimiu E.

2014-03-01

Segmentation of the prostate in medical imaging is a challenging and important task for surgical planning and delivery of prostate cancer treatment. Automatic prostate segmentation can improve speed, reproducibility and consistency of the process. In this work, we propose a method for automatic segmentation of the prostate in magnetic resonance elastography (MRE) images. The method utilizes the complementary property of the elastogram and the corresponding T2-weighted image, which are obtained from the phase and magnitude components of the imaging signal, respectively. It follows a variational approach to propagate an active contour model based on the combination of region statistics in the elastogram and the edge map of the T2-weighted image. The method is fast and does not require prior shape information. The proposed algorithm is tested on 35 clinical image pairs from five MRE data sets, and is evaluated in comparison with manual contouring. The mean absolute distance between the automatic and manual contours is 1.8mm, with a maximum distance of 5.6mm. The relative area error is 7.6%, and the duration of the segmentation process is 2s per slice.

Accurate computer-aided quantification of left ventricular parameters: experience in 1555 cardiac magnetic resonance studies from the Framingham Heart Study.

PubMed

Hautvast, Gilion L T F; Salton, Carol J; Chuang, Michael L; Breeuwer, Marcel; O'Donnell, Christopher J; Manning, Warren J

2012-05-01

Quantitative analysis of short-axis functional cardiac magnetic resonance images can be performed using automatic contour detection methods. The resulting myocardial contours must be reviewed and possibly corrected, which can be time-consuming, particularly when performed across all cardiac phases. We quantified the impact of manual contour corrections on both analysis time and quantitative measurements obtained from left ventricular short-axis cine images acquired from 1555 participants of the Framingham Heart Study Offspring cohort using computer-aided contour detection methods. The total analysis time for a single case was 7.6 ± 1.7 min for an average of 221 ± 36 myocardial contours per participant. This included 4.8 ± 1.6 min for manual contour correction of 2% of all automatically detected endocardial contours and 8% of all automatically detected epicardial contours. However, the impact of these corrections on global left ventricular parameters was limited, introducing differences of 0.4 ± 4.1 mL for end-diastolic volume, -0.3 ± 2.9 mL for end-systolic volume, 0.7 ± 3.1 mL for stroke volume, and 0.3 ± 1.8% for ejection fraction. We conclude that left ventricular functional parameters can be obtained under 5 min from short-axis functional cardiac magnetic resonance images using automatic contour detection methods. Manual correction more than doubles analysis time, with minimal impact on left ventricular volumes and ejection fraction. Copyright © 2011 Wiley Periodicals, Inc.

Normal contour error measurement on-machine and compensation method for polishing complex surface by MRF

NASA Astrophysics Data System (ADS)

Chen, Hua; Chen, Jihong; Wang, Baorui; Zheng, Yongcheng

2016-10-01

The Magnetorheological finishing (MRF) process, based on the dwell time method with the constant normal spacing for flexible polishing, would bring out the normal contour error in the fine polishing complex surface such as aspheric surface. The normal contour error would change the ribbon's shape and removal characteristics of consistency for MRF. Based on continuously scanning the normal spacing between the workpiece and the finder by the laser range finder, the novel method was put forward to measure the normal contour errors while polishing complex surface on the machining track. The normal contour errors was measured dynamically, by which the workpiece's clamping precision, multi-axis machining NC program and the dynamic performance of the MRF machine were achieved for the verification and security check of the MRF process. The unit for measuring the normal contour errors of complex surface on-machine was designed. Based on the measurement unit's results as feedback to adjust the parameters of the feed forward control and the multi-axis machining, the optimized servo control method was presented to compensate the normal contour errors. The experiment for polishing 180mm × 180mm aspherical workpiece of fused silica by MRF was set up to validate the method. The results show that the normal contour error was controlled in less than 10um. And the PV value of the polished surface accuracy was improved from 0.95λ to 0.09λ under the conditions of the same process parameters. The technology in the paper has been being applied in the PKC600-Q1 MRF machine developed by the China Academe of Engineering Physics for engineering application since 2014. It is being used in the national huge optical engineering for processing the ultra-precision optical parts.

Saliency-aware food image segmentation for personal dietary assessment using a wearable computer

PubMed Central

Chen, Hsin-Chen; Jia, Wenyan; Sun, Xin; Li, Zhaoxin; Li, Yuecheng; Fernstrom, John D.; Burke, Lora E.; Baranowski, Thomas; Sun, Mingui

2015-01-01

Image-based dietary assessment has recently received much attention in the community of obesity research. In this assessment, foods in digital pictures are specified, and their portion sizes (volumes) are estimated. Although manual processing is currently the most utilized method, image processing holds much promise since it may eventually lead to automatic dietary assessment. In this paper we study the problem of segmenting food objects from images. This segmentation is difficult because of various food types, shapes and colors, different decorating patterns on food containers, and occlusions of food and non-food objects. We propose a novel method based on a saliency-aware active contour model (ACM) for automatic food segmentation from images acquired by a wearable camera. An integrated saliency estimation approach based on food location priors and visual attention features is designed to produce a salient map of possible food regions in the input image. Next, a geometric contour primitive is generated and fitted to the salient map by means of multi-resolution optimization with respect to a set of affine and elastic transformation parameters. The food regions are then extracted after contour fitting. Our experiments using 60 food images showed that the proposed method achieved significantly higher accuracy in food segmentation when compared to conventional segmentation methods. PMID:26257473

Saliency-aware food image segmentation for personal dietary assessment using a wearable computer

NASA Astrophysics Data System (ADS)

Chen, Hsin-Chen; Jia, Wenyan; Sun, Xin; Li, Zhaoxin; Li, Yuecheng; Fernstrom, John D.; Burke, Lora E.; Baranowski, Thomas; Sun, Mingui

2015-02-01

Image-based dietary assessment has recently received much attention in the community of obesity research. In this assessment, foods in digital pictures are specified, and their portion sizes (volumes) are estimated. Although manual processing is currently the most utilized method, image processing holds much promise since it may eventually lead to automatic dietary assessment. In this paper we study the problem of segmenting food objects from images. This segmentation is difficult because of various food types, shapes and colors, different decorating patterns on food containers, and occlusions of food and non-food objects. We propose a novel method based on a saliency-aware active contour model (ACM) for automatic food segmentation from images acquired by a wearable camera. An integrated saliency estimation approach based on food location priors and visual attention features is designed to produce a salient map of possible food regions in the input image. Next, a geometric contour primitive is generated and fitted to the salient map by means of multi-resolution optimization with respect to a set of affine and elastic transformation parameters. The food regions are then extracted after contour fitting. Our experiments using 60 food images showed that the proposed method achieved significantly higher accuracy in food segmentation when compared to conventional segmentation methods.

SU-E-J-109: Accurate Contour Transfer Between Different Image Modalities Using a Hybrid Deformable Image Registration and Fuzzy Connected Image Segmentation Method.

PubMed

Yang, C; Paulson, E; Li, X

2012-06-01

To develop and evaluate a tool that can improve the accuracy of contour transfer between different image modalities under challenging conditions of low image contrast and large image deformation, comparing to a few commonly used methods, for radiation treatment planning. The software tool includes the following steps and functionalities: (1) accepting input of images of different modalities, (2) converting existing contours on reference images (e.g., MRI) into delineated volumes and adjusting the intensity within the volumes to match target images (e.g., CT) intensity distribution for enhanced similarity metric, (3) registering reference and target images using appropriate deformable registration algorithms (e.g., B-spline, demons) and generate deformed contours, (4) mapping the deformed volumes on target images, calculating mean, variance, and center of mass as the initialization parameters for consecutive fuzzy connectedness (FC) image segmentation on target images, (5) generate affinity map from FC segmentation, (6) achieving final contours by modifying the deformed contours using the affinity map with a gradient distance weighting algorithm. The tool was tested with the CT and MR images of four pancreatic cancer patients acquired at the same respiration phase to minimize motion distortion. Dice's Coefficient was calculated against direct delineation on target image. Contours generated by various methods, including rigid transfer, auto-segmentation, deformable only transfer and proposed method, were compared. Fuzzy connected image segmentation needs careful parameter initialization and user involvement. Automatic contour transfer by multi-modality deformable registration leads up to 10% of accuracy improvement over the rigid transfer. Two extra proposed steps of adjusting intensity distribution and modifying the deformed contour with affinity map improve the transfer accuracy further to 14% averagely. Deformable image registration aided by contrast adjustment and fuzzy connectedness segmentation improves the contour transfer accuracy between multi-modality images, particularly with large deformation and low image contrast. © 2012 American Association of Physicists in Medicine.

Joint classification and contour extraction of large 3D point clouds

NASA Astrophysics Data System (ADS)

Hackel, Timo; Wegner, Jan D.; Schindler, Konrad

2017-08-01

We present an effective and efficient method for point-wise semantic classification and extraction of object contours of large-scale 3D point clouds. What makes point cloud interpretation challenging is the sheer size of several millions of points per scan and the non-grid, sparse, and uneven distribution of points. Standard image processing tools like texture filters, for example, cannot handle such data efficiently, which calls for dedicated point cloud labeling methods. It turns out that one of the major drivers for efficient computation and handling of strong variations in point density, is a careful formulation of per-point neighborhoods at multiple scales. This allows, both, to define an expressive feature set and to extract topologically meaningful object contours. Semantic classification and contour extraction are interlaced problems. Point-wise semantic classification enables extracting a meaningful candidate set of contour points while contours help generating a rich feature representation that benefits point-wise classification. These methods are tailored to have fast run time and small memory footprint for processing large-scale, unstructured, and inhomogeneous point clouds, while still achieving high classification accuracy. We evaluate our methods on the semantic3d.net benchmark for terrestrial laser scans with >109 points.

A Hybrid Method for Endocardial Contour Extraction of Right Ventricle in 4-Slices from 3D Echocardiography Dataset.

PubMed

Dawood, Faten A; Rahmat, Rahmita W; Kadiman, Suhaini B; Abdullah, Lili N; Zamrin, Mohd D

2014-01-01

This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.

Creation of digital contours that approach the characteristics of cartographic contours

USGS Publications Warehouse

Tyler, Dean J.; Greenlee, Susan K.

2012-01-01

The capability to easily create digital contours using commercial off-the-shelf (COTS) software has existed for decades. Out-of-the-box raw contours are suitable for many scientific applications without pre- or post-processing; however, cartographic applications typically require additional improvements. For example, raw contours generally require smoothing before placement on a map. Cartographic contours must also conform to certain spatial/logical rules; for example, contours may not cross waterbodies. The objective was to create contours that match as closely as possible the cartographic contours produced by manual methods on the 1:24,000-scale, 7.5-minute Topographic Map series. This report outlines the basic approach, describes a variety of problems that were encountered, and discusses solutions. Many of the challenges described herein were the result of imperfect input raster elevation data and the requirement to have the contours integrated with hydrographic features from the National Hydrography Dataset (NHD).

Determination of Vertical Borehole and Geological Formation Properties using the Crossed Contour Method.

PubMed

Leyde, Brian P; Klein, Sanford A; Nellis, Gregory F; Skye, Harrison

2017-03-01

This paper presents a new method called the Crossed Contour Method for determining the effective properties (borehole radius and ground thermal conductivity) of a vertical ground-coupled heat exchanger. The borehole radius is used as a proxy for the overall borehole thermal resistance. The method has been applied to both simulated and experimental borehole Thermal Response Test (TRT) data using the Duct Storage vertical ground heat exchanger model implemented in the TRansient SYstems Simulation software (TRNSYS). The Crossed Contour Method generates a parametric grid of simulated TRT data for different combinations of borehole radius and ground thermal conductivity in a series of time windows. The error between the average of the simulated and experimental bore field inlet and outlet temperatures is calculated for each set of borehole properties within each time window. Using these data, contours of the minimum error are constructed in the parameter space of borehole radius and ground thermal conductivity. When all of the minimum error contours for each time window are superimposed, the point where the contours cross (intersect) identifies the effective borehole properties for the model that most closely represents the experimental data in every time window and thus over the entire length of the experimental data set. The computed borehole properties are compared with results from existing model inversion methods including the Ground Property Measurement (GPM) software developed by Oak Ridge National Laboratory, and the Line Source Model.

Segmentation Using Multispectral Adaptive Contours

DTIC Science & Technology

2004-02-29

Geometry, University of Toronto Press, 1959. 13. R . Malladi , J. Sethian, “Image Processing via Level Set Curvature Flow,” National Academy of Science, vol...92, pp. 7046, 1995. 14. R . Malladi , J. Sethian, C. Vemuri, "Shape Modeling with Front Propagation: a Level Set Approach," IEEE Transactions on...boundary-based active contour models are reviewed in this report; geometric active contours proposed by Caselles et al. [2] and by Malladi and Sethian [13

[Validation of an improved Demons deformable registration algorithm and its application in re-contouring in 4D-CT].

PubMed

Zhen, Xin; Zhou, Ling-hong; Lu, Wen-ting; Zhang, Shu-xu; Zhou, Lu

2010-12-01

To validate the efficiency and accuracy of an improved Demons deformable registration algorithm and evaluate its application in contour recontouring in 4D-CT. To increase the additional Demons force and reallocate the bilateral forces to accelerate convergent speed, we propose a novel energy function as the similarity measure, and utilize a BFGS method for optimization to avoid specifying the numbers of iteration. Mathematical transformed deformable CT images and home-made deformable phantom were used to validate the accuracy of the improved algorithm, and its effectiveness for contour recontouring was tested. The improved algorithm showed a relatively high registration accuracy and speed when compared with the classic Demons algorithm and optical flow based method. Visual inspection of the positions and shapes of the deformed contours agreed well with the physician-drawn contours. Deformable registration is a key technique in 4D-CT, and this improved Demons algorithm for contour recontouring can significantly reduce the workload of the physicians. The registration accuracy of this method proves to be sufficient for clinical needs.

Kidney segmentation in CT sequences using graph cuts based active contours model and contextual continuity.

PubMed

Zhang, Pin; Liang, Yanmei; Chang, Shengjiang; Fan, Hailun

2013-08-01

Accurate segmentation of renal tissues in abdominal computed tomography (CT) image sequences is an indispensable step for computer-aided diagnosis and pathology detection in clinical applications. In this study, the goal is to develop a radiology tool to extract renal tissues in CT sequences for the management of renal diagnosis and treatments. In this paper, the authors propose a new graph-cuts-based active contours model with an adaptive width of narrow band for kidney extraction in CT image sequences. Based on graph cuts and contextual continuity, the segmentation is carried out slice-by-slice. In the first stage, the middle two adjacent slices in a CT sequence are segmented interactively based on the graph cuts approach. Subsequently, the deformable contour evolves toward the renal boundaries by the proposed model for the kidney extraction of the remaining slices. In this model, the energy function combining boundary with regional information is optimized in the constructed graph and the adaptive search range is determined by contextual continuity and the object size. In addition, in order to reduce the complexity of the min-cut computation, the nodes in the graph only have n-links for fewer edges. The total 30 CT images sequences with normal and pathological renal tissues are used to evaluate the accuracy and effectiveness of our method. The experimental results reveal that the average dice similarity coefficient of these image sequences is from 92.37% to 95.71% and the corresponding standard deviation for each dataset is from 2.18% to 3.87%. In addition, the average automatic segmentation time for one kidney in each slice is about 0.36 s. Integrating the graph-cuts-based active contours model with contextual continuity, the algorithm takes advantages of energy minimization and the characteristics of image sequences. The proposed method achieves effective results for kidney segmentation in CT sequences.

Method for 3D profilometry measurement based on contouring moire fringe

NASA Astrophysics Data System (ADS)

Shi, Zhiwei; Lin, Juhua

2007-12-01

3D shape measurement is one of the most active branches of optical research recently. A method of 3D profilometry measurement by the combination of Moire projection method and phase-shifting technology based on SCM (Single Chip Microcomputer) control is presented in the paper. Automatic measurement of 3D surface profiles can be carried out by applying this method with high speed and high precision.

Radiographic and anatomic basis for prostate contouring errors and methods to improve prostate contouring accuracy.

PubMed

McLaughlin, Patrick W; Evans, Cheryl; Feng, Mary; Narayana, Vrinda

2010-02-01

Use of highly conformal radiation for prostate cancer can lead to both overtreatment of surrounding normal tissues and undertreatment of the prostate itself. In this retrospective study we analyzed the radiographic and anatomic basis of common errors in computed tomography (CT) contouring and suggest methods to correct them. Three hundred patients with prostate cancer underwent CT and magnetic resonance imaging (MRI). The prostate was delineated independently on the data sets. CT and MRI contours were compared by use of deformable registration. Errors in target delineation were analyzed and methods to avoid such errors detailed. Contouring errors were identified at the prostatic apex, mid gland, and base on CT. At the apex, the genitourinary diaphragm, rectum, and anterior fascia contribute to overestimation. At the mid prostate, the anterior and lateral fasciae contribute to overestimation. At the base, the bladder and anterior fascia contribute to anterior overestimation. Transition zone hypertrophy and bladder neck variability contribute to errors of overestimation and underestimation at the superior base, whereas variable prostate-to-seminal vesicle relationships with prostate hypertrophy contribute to contouring errors at the posterior base. Most CT contouring errors can be detected by (1) inspection of a lateral view of prostate contours to detect projection from the expected globular form and (2) recognition of anatomic structures (genitourinary diaphragm) on the CT scans that are clearly visible on MRI. This study shows that many CT prostate contouring errors can be improved without direct incorporation of MRI data. Copyright 2010 Elsevier Inc. All rights reserved.

The impact of system matrix dimension on small FOV SPECT reconstruction with truncated projections

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

Chan, Chung, E-mail: Chung.Chan@yale.edu, E-mail: Chi.Liu@yale.edu; Wu, Jing; Liu, Chi, E-mail: Chung.Chan@yale.edu, E-mail: Chi.Liu@yale.edu

Purpose: A dedicated cardiac hybrid single photon emission computed tomography (SPECT)/CT scanner that uses cadmium zinc telluride detectors and multiple pinhole collimators for stationary acquisition offers many advantages. However, the impact of the reconstruction system matrix (SM) dimension on the reconstructed image quality from truncated projections and 19 angular samples acquired on this scanner has not been extensively investigated. In this study, the authors aimed to investigate the impact of the dimensions of SM and the use of body contour derived from adjunctive CT imaging as an object support in reconstruction on this scanner, in relation to background extracardiac activity.more » Methods: The authors first simulated a generic SPECT/CT system to image four NCAT phantoms with various levels of extracardiac activity and compared the reconstructions using SM in different dimensions and with/without body contour as a support for quantitative evaluations. The authors then compared the reconstructions of 18 patient studies, which were acquired on a GE Discovery NM570c scanner following injection of different radiotracers, including {sup 99m}Tc-Tetrofosmin and {sup 123}I-mIBG, comparing the scanner’s default SM that incompletely covers the body with a large SM that incorporates a patient specific full body contour. Results: The simulation studies showed that the reconstructions using a SM that only partially covers the body yielded artifacts on the edge of the field of view (FOV), overestimation of activity and increased nonuniformity in the blood pool for the phantoms with higher relative levels of extracardiac activity. However, the impact on the quantitative accuracy in the high activity region, such as the myocardium, was subtle. On the other hand, an excessively large SM that enclosed the entire body alleviated the artifacts and reduced overestimation in the blood pool, but yielded slight underestimation in myocardium and defect regions. The reconstruction using the larger SM with body contour yielded the most quantitatively accurate results in all the regions of interest for a range of uptake levels in the extracardiac regions. In patient studies, the SM incorporating patient specific body contour minimized extracardiac artifacts, yielded similar myocardial activity, lower blood pool activity, and subsequently improved myocardium-to-blood pool contrast (p < 0.0001) by an average of 7% (range 0%–18%) across all the patients, compared to the reconstructions using the scanner’s default SM. Conclusions: Their results demonstrate that using a large SM that incorporates a CT derived body contour in the reconstruction could improve quantitative accuracy within the FOV for clinical studies with high extracardiac activity.« less

Breast boundary detection with active contours

NASA Astrophysics Data System (ADS)

Balic, I.; Goyal, P.; Roy, O.; Duric, N.

2014-03-01

Ultrasound tomography is a modality that can be used to image various characteristics of the breast, such as sound speed, attenuation, and reflectivity. In the considered setup, the breast is immersed in water and scanned along the coronal axis from the chest wall to the nipple region. To improve image visualization, it is desirable to remove the water background. To this end, the 3D boundary of the breast must be accurately estimated. We present an iterative algorithm based on active contours that automatically detects the boundary of a breast using a 3D stack of attenuation images obtained from an ultrasound tomography scanner. We build upon an existing method to design an algorithm that is fast, fully automated, and reliable. We demonstrate the effectiveness of the proposed technique using clinical data sets.

Determination Of The Activity Space By The Stereometric Method

NASA Astrophysics Data System (ADS)

Deloison, Y.; Crete, N.; Mollard, R.

1980-07-01

To determine the activity space of a sitting subject, it is necessary to go beyond the mere statistical description of morphology and the knowledge of the displacement volume. An anlysis of the positions or variations of the positions of the diverse segmental elements (arms, hands, lower limbs, etc...) in the course of a given activity is required. Of the various methods used to locate quickly and accurately the spatial positions of anatomical points, stereometry makes it possible to plot the three-dimensional coordinates of any point in space in relation to a fixed trirectangle frame of reference determined by the stereome-tric measuring device. Thus, regardless of the orientation and posture of the subject, his segmental elements can be easily pin-pointed, throughout the experiment, within the space they occupy. Using this method, it is possible for a sample of operators seated at an operation station and applying either manual controls or pedals and belonging to a population statistically defined from the data collected and the analyses produced by the anthropometric study to determine a contour line of reach capability marking out the usable working space and to know, within this working space, a contour line of preferential activity that is limited, in space, by the whole range of optimal reach capability of all the subjects.

Comparison of [{sup 11}C]choline Positron Emission Tomography With T2- and Diffusion-Weighted Magnetic Resonance Imaging for Delineating Malignant Intraprostatic Lesions

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

Chang, Joe H.; University of Melbourne, Victoria; Lim Joon, Daryl

2015-06-01

Purpose: The purpose of this study was to compare the accuracy of [{sup 11}C]choline positron emission tomography (CHOL-PET) with that of the combination of T2-weighted and diffusion-weighted (T2W/DW) magnetic resonance imaging (MRI) for delineating malignant intraprostatic lesions (IPLs) for guiding focal therapies and to investigate factors predicting the accuracy of CHOL-PET. Methods and Materials: This study included 21 patients who underwent CHOL-PET and T2W/DW MRI prior to radical prostatectomy. Two observers manually delineated IPL contours for each scan, and automatic IPL contours were generated on CHOL-PET based on varying proportions of the maximum standardized uptake value (SUV). IPLs identified onmore » prostatectomy specimens defined reference standard contours. The imaging-based contours were compared with the reference standard contours using Dice similarity coefficient (DSC), and sensitivity and specificity values. Factors that could potentially predict the DSC of the best contouring method were analyzed using linear models. Results: The best automatic contouring method, 60% of the maximum SUV (SUV{sub 60}) , had similar correlations (DSC: 0.59) with the manual PET contours (DSC: 0.52, P=.127) and significantly better correlations than the manual MRI contours (DSC: 0.37, P<.001). The sensitivity and specificity values were 72% and 71% for SUV{sub 60}; 53% and 86% for PET manual contouring; and 28% and 92% for MRI manual contouring. The tumor volume and transition zone pattern could independently predict the accuracy of CHOL-PET. Conclusions: CHOL-PET is superior to the combination of T2W/DW MRI for delineating IPLs. The accuracy of CHOL-PET is insufficient for gland-sparing focal therapies but may be accurate enough for focal boost therapies. The transition zone pattern is a new classification that may predict how well CHOL-PET delineates IPLs.« less

Active illuminated space object imaging and tracking simulation

NASA Astrophysics Data System (ADS)

Yue, Yufang; Xie, Xiaogang; Luo, Wen; Zhang, Feizhou; An, Jianzhu

2016-10-01

Optical earth imaging simulation of a space target in orbit and it's extraction in laser illumination condition were discussed. Based on the orbit and corresponding attitude of a satellite, its 3D imaging rendering was built. General simulation platform was researched, which was adaptive to variable 3D satellite models and relative position relationships between satellite and earth detector system. Unified parallel projection technology was proposed in this paper. Furthermore, we denoted that random optical distribution in laser-illuminated condition was a challenge for object discrimination. Great randomicity of laser active illuminating speckles was the primary factor. The conjunction effects of multi-frame accumulation process and some tracking methods such as Meanshift tracking, contour poid, and filter deconvolution were simulated. Comparison of results illustrates that the union of multi-frame accumulation and contour poid was recommendable for laser active illuminated images, which had capacities of high tracking precise and stability for multiple object attitudes.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-01

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

Augmenting atlas-based liver segmentation for radiotherapy treatment planning by incorporating image features proximal to the atlas contours.

PubMed

Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng; Yin, Yong; Ibragimov, Bulat; Xing, Lei

2017-01-07

Atlas-based segmentation utilizes a library of previously delineated contours of similar cases to facilitate automatic segmentation. The problem, however, remains challenging because of limited information carried by the contours in the library. In this studying, we developed a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. This study presented a new concept of atlas based segmentation method. Instead of using the complete volume of the target organs, only information along the organ contours from the atlas images was used for guiding segmentation of the new image. In setting up an atlas-based library, we included not only the coordinates of contour points, but also the image features adjacent to the contour. In this work, 139 CT images with normal appearing livers collected for radiotherapy treatment planning were used to construct the library. The CT images within the library were first registered to each other using affine registration. The nonlinear narrow shell was generated alongside the object contours of registered images. Matching voxels were selected inside common narrow shell image features of a library case and a new case using a speed-up robust features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the new image by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy optimization within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by physicians. A novel atlas-based segmentation technique with inclusion of neighborhood image features through the introduction of a narrow-shell surrounding the target objects was established. Application of the technique to 30 liver cases suggested that the technique was capable to reliably segment liver cases from CT, 4D-CT, and CBCT images with little human interaction. The accuracy and speed of the proposed method are quantitatively validated by comparing automatic segmentation results with the manual delineation results. The Jaccard similarity metric between the automatically generated liver contours obtained by the proposed method and the physician delineated results are on an average 90%-96% for planning images. Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. The proposed mountainous narrow shell atlas based method can achieve efficient automatic liver propagation for CT, 4D-CT and CBCT images with following treatment planning and should find widespread application in future treatment planning systems.

3D Filament Network Segmentation with Multiple Active Contours

NASA Astrophysics Data System (ADS)

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2014-03-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Novel active contour model based on multi-variate local Gaussian distribution for local segmentation of MR brain images

NASA Astrophysics Data System (ADS)

Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong

2017-12-01

Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Salient contour extraction from complex natural scene in night vision image

NASA Astrophysics Data System (ADS)

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lian-fa

2014-03-01

The theory of center-surround interaction in non-classical receptive field can be applied in night vision information processing. In this work, an optimized compound receptive field modulation method is proposed to extract salient contour from complex natural scene in low-light-level (LLL) and infrared images. The kernel idea is that multi-feature analysis can recognize the inhomogeneity in modulatory coverage more accurately and that center and surround with the grouping structure satisfying Gestalt rule deserves high connection-probability. Computationally, a multi-feature contrast weighted inhibition model is presented to suppress background and lower mutual inhibition among contour elements; a fuzzy connection facilitation model is proposed to achieve the enhancement of contour response, the connection of discontinuous contour and the further elimination of randomly distributed noise and texture; a multi-scale iterative attention method is designed to accomplish dynamic modulation process and extract contours of targets in multi-size. This work provides a series of biologically motivated computational visual models with high-performance for contour detection from cluttered scene in night vision images.

Automatic segmentation of equine larynx for diagnosis of laryngeal hemiplegia

NASA Astrophysics Data System (ADS)

Salehin, Md. Musfequs; Zheng, Lihong; Gao, Junbin

2013-10-01

This paper presents an automatic segmentation method for delineation of the clinically significant contours of the equine larynx from an endoscopic image. These contours are used to diagnose the most common disease of horse larynx laryngeal hemiplegia. In this study, hierarchal structured contour map is obtained by the state-of-the-art segmentation algorithm, gPb-OWT-UCM. The conic-shaped outer boundary of equine larynx is extracted based on Pascal's theorem. Lastly, Hough Transformation method is applied to detect lines related to the edges of vocal folds. The experimental results show that the proposed approach has better performance in extracting the targeted contours of equine larynx than the results of using only the gPb-OWT-UCM method.

Improved approach to quantitative cardiac volumetrics using automatic thresholding and manual trimming: a cardiovascular MRI study.

PubMed

Rayarao, Geetha; Biederman, Robert W W; Williams, Ronald B; Yamrozik, June A; Lombardi, Richard; Doyle, Mark

2018-01-01

To establish the clinical validity and accuracy of automatic thresholding and manual trimming (ATMT) by comparing the method with the conventional contouring method for in vivo cardiac volume measurements. CMR was performed on 40 subjects (30 patients and 10 controls) using steady-state free precession cine sequences with slices oriented in the short-axis and acquired contiguously from base to apex. Left ventricular (LV) volumes, end-diastolic volume, end-systolic volume, and stroke volume (SV) were obtained with ATMT and with the conventional contouring method. Additionally, SV was measured independently using CMR phase velocity mapping (PVM) of the aorta for validation. Three methods of calculating SV were compared by applying Bland-Altman analysis. The Bland-Altman standard deviation of variation (SD) and offset bias for LV SV for the three sets of data were: ATMT-PVM (7.65, [Formula: see text]), ATMT-contours (7.85, [Formula: see text]), and contour-PVM (11.01, 4.97), respectively. Equating the observed range to the error contribution of each approach, the error magnitude of ATMT:PVM:contours was in the ratio 1:2.4:2.5. Use of ATMT for measuring ventricular volumes accommodates trabeculae and papillary structures more intuitively than contemporary contouring methods. This results in lower variation when analyzing cardiac structure and function and consequently improved accuracy in assessing chamber volumes.

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

NASA Astrophysics Data System (ADS)

Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

2016-03-01

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

Novel Computerized Method for Measurement of Retinal Vessel Diameters

PubMed Central

Guedri, Hichem; Ben Abdallah, Mariem; Echouchene, Fraj; Belmabrouk, Hafedh

2017-01-01

Several clinical studies reveal the relationship between alterations in the topologies of the human retinal blood vessel, the outcrop and the disease evolution, such as diabetic retinopathy, hypertensive retinopathy, and macular degeneration. Indeed, the detection of these vascular changes always has gaps. In addition, the manual steps are slow, which may be subjected to a bias of the perceiver. However, we can overcome these troubles using computer algorithms that are quicker and more accurate. This paper presents and investigates a novel method for measuring the blood vessel diameter in the retinal image. The proposed method is based on a thresholding segmentation and thinning step, followed by the characteristic point determination step by the Douglas-Peucker algorithm. Thereafter, it uses the active contours to detect vessel contour. Finally, Heron’s Formula is applied to assure the calculation of vessel diameter. The obtained results for six sample images showed that the proposed method generated less errors compared to other techniques, which confirms the high performance of the proposed method. PMID:28536355

Small Bowel Dose Parameters Predicting Grade ≥3 Acute Toxicity in Rectal Cancer Patients Treated With Neoadjuvant Chemoradiation: An Independent Validation Study Comparing Peritoneal Space Versus Small Bowel Loop Contouring Techniques

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

Banerjee, Robyn, E-mail: robynbanerjee@gmail.com; Chakraborty, Santam; Nygren, Ian

Purpose: To determine whether volumes based on contours of the peritoneal space can be used instead of individual small bowel loops to predict for grade ≥3 acute small bowel toxicity in patients with rectal cancer treated with neoadjuvant chemoradiation therapy. Methods and Materials: A standardized contouring method was developed for the peritoneal space and retrospectively applied to the radiation treatment plans of 67 patients treated with neoadjuvant chemoradiation therapy for rectal cancer. Dose-volume histogram (DVH) data were extracted and analyzed against patient toxicity. Receiver operating characteristic analysis and logistic regression were carried out for both contouring methods. Results: Grade ≥3more » small bowel toxicity occurred in 16% (11/67) of patients in the study. A highly significant dose-volume relationship between small bowel irradiation and acute small bowel toxicity was supported by the use of both small bowel loop and peritoneal space contouring techniques. Receiver operating characteristic analysis demonstrated that, for both contouring methods, the greatest sensitivity for predicting toxicity was associated with the volume receiving between 15 and 25 Gy. Conclusion: DVH analysis of peritoneal space volumes accurately predicts grade ≥3 small bowel toxicity in patients with rectal cancer receiving neoadjuvant chemoradiation therapy, suggesting that the contours of the peritoneal space provide a reasonable surrogate for the contours of individual small bowel loops. The study finds that a small bowel V15 less than 275 cc and a peritoneal space V15 less than 830 cc are associated with a less than 10% risk of grade ≥3 acute toxicity.« less

SU-C-BRA-05: Delineating High-Dose Clinical Target Volumes for Head and Neck Tumors Using Machine Learning Algorithms

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

Cardenas, C; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Wong, A

Purpose: To develop and test population-based machine learning algorithms for delineating high-dose clinical target volumes (CTVs) in H&N tumors. Automating and standardizing the contouring of CTVs can reduce both physician contouring time and inter-physician variability, which is one of the largest sources of uncertainty in H&N radiotherapy. Methods: Twenty-five node-negative patients treated with definitive radiotherapy were selected (6 right base of tongue, 11 left and 9 right tonsil). All patients had GTV and CTVs manually contoured by an experienced radiation oncologist prior to treatment. This contouring process, which is driven by anatomical, pathological, and patient specific information, typically results inmore » non-uniform margin expansions about the GTV. Therefore, we tested two methods to delineate high-dose CTV given a manually-contoured GTV: (1) regression-support vector machines(SVM) and (2) classification-SVM. These models were trained and tested on each patient group using leave-one-out cross-validation. The volume difference(VD) and Dice similarity coefficient(DSC) between the manual and auto-contoured CTV were calculated to evaluate the results. Distances from GTV-to-CTV were computed about each patient’s GTV and these distances, in addition to distances from GTV to surrounding anatomy in the expansion direction, were utilized in the regression-SVM method. The classification-SVM method used categorical voxel-information (GTV, selected anatomical structures, else) from a 3×3×3cm3 ROI centered about the voxel to classify voxels as CTV. Results: Volumes for the auto-contoured CTVs ranged from 17.1 to 149.1cc and 17.4 to 151.9cc; the average(range) VD between manual and auto-contoured CTV were 0.93 (0.48–1.59) and 1.16(0.48–1.97); while average(range) DSC values were 0.75(0.59–0.88) and 0.74(0.59–0.81) for the regression-SVM and classification-SVM methods, respectively. Conclusion: We developed two novel machine learning methods to delineate high-dose CTV for H&N patients. Both methods showed promising results that hint to a solution to the standardization of the contouring process of clinical target volumes. Varian Medical Systems grant.« less

Determination of Vertical Borehole and Geological Formation Properties using the Crossed Contour Method

PubMed Central

Leyde, Brian P.; Klein, Sanford A; Nellis, Gregory F.; Skye, Harrison

2017-01-01

This paper presents a new method called the Crossed Contour Method for determining the effective properties (borehole radius and ground thermal conductivity) of a vertical ground-coupled heat exchanger. The borehole radius is used as a proxy for the overall borehole thermal resistance. The method has been applied to both simulated and experimental borehole Thermal Response Test (TRT) data using the Duct Storage vertical ground heat exchanger model implemented in the TRansient SYstems Simulation software (TRNSYS). The Crossed Contour Method generates a parametric grid of simulated TRT data for different combinations of borehole radius and ground thermal conductivity in a series of time windows. The error between the average of the simulated and experimental bore field inlet and outlet temperatures is calculated for each set of borehole properties within each time window. Using these data, contours of the minimum error are constructed in the parameter space of borehole radius and ground thermal conductivity. When all of the minimum error contours for each time window are superimposed, the point where the contours cross (intersect) identifies the effective borehole properties for the model that most closely represents the experimental data in every time window and thus over the entire length of the experimental data set. The computed borehole properties are compared with results from existing model inversion methods including the Ground Property Measurement (GPM) software developed by Oak Ridge National Laboratory, and the Line Source Model. PMID:28785125

Improved operator agreement and efficiency using the minimum area contour change method for delineation of hyperintense multiple sclerosis lesions on FLAIR MRI

PubMed Central

2013-01-01

Background Activity of disease in patients with multiple sclerosis (MS) is monitored by detecting and delineating hyper-intense lesions on MRI scans. The Minimum Area Contour Change (MACC) algorithm has been created with two main goals: a) to improve inter-operator agreement on outlining regions of interest (ROIs) and b) to automatically propagate longitudinal ROIs from the baseline scan to a follow-up scan. Methods The MACC algorithm first identifies an outer bound for the solution path, forms a high number of iso-contour curves based on equally spaced contour values, and then selects the best contour value to outline the lesion. The MACC software was tested on a set of 17 FLAIR MRI images evaluated by a pair of human experts and a longitudinal dataset of 12 pairs of T2-weighted Fluid Attenuated Inversion Recovery (FLAIR) images that had lesion analysis ROIs drawn by a single expert operator. Results In the tests where two human experts evaluated the same MRI images, the MACC program demonstrated that it could markedly reduce inter-operator outline error. In the longitudinal part of the study, the MACC program created ROIs on follow-up scans that were in close agreement to the original expert’s ROIs. Finally, in a post-hoc analysis of 424 follow-up scans 91% of propagated MACC were accepted by an expert and only 9% of the final accepted ROIS had to be created or edited by the expert. Conclusion When used with an expert operator's verification of automatically created ROIs, MACC can be used to improve inter- operator agreement and decrease analysis time, which should improve data collected and analyzed in multicenter clinical trials. PMID:24004511

Detecting the Edge of the Tongue: A Tutorial

ERIC Educational Resources Information Center

Iskarous, Khalil

2005-01-01

The goal of this paper is to provide a tutorial introduction to the topic of edge detection of the tongue from ultrasound scans for researchers in speech science and phonetics. The method introduced here is Active Contours (also called snakes), a method for searching for an edge, assuming that it is a smooth curve in the image data. The advantage…

Comparative Study With New Accuracy Metrics for Target Volume Contouring in PET Image Guided Radiation Therapy

PubMed Central

Shepherd, T; Teras, M; Beichel, RR; Boellaard, R; Bruynooghe, M; Dicken, V; Gooding, MJ; Julyan, PJ; Lee, JA; Lefèvre, S; Mix, M; Naranjo, V; Wu, X; Zaidi, H; Zeng, Z; Minn, H

2017-01-01

The impact of positron emission tomography (PET) on radiation therapy is held back by poor methods of defining functional volumes of interest. Many new software tools are being proposed for contouring target volumes but the different approaches are not adequately compared and their accuracy is poorly evaluated due to the ill-definition of ground truth. This paper compares the largest cohort to date of established, emerging and proposed PET contouring methods, in terms of accuracy and variability. We emphasize spatial accuracy and present a new metric that addresses the lack of unique ground truth. Thirty methods are used at 13 different institutions to contour functional volumes of interest in clinical PET/CT and a custom-built PET phantom representing typical problems in image guided radiotherapy. Contouring methods are grouped according to algorithmic type, level of interactivity and how they exploit structural information in hybrid images. Experiments reveal benefits of high levels of user interaction, as well as simultaneous visualization of CT images and PET gradients to guide interactive procedures. Method-wise evaluation identifies the danger of over-automation and the value of prior knowledge built into an algorithm. PMID:22692898

Detection of Cardiac Quiescence from B-Mode Echocardiography Using a Correlation-Based Frame-to-Frame Deviation Measure

PubMed Central

Mcclellan, James H.; Ravichandran, Lakshminarayan; Tridandapani, Srini

2013-01-01

Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of many imaging modalities, including computed tomography coronary angiography (CTCA). Synchronous electrocardiography (ECG) and echocardiography data were obtained from 10 healthy human subjects (four male, six female, 23–45 years) and the interventricular septum (IVS) was observed using the apical four-chamber echocardiographic view. The velocity of the IVS was derived from active contour tracking and verified using tissue Doppler imaging echocardiography methods. In turn, the frame-to-frame deviation methods for identifying quiescence of the IVS were verified using active contour tracking. The timing of the diastolic quiescent phase was found to exhibit both inter- and intra-subject variability, suggesting that the current method of CTCA gating based on the ECG is suboptimal and that gating based on signals derived from cardiac motion are likely more accurate in predicting quiescence for cardiac imaging. Two robust and efficient methods for identifying cardiac quiescent phases from B-mode echocardiographic data were developed and verified. The methods presented in this paper will be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality. PMID:26609501

The Case of the Flooded Island.

ERIC Educational Resources Information Center

McGinnis, Randy

1989-01-01

Presents a hands-on activity for bridging the gap between the exposure to three-dimensional topography and contour mapping. This activity describes the use of a volcano-making activity and offers laboratory sheets that can be duplicated for student use. Argues that students learn the concept of contour mapping better in a guided fashion that holds…

A Method for Producing a Shaped Contour Radiation Pattern Using a Single Shaped Reflector and a Single Feed

NASA Technical Reports Server (NTRS)

Cherrette, A. R.; Lee, S. W.; Acosta, R. J.

1988-01-01

Eliminating the corporate feed network in shaped contour beam antennas will reduce the expense, weight, and RF loss of the antenna system. One way of producing a shaped contour beam without using a feed network is to use a single shaped reflector with a single feed element. For a prescribed contour beam and feed, an optimization method for designing the reflector shape is given. As a design example, a shaped reflector is designed to produce a continental U.S. coverage (CONUS) beam. The RF performance of the shaped reflector is then verified by physical optics.

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 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

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

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

Chen, H; Tan, J; Kavanaugh, J

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-timemore » and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.« less

Effects of inverting contour and features on processing for static and dynamic face perception: an MEG study.

PubMed

Miki, Kensaku; Takeshima, Yasuyuki; Watanabe, Shoko; Honda, Yukiko; Kakigi, Ryusuke

2011-04-06

We investigated the effects of inverting facial contour (hair and chin) and features (eyes, nose and mouth) on processing for static and dynamic face perception using magnetoencephalography (MEG). We used apparent motion, in which the first stimulus (S1) was replaced by a second stimulus (S2) with no interstimulus interval and subjects perceived visual motion, and presented three conditions as follows: (1) U&U: Upright contour and Upright features, (2) U&I: Upright contour and Inverted features, and (3) I&I: Inverted contour and Inverted features. In static face perception (S1 onset), the peak latency of the fusiform area's activity, which was related to static face perception, was significantly longer for U&I and I&I than for U&U in the right hemisphere and for U&I than for U&U and I&I in the left. In dynamic face perception (S2 onset), the strength (moment) of the occipitotemporal area's activity, which was related to dynamic face perception, was significantly larger for I&I than for U&U and U&I in the right hemisphere, but not the left. These results can be summarized as follows: (1) in static face perception, the activity of the right fusiform area was more affected by the inversion of features while that of the left fusiform area was more affected by the disruption of the spatial relation between the contour and features, and (2) in dynamic face perception, the activity of the right occipitotemporal area was affected by the inversion of the facial contour. Copyright © 2011 Elsevier B.V. All rights reserved.

Reproducibility of isopach data and estimates of dispersal and eruption volumes

NASA Astrophysics Data System (ADS)

Klawonn, M.; Houghton, B. F.; Swanson, D.; Fagents, S. A.; Wessel, P.; Wolfe, C. J.

2012-12-01

Total erupted volume and deposit thinning relationships are key parameters in characterizing explosive eruptions and evaluating the potential risk from a volcano as well as inputs to volcanic plume models. Volcanologists most commonly estimate these parameters by hand-contouring deposit data, then representing these contours in thickness versus square root area plots, fitting empirical laws to the thinning relationships and integrating over the square root area to arrive at volume estimates. In this study we analyze the extent to which variability in hand-contouring thickness data for pyroclastic fall deposits influences the resulting estimates and investigate the effects of different fitting laws. 96 volcanologists (3% MA students, 19% PhD students, 20% postdocs, 27% professors, and 30% professional geologists) from 11 countries (Australia, Ecuador, France, Germany, Iceland, Italy, Japan, New Zealand, Switzerland, UK, USA) participated in our study and produced hand-contours on identical maps using our unpublished thickness measurements of the Kilauea Iki 1959 fall deposit. We computed volume estimates by (A) integrating over a surface fitted through the contour lines, as well as using the established methods of integrating over the thinning relationships of (B) an exponential fit with one to three segments, (C) a power law fit, and (D) a Weibull function fit. To focus on the differences from the hand-contours of the well constrained deposit and eliminate the effects of extrapolations to great but unmeasured thicknesses near the vent, we removed the volume contribution of the near vent deposit (defined as the deposit above 3.5 m) from the volume estimates. The remaining volume approximates to 1.76 *106 m3 (geometric mean for all methods) with maximum and minimum estimates of 2.5 *106 m3 and 1.1 *106 m3. Different integration methods of identical isopach maps result in volume estimate differences of up to 50% and, on average, maximum variation between integration methods of 14%. Volume estimates with methods (A), (C) and (D) show strong correlation (r = 0.8 to r = 0.9), while correlation of (B) with the other methods is weaker (r = 0.2 to r = 0.6) and correlation between (B) and (C) is not statistically significant. We find that the choice of larger maximum contours leads to smaller volume estimates due to method (C), but larger estimates with the other methods. We do not find statistically significant correlation between volume estimations and participants experience level, number of chosen contour levels, nor smoothness of contours. Overall, application of the different methods to the same maps leads to similar mean volume estimates, but the different methods show different dependencies and varying spread of volume estimates. The results indicate that these key parameters are less critically dependent on the operator and their choices of contour values, intervals etc., and more sensitive to the selection of technique to integrate these data.

Constraint factor graph cut-based active contour method for automated cellular image segmentation in RNAi screening.

PubMed

Chen, C; Li, H; Zhou, X; Wong, S T C

2008-05-01

Image-based, high throughput genome-wide RNA interference (RNAi) experiments are increasingly carried out to facilitate the understanding of gene functions in intricate biological processes. Automated screening of such experiments generates a large number of images with great variations in image quality, which makes manual analysis unreasonably time-consuming. Therefore, effective techniques for automatic image analysis are urgently needed, in which segmentation is one of the most important steps. This paper proposes a fully automatic method for cells segmentation in genome-wide RNAi screening images. The method consists of two steps: nuclei and cytoplasm segmentation. Nuclei are extracted and labelled to initialize cytoplasm segmentation. Since the quality of RNAi image is rather poor, a novel scale-adaptive steerable filter is designed to enhance the image in order to extract long and thin protrusions on the spiky cells. Then, constraint factor GCBAC method and morphological algorithms are combined to be an integrated method to segment tight clustered cells. Compared with the results obtained by using seeded watershed and the ground truth, that is, manual labelling results by experts in RNAi screening data, our method achieves higher accuracy. Compared with active contour methods, our method consumes much less time. The positive results indicate that the proposed method can be applied in automatic image analysis of multi-channel image screening data.

Methodology for Image-Based Reconstruction of Ventricular Geometry for Patient-Specific Modeling of Cardiac Electrophysiology

PubMed Central

Prakosa, A.; Malamas, P.; Zhang, S.; Pashakhanloo, F.; Arevalo, H.; Herzka, D. A.; Lardo, A.; Halperin, H.; McVeigh, E.; Trayanova, N.; Vadakkumpadan, F.

2014-01-01

Patient-specific modeling of ventricular electrophysiology requires an interpolated reconstruction of the 3-dimensional (3D) geometry of the patient ventricles from the low-resolution (Lo-res) clinical images. The goal of this study was to implement a processing pipeline for obtaining the interpolated reconstruction, and thoroughly evaluate the efficacy of this pipeline in comparison with alternative methods. The pipeline implemented here involves contouring the epi- and endocardial boundaries in Lo-res images, interpolating the contours using the variational implicit functions method, and merging the interpolation results to obtain the ventricular reconstruction. Five alternative interpolation methods, namely linear, cubic spline, spherical harmonics, cylindrical harmonics, and shape-based interpolation were implemented for comparison. In the thorough evaluation of the processing pipeline, Hi-res magnetic resonance (MR), computed tomography (CT), and diffusion tensor (DT) MR images from numerous hearts were used. Reconstructions obtained from the Hi-res images were compared with the reconstructions computed by each of the interpolation methods from a sparse sample of the Hi-res contours, which mimicked Lo-res clinical images. Qualitative and quantitative comparison of these ventricular geometry reconstructions showed that the variational implicit functions approach performed better than others. Additionally, the outcomes of electrophysiological simulations (sinus rhythm activation maps and pseudo-ECGs) conducted using models based on the various reconstructions were compared. These electrophysiological simulations demonstrated that our implementation of the variational implicit functions-based method had the best accuracy. PMID:25148771

An automated workflow for patient-specific quality control of contour propagation

NASA Astrophysics Data System (ADS)

Beasley, William J.; McWilliam, Alan; Slevin, Nicholas J.; Mackay, Ranald I.; van Herk, Marcel

2016-12-01

Contour propagation is an essential component of adaptive radiotherapy, but current contour propagation algorithms are not yet sufficiently accurate to be used without manual supervision. Manual review of propagated contours is time-consuming, making routine implementation of real-time adaptive radiotherapy unrealistic. Automated methods of monitoring the performance of contour propagation algorithms are therefore required. We have developed an automated workflow for patient-specific quality control of contour propagation and validated it on a cohort of head and neck patients, on which parotids were outlined by two observers. Two types of error were simulated—mislabelling of contours and introducing noise in the scans before propagation. The ability of the workflow to correctly predict the occurrence of errors was tested, taking both sets of observer contours as ground truth, using receiver operator characteristic analysis. The area under the curve was 0.90 and 0.85 for the observers, indicating good ability to predict the occurrence of errors. This tool could potentially be used to identify propagated contours that are likely to be incorrect, acting as a flag for manual review of these contours. This would make contour propagation more efficient, facilitating the routine implementation of adaptive radiotherapy.

Joint Data Management for MOVINT Data-to-Decision Making

DTIC Science & Technology

2011-07-01

flux tensor , aligned motion history images, and related approaches have been shown to be versatile approaches [12, 16, 17, 18]. Scaling these...methods include voting , neural networks, fuzzy logic, neuro-dynamic programming, support vector machines, Bayesian and Dempster-Shafer methods. One way...Information Fusion, 2010. [16] F. Bunyak, K. Palaniappan, S. K. Nath, G. Seetharaman, “Flux tensor constrained geodesic active contours with sensor fusion

Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer

NASA Astrophysics Data System (ADS)

Gardner, Stephen J.; Wen, Ning; Kim, Jinkoo; Liu, Chang; Pradhan, Deepak; Aref, Ibrahim; Cattaneo, Richard, II; Vance, Sean; Movsas, Benjamin; Chetty, Indrin J.; Elshaikh, Mohamed A.

2015-06-01

This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient—0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance—4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)—1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation—2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on CBCT, we conclude that contours generated with B-Spline DIR require physician review and editing if they are to be used in the clinic.

A method for smoothing segmented lung boundary in chest CT images

NASA Astrophysics Data System (ADS)

Yim, Yeny; Hong, Helen

2007-03-01

To segment low density lung regions in chest CT images, most of methods use the difference in gray-level value of pixels. However, radiodense pulmonary vessels and pleural nodules that contact with the surrounding anatomy are often excluded from the segmentation result. To smooth lung boundary segmented by gray-level processing in chest CT images, we propose a new method using scan line search. Our method consists of three main steps. First, lung boundary is extracted by our automatic segmentation method. Second, segmented lung contour is smoothed in each axial CT slice. We propose a scan line search to track the points on lung contour and find rapidly changing curvature efficiently. Finally, to provide consistent appearance between lung contours in adjacent axial slices, 2D closing in coronal plane is applied within pre-defined subvolume. Our method has been applied for performance evaluation with the aspects of visual inspection, accuracy and processing time. The results of our method show that the smoothness of lung contour was considerably increased by compensating for pulmonary vessels and pleural nodules.

Research on feature extraction techniques of Hainan Li brocade pattern

NASA Astrophysics Data System (ADS)

Zhou, Yuping; Chen, Fuqiang; Zhou, Yuhua

2016-03-01

Hainan Li brocade skills has been listed as world non-material cultural heritage preservation, therefore, the research on Hainan Li brocade patterns plays an important role in Li brocade culture inheritance. The meaning of Li brocade patterns was analyzed and the shape feature extraction techniques to original Li brocade patterns were advanced in this paper, based on the contour tracking algorithm. First, edge detection was made on the design patterns, and then the morphological closing operation was used to smooth the image, and finally contour tracking was used to extract the outer contours of Li brocade patterns. The extracted contour features were processed by means of morphology, and digital characteristics of contours are obtained by invariant moments. At last, different patterns of Li brocade design are briefly analyzed according to the digital characteristics. The results showed that the pattern extraction method to Li brocade pattern shapes is feasible and effective according to above method.

Novel real-time tumor-contouring method using deep learning to prevent mistracking in X-ray fluoroscopy.

PubMed

Terunuma, Toshiyuki; Tokui, Aoi; Sakae, Takeji

2018-03-01

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

Measurement of large steel plates based on linear scan structured light scanning

NASA Astrophysics Data System (ADS)

Xiao, Zhitao; Li, Yaru; Lei, Geng; Xi, Jiangtao

2018-01-01

A measuring method based on linear structured light scanning is proposed to achieve the accurate measurement of the complex internal shape of large steel plates. Firstly, by using a calibration plate with round marks, an improved line scanning calibration method is designed. The internal and external parameters of camera are determined through the calibration method. Secondly, the images of steel plates are acquired by line scan camera. Then the Canny edge detection method is used to extract approximate contours of the steel plate images, the Gauss fitting algorithm is used to extract the sub-pixel edges of the steel plate contours. Thirdly, for the problem of inaccurate restoration of contour size, by measuring the distance between adjacent points in the grid of known dimensions, the horizontal and vertical error curves of the images are obtained. Finally, these horizontal and vertical error curves can be used to correct the contours of steel plates, and then combined with the calibration parameters of internal and external, the size of these contours can be calculated. The experiments results demonstrate that the proposed method can achieve the error of 1 mm/m in 1.2m×2.6m field of view, which has satisfied the demands of industrial measurement.

Surface Curvatures Computation from Equidistance Contours

NASA Astrophysics Data System (ADS)

Tanaka, Hiromi T.; Kling, Olivier; Lee, Daniel T. L.

1990-03-01

The subject of our research is on the 3D shape representation problem for a special class of range image, one where the natural mode of the acquired range data is in the form of equidistance contours, as exemplified by a moire interferometry range system. In this paper we present a novel surface curvature computation scheme that directly computes the surface curvatures (the principal curvatures, Gaussian curvature and mean curvature) from the equidistance contours without any explicit computations or implicit estimates of partial derivatives. We show how the special nature of the equidistance contours, specifically, the dense information of the surface curves in the 2D contour plane, turns into an advantage for the computation of the surface curvatures. The approach is based on using simple geometric construction to obtain the normal sections and the normal curvatures. This method is general and can be extended to any dense range image data. We show in details how this computation is formulated and give an analysis on the error bounds of the computation steps showing that the method is stable. Computation results on real equidistance range contours are also shown.

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Generic method for automatic bladder segmentation on cone beam CT using a patient-specific bladder shape model

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

Schoot, A. J. A. J. van de, E-mail: a.j.schootvande@amc.uva.nl; Schooneveldt, G.; Wognum, S.

Purpose: The aim of this study is to develop and validate a generic method for automatic bladder segmentation on cone beam computed tomography (CBCT), independent of gender and treatment position (prone or supine), using only pretreatment imaging data. Methods: Data of 20 patients, treated for tumors in the pelvic region with the entire bladder visible on CT and CBCT, were divided into four equally sized groups based on gender and treatment position. The full and empty bladder contour, that can be acquired with pretreatment CT imaging, were used to generate a patient-specific bladder shape model. This model was used tomore » guide the segmentation process on CBCT. To obtain the bladder segmentation, the reference bladder contour was deformed iteratively by maximizing the cross-correlation between directional grey value gradients over the reference and CBCT bladder edge. To overcome incorrect segmentations caused by CBCT image artifacts, automatic adaptations were implemented. Moreover, locally incorrect segmentations could be adapted manually. After each adapted segmentation, the bladder shape model was expanded and new shape patterns were calculated for following segmentations. All available CBCTs were used to validate the segmentation algorithm. The bladder segmentations were validated by comparison with the manual delineations and the segmentation performance was quantified using the Dice similarity coefficient (DSC), surface distance error (SDE) and SD of contour-to-contour distances. Also, bladder volumes obtained by manual delineations and segmentations were compared using a Bland-Altman error analysis. Results: The mean DSC, mean SDE, and mean SD of contour-to-contour distances between segmentations and manual delineations were 0.87, 0.27 cm and 0.22 cm (female, prone), 0.85, 0.28 cm and 0.22 cm (female, supine), 0.89, 0.21 cm and 0.17 cm (male, supine) and 0.88, 0.23 cm and 0.17 cm (male, prone), respectively. Manual local adaptations improved the segmentation results significantly (p < 0.01) based on DSC (6.72%) and SD of contour-to-contour distances (0.08 cm) and decreased the 95% confidence intervals of the bladder volume differences. Moreover, expanding the shape model improved the segmentation results significantly (p < 0.01) based on DSC and SD of contour-to-contour distances. Conclusions: This patient-specific shape model based automatic bladder segmentation method on CBCT is accurate and generic. Our segmentation method only needs two pretreatment imaging data sets as prior knowledge, is independent of patient gender and patient treatment position and has the possibility to manually adapt the segmentation locally.« less

Matching shapes with self-intersections: application to leaf classification.

PubMed

Mokhtarian, Farzin; Abbasi, Sadegh

2004-05-01

We address the problem of two-dimensional (2-D) shape representation and matching in presence of self-intersection for large image databases. This may occur when part of an object is hidden behind another part and results in a darker section in the gray level image of the object. The boundary contour of the object must include the boundary of this part which is entirely inside the outline of the object. The Curvature Scale Space (CSS) image of a shape is a multiscale organization of its inflection points as it is smoothed. The CSS-based shape representation method has been selected for MPEG-7 standardization. We study the effects of contour self-intersection on the Curvature Scale Space image. When there is no self-intersection, the CSS image contains several arch shape contours, each related to a concavity or a convexity of the shape. Self intersections create contours with minima as well as maxima in the CSS image. An efficient shape representation method has been introduced in this paper which describes a shape using the maxima as well as the minima of its CSS contours. This is a natural generalization of the conventional method which only includes the maxima of the CSS image contours. The conventional matching algorithm has also been modified to accommodate the new information about the minima. The method has been successfully used in a real world application to find, for an unknown leaf, similar classes from a database of classified leaf images representing different varieties of chrysanthemum. For many classes of leaves, self-intersection is inevitable during the scanning of the image. Therefore the original contributions of this paper is the generalization of the Curvature Scale Space representation to the class of 2-D contours with self-intersection, and its application to the classification of Chrysanthemum leaves.

A 3D Hermite-based multiscale local active contour method with elliptical shape constraints for segmentation of cardiac MR and CT volumes.

PubMed

Barba-J, Leiner; Escalante-Ramírez, Boris; Vallejo Venegas, Enrique; Arámbula Cosío, Fernando

2018-05-01

Analysis of cardiac images is a fundamental task to diagnose heart problems. Left ventricle (LV) is one of the most important heart structures used for cardiac evaluation. In this work, we propose a novel 3D hierarchical multiscale segmentation method based on a local active contour (AC) model and the Hermite transform (HT) for LV analysis in cardiac magnetic resonance (MR) and computed tomography (CT) volumes in short axis view. Features such as directional edges, texture, and intensities are analyzed using the multiscale HT space. A local AC model is configured using the HT coefficients and geometrical constraints. The endocardial and epicardial boundaries are used for evaluation. Segmentation of the endocardium is controlled using elliptical shape constraints. The final endocardial shape is used to define the geometrical constraints for segmentation of the epicardium. We follow the assumption that epicardial and endocardial shapes are similar in volumes with short axis view. An initialization scheme based on a fuzzy C-means algorithm and mathematical morphology was designed. The algorithm performance was evaluated using cardiac MR and CT volumes in short axis view demonstrating the feasibility of the proposed method.

Content based image retrieval for matching images of improvised explosive devices in which snake initialization is viewed as an inverse problem

NASA Astrophysics Data System (ADS)

Acton, Scott T.; Gilliam, Andrew D.; Li, Bing; Rossi, Adam

2008-02-01

Improvised explosive devices (IEDs) are common and lethal instruments of terrorism, and linking a terrorist entity to a specific device remains a difficult task. In the effort to identify persons associated with a given IED, we have implemented a specialized content based image retrieval system to search and classify IED imagery. The system makes two contributions to the art. First, we introduce a shape-based matching technique exploiting shape, color, and texture (wavelet) information, based on novel vector field convolution active contours and a novel active contour initialization method which treats coarse segmentation as an inverse problem. Second, we introduce a unique graph theoretic approach to match annotated printed circuit board images for which no schematic or connectivity information is available. The shape-based image retrieval method, in conjunction with the graph theoretic tool, provides an efficacious system for matching IED images. For circuit imagery, the basic retrieval mechanism has a precision of 82.1% and the graph based method has a precision of 98.1%. As of the fall of 2007, the working system has processed over 400,000 case images.

Role of endocortical contouring methods on precision of HR-pQCT-derived cortical micro-architecture in postmenopausal women and young adults.

PubMed

Kawalilak, C E; Johnston, J D; Cooper, D M L; Olszynski, W P; Kontulainen, S A

2016-02-01

Precision errors of cortical bone micro-architecture from high-resolution peripheral quantitative computed tomography (pQCT) ranged from 1 to 16 % and did not differ between automatic or manually modified endocortical contour methods in postmenopausal women or young adults. In postmenopausal women, manually modified contours led to generally higher cortical bone properties when compared to the automated method. First, the objective of the study was to define in vivo precision errors (coefficient of variation root mean square (CV%RMS)) and least significant change (LSC) for cortical bone micro-architecture using two endocortical contouring methods: automatic (AUTO) and manually modified (MOD) in two groups (postmenopausal women and young adults) from high-resolution pQCT (HR-pQCT) scans. Second, it was to compare precision errors and bone outcomes obtained with both methods within and between groups. Using HR-pQCT, we scanned twice the distal radius and tibia of 34 postmenopausal women (mean age ± SD 74 ± 7 years) and 30 young adults (27 ± 9 years). Cortical micro-architecture was determined using AUTO and MOD contour methods. CV%RMS and LSC were calculated. Repeated measures and multivariate ANOVA were used to compare mean CV% and bone outcomes between the methods within and between the groups. Significance was accepted at P < 0.05. CV%RMS ranged from 0.9 to 16.3 %. Within-group precision did not differ between evaluation methods. Compared to young adults, postmenopausal women had better precision for radial cortical porosity (precision difference 9.3 %) and pore volume (7.5 %) with MOD. Young adults had better precision for cortical thickness (0.8 %, MOD) and tibial cortical density (0.2 %, AUTO). In postmenopausal women, MOD resulted in 0.2-54 % higher values for most cortical outcomes, as well as 6-8 % lower radial and tibial cortical BMD and 2 % lower tibial cortical thickness. Results suggest that AUTO and MOD endocortical contour methods provide comparable repeatability. In postmenopausal women, manual modification of endocortical contours led to generally higher cortical bone properties when compared to the automated method, while no between-method differences were observed in young adults.

Four years with FALCON - an ESTRO educational project: achievements and perspectives.

PubMed

Eriksen, Jesper Grau; Salembier, Carl; Rivera, Sofia; De Bari, Berardino; Berger, Daniel; Mantello, Giovanna; Müller, Arndt-Christian; Martin, Arturo Navarro; Pasini, Danilo; Tanderup, Kari; Palmu, Miika; Verfaillie, Christine; Pötter, Richard; Valentini, Vincenzo

2014-07-01

Variability in anatomical contouring is one of the important uncertainties in radiotherapy. FALCON (Fellowship in Anatomic deLineation and CONtouring) is an educational ESTRO (European SocieTy for Radiation and Oncology) project devoted to improve interactive teaching, the homogeneity in contouring and to compare individual contours with endorsed guidelines or expert opinions. This report summarizes the experience from the first 4 years using FALCON for educational activities within ESTRO School and presents the perspectives for the future. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A robust and fast active contour model for image segmentation with intensity inhomogeneity

NASA Astrophysics Data System (ADS)

Ding, Keyan; Weng, Guirong

2018-04-01

In this paper, a robust and fast active contour model is proposed for image segmentation in the presence of intensity inhomogeneity. By introducing the local image intensities fitting functions before the evolution of curve, the proposed model can effectively segment images with intensity inhomogeneity. And the computation cost is low because the fitting functions do not need to be updated in each iteration. Experiments have shown that the proposed model has a higher segmentation efficiency compared to some well-known active contour models based on local region fitting energy. In addition, the proposed model is robust to initialization, which allows the initial level set function to be a small constant function.

The deconvolution of complex spectra by artificial immune system

NASA Astrophysics Data System (ADS)

Galiakhmetova, D. I.; Sibgatullin, M. E.; Galimullin, D. Z.; Kamalova, D. I.

2017-11-01

An application of the artificial immune system method for decomposition of complex spectra is presented. The results of decomposition of the model contour consisting of three components, Gaussian contours, are demonstrated. The method of artificial immune system is an optimization method, which is based on the behaviour of the immune system and refers to modern methods of search for the engine optimization.

The TICTOP nozzle: a new nozzle contouring concept

NASA Astrophysics Data System (ADS)

Frey, Manuel; Makowka, Konrad; Aichner, Thomas

2017-06-01

Currently, mainly two types of nozzle contouring methods are applied in space propulsion: the truncated ideal contour (TIC) and the thrust-optimized parabola (TOP). This article presents a new nozzle contouring method called TICTOP, combining elements of TIC and TOP design. The resulting nozzle is shock-free as the TIC and therefore does not induce restricted shock separation leading to excessive side-loads. Simultaneously, the TICTOP nozzle will allow higher nozzle wall exit pressures and hence give a better separation margin than is the case for a TIC. Hence, this new nozzle type combines the good properties of TIC and TOP nozzles and eliminates their drawbacks. It is especially suited for first stage application in launchers where flow separation and side-loads are design drivers.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming.

PubMed

Chiu, Stephanie J; Toth, Cynthia A; Bowes Rickman, Catherine; Izatt, Joseph A; Farsiu, Sina

2012-05-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique.

Contour Detection and Completion for Inpainting and Segmentation Based on Topological Gradient and Fast Marching Algorithms

PubMed Central

Auroux, Didier; Cohen, Laurent D.; Masmoudi, Mohamed

2011-01-01

We combine in this paper the topological gradient, which is a powerful method for edge detection in image processing, and a variant of the minimal path method in order to find connected contours. The topological gradient provides a more global analysis of the image than the standard gradient and identifies the main edges of an image. Several image processing problems (e.g., inpainting and segmentation) require continuous contours. For this purpose, we consider the fast marching algorithm in order to find minimal paths in the topological gradient image. This coupled algorithm quickly provides accurate and connected contours. We present then two numerical applications, to image inpainting and segmentation, of this hybrid algorithm. PMID:22194734

Feasibility study consisting of a review of contour generation methods from stereograms

NASA Technical Reports Server (NTRS)

Kim, C. J.; Wyant, J. C.

1980-01-01

A review of techniques for obtaining contour information from stereo pairs is given. Photogrammetric principles including a description of stereoscopic vision are presented. The use of conventional contour generation methods, such as the photogrammetric plotting technique, electronic correlator, and digital correlator are described. Coherent optical techniques for contour generation are discussed and compared to the electronic correlator. The optical techniques are divided into two categories: (1) image plane operation and (2) frequency plane operation. The description of image plane correlators are further divided into three categories: (1) image to image correlator, (2) interferometric correlator, and (3) positive negative transparencies. The frequency plane correlators are divided into two categories: (1) correlation of Fourier transforms, and (2) filtering techniques.

Automatic segmentation of closed-contour features in ophthalmic images using graph theory and dynamic programming

PubMed Central

Chiu, Stephanie J.; Toth, Cynthia A.; Bowes Rickman, Catherine; Izatt, Joseph A.; Farsiu, Sina

2012-01-01

This paper presents a generalized framework for segmenting closed-contour anatomical and pathological features using graph theory and dynamic programming (GTDP). More specifically, the GTDP method previously developed for quantifying retinal and corneal layer thicknesses is extended to segment objects such as cells and cysts. The presented technique relies on a transform that maps closed-contour features in the Cartesian domain into lines in the quasi-polar domain. The features of interest are then segmented as layers via GTDP. Application of this method to segment closed-contour features in several ophthalmic image types is shown. Quantitative validation experiments for retinal pigmented epithelium cell segmentation in confocal fluorescence microscopy images attests to the accuracy of the presented technique. PMID:22567602

The Development of Skull Prosthesis Through Active Contour Model.

PubMed

Chen, Yi-Wen; Shih, Cheng-Ting; Cheng, Chen-Yang; Lin, Yu-Cheng

2017-09-09

Skull defects result in brain infection and inadequate brain protection and pose a general danger to patient health. To avoid these situations and prevent re-injury, a prosthesis must be constructed and grafted onto the deficient region. With the development of rapid customization through additive manufacturing and 3D printing technology, skull prostheses can be fabricated accurately and efficiently prior to cranioplasty. However, an unfitted skull prosthesis made with a metal implant can cause repeated infection, potentially necessitating secondary surgery. This paper presents a method of creating suitably geometric graphics of skull defects to be applied in skull repair through active contour models. These models can be adjusted in each computed tomography slice according to the graphic features, and the curves representing the skull defect can be modeled. The generated graphics can adequately mimic the natural curvature of the complete skull. This method will enable clinical surgeons to rapidly implant customized prostheses, which is of particular importance in emergency surgery. The findings of this research can help surgeons provide patients with skull defects with treatment of the highest quality.

Modelling prehistoric terrain Models using LiDAR-data: a geomorphological approach

NASA Astrophysics Data System (ADS)

Höfler, Veit; Wessollek, Christine; Karrasch, Pierre

2015-10-01

Terrain surfaces conserve human activities in terms of textures and structures. With reference to archaeological questions, the geological archive is investigated by means of models regarding anthropogenic traces. In doing so, the high-resolution digital terrain model is of inestimable value for the decoding of the archive. The evaluation of these terrain models and the reconstruction of historical surfaces is still a challenging issue. Due to the data collection by means of LiDAR systems (light detection and ranging) and despite their subsequent pre-processing and filtering, recently anthropogenic artefacts are still present in the digital terrain model. Analysis have shown that elements, such as contour lines and channels, can well be extracted from a high-resolution digital terrain model. This way, channels in settlement areas show a clear anthropogenic character. This fact can also be observed for contour lines. Some contour lines representing a possibly natural ground surface and avoid anthropogenic artefacts. Comparable to channels, noticeable patterns of contour lines become visible in areas with anthropogenic artefacts. The presented workflow uses functionalities of ArcGIS and the programming language R.1 The method starts with the extraction of contour lines from the digital terrain model. Through macroscopic analyses based on geomorphological expert knowledge, contour lines are selected representing the natural geomorphological character of the surface. In a first step, points are determined along each contour line in regular intervals. This points and the corresponding height information which is taken from an original digital terrain model is saved as a point cloud. Using the programme library gstat, a variographic analysis and the use of a Kriging-procedure based on this follow.2-4 The result is a digital terrain model filtered considering geomorphological expert knowledge showing no human degradation in terms of artefacts, preserving the landscape-genetic character and can be called a prehistoric terrain model.

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 Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Method for measuring the contour of a machined part

DOEpatents

Bieg, L.F.

1995-05-30

A method is disclosed for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining. 5 figs.

Method for measuring the contour of a machined part

DOEpatents

Bieg, Lothar F.

1995-05-30

A method for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining.

A magnetic resonance imaging study on the articulatory and acoustic speech parameters of Malay vowels

PubMed Central

2014-01-01

The phonetic properties of six Malay vowels are investigated using magnetic resonance imaging (MRI) to visualize the vocal tract in order to obtain dynamic articulatory parameters during speech production. To resolve image blurring due to the tongue movement during the scanning process, a method based on active contour extraction is used to track tongue contours. The proposed method efficiently tracks tongue contours despite the partial blurring of MRI images. Consequently, the articulatory parameters that are effectively measured as tongue movement is observed, and the specific shape of the tongue and its position for all six uttered Malay vowels are determined. Speech rehabilitation procedure demands some kind of visual perceivable prototype of speech articulation. To investigate the validity of the measured articulatory parameters based on acoustic theory of speech production, an acoustic analysis based on the uttered vowels by subjects has been performed. As the acoustic speech and articulatory parameters of uttered speech were examined, a correlation between formant frequencies and articulatory parameters was observed. The experiments reported a positive correlation between the constriction location of the tongue body and the first formant frequency, as well as a negative correlation between the constriction location of the tongue tip and the second formant frequency. The results demonstrate that the proposed method is an effective tool for the dynamic study of speech production. PMID:25060583

A magnetic resonance imaging study on the articulatory and acoustic speech parameters of Malay vowels.

PubMed

Zourmand, Alireza; Mirhassani, Seyed Mostafa; Ting, Hua-Nong; Bux, Shaik Ismail; Ng, Kwan Hoong; Bilgen, Mehmet; Jalaludin, Mohd Amin

2014-07-25

The phonetic properties of six Malay vowels are investigated using magnetic resonance imaging (MRI) to visualize the vocal tract in order to obtain dynamic articulatory parameters during speech production. To resolve image blurring due to the tongue movement during the scanning process, a method based on active contour extraction is used to track tongue contours. The proposed method efficiently tracks tongue contours despite the partial blurring of MRI images. Consequently, the articulatory parameters that are effectively measured as tongue movement is observed, and the specific shape of the tongue and its position for all six uttered Malay vowels are determined.Speech rehabilitation procedure demands some kind of visual perceivable prototype of speech articulation. To investigate the validity of the measured articulatory parameters based on acoustic theory of speech production, an acoustic analysis based on the uttered vowels by subjects has been performed. As the acoustic speech and articulatory parameters of uttered speech were examined, a correlation between formant frequencies and articulatory parameters was observed. The experiments reported a positive correlation between the constriction location of the tongue body and the first formant frequency, as well as a negative correlation between the constriction location of the tongue tip and the second formant frequency. The results demonstrate that the proposed method is an effective tool for the dynamic study of speech production.

Image registration method for medical image sequences

DOEpatents

Gee, Timothy F.; Goddard, James S.

2013-03-26

Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

Active contours on statistical manifolds and texture segmentation

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Neil A. Clark; Philip A. Araman

2005-01-01

A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2- dimensional Riemannian manifolds that are statistically defined by maps that transform a parameter domain onto a set of probability density functions. In this novel framework, color or texture features are measured at each image point and their statistical...

Active contours on statistical manifolds and texture segmentaiton

Treesearch

Sang-Mook Lee; A. Lynn Abbott; Neil A. Clark; Philip A. Araman

2005-01-01

A new approach to active contours on statistical manifolds is presented. The statistical manifolds are 2- dimensional Riemannian manifolds that are statistically defined by maps that transform a parameter domain onto-a set of probability density functions. In this novel framework, color or texture features are measured at each Image point and their statistical...

Total luminescence contour spectra of six topped crude oils

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

Chisholm, B.R.; Eldering, H.G.; Giering, L.P.

1976-11-01

The results of a preliminary study of six topped crude oils by total luminescence are presented. Included are six contour spectra, six principal excitation/emission spectra, an interpretation of the contours by comparison with other data, a discussion of the method and recommendations for further related studies. These data are used in oil spill identification.

Tongue Motion Averaging from Contour Sequences

ERIC Educational Resources Information Center

Li, Min; Kambhamettu, Chandra; Stone, Maureen

2005-01-01

In this paper, a method to get the best representation of a speech motion from several repetitions is presented. Each repetition is a representation of the same speech captured at different times by sequence of ultrasound images and is composed of a set of 2D spatio-temporal contours. These 2D contours in different repetitions are time aligned…

TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

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

Liu, J; Wu, Q.J.; Yin, F

2014-06-15

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into fivemore » groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.« less

SU-E-J-129: Atlas Development for Cardiac Automatic Contouring Using Multi-Atlas Segmentation

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

Zhou, R; Yang, J; Pan, T

Purpose: To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity. Methods: Six thoracic cancer patients with both contrast and non-contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non-contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fusedmore » using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in-house multi-atlas segmentation. Using leave-one-out test, we generated auto-segmented contours for each ROI and each patient. The auto-segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: Inter-observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto-segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm. Conclusion: A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need for auto-segmented contours of indistinguishable small structures.« less

Multi-object segmentation framework using deformable models for medical imaging analysis.

PubMed

Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

2016-08-01

Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed framework has a wide range of applications especially in the presence of adjacent structures of interest or under intra-structure inhomogeneities giving excellent quantitative results.

Human recognition based on head-shoulder contour extraction and BP neural network

NASA Astrophysics Data System (ADS)

Kong, Xiao-fang; Wang, Xiu-qin; Gu, Guohua; Chen, Qian; Qian, Wei-xian

2014-11-01

In practical application scenarios like video surveillance and human-computer interaction, human body movements are uncertain because the human body is a non-rigid object. Based on the fact that the head-shoulder part of human body can be less affected by the movement, and will seldom be obscured by other objects, in human detection and recognition, a head-shoulder model with its stable characteristics can be applied as a detection feature to describe the human body. In order to extract the head-shoulder contour accurately, a head-shoulder model establish method with combination of edge detection and the mean-shift algorithm in image clustering has been proposed in this paper. First, an adaptive method of mixture Gaussian background update has been used to extract targets from the video sequence. Second, edge detection has been used to extract the contour of moving objects, and the mean-shift algorithm has been combined to cluster parts of target's contour. Third, the head-shoulder model can be established, according to the width and height ratio of human head-shoulder combined with the projection histogram of the binary image, and the eigenvectors of the head-shoulder contour can be acquired. Finally, the relationship between head-shoulder contour eigenvectors and the moving objects will be formed by the training of back-propagation (BP) neural network classifier, and the human head-shoulder model can be clustered for human detection and recognition. Experiments have shown that the method combined with edge detection and mean-shift algorithm proposed in this paper can extract the complete head-shoulder contour, with low calculating complexity and high efficiency.

Propfan experimental data analysis

NASA Technical Reports Server (NTRS)

Vernon, David F.; Page, Gregory S.; Welge, H. Robert

1984-01-01

A data reduction method, which is consistent with the performance prediction methods used for analysis of new aircraft designs, is defined and compared to the method currently used by NASA using data obtained from an Ames Res. Center 11 foot transonic wind tunnel test. Pressure and flow visualization data from the Ames test for both the powered straight underwing nacelle, and an unpowered contoured overwing nacelle installation is used to determine the flow phenomena present for a wind mounted turboprop installation. The test data is compared to analytic methods, showing the analytic methods to be suitable for design and analysis of new configurations. The data analysis indicated that designs with zero interference drag levels are achieveable with proper wind and nacelle tailoring. A new overwing contoured nacelle design and a modification to the wing leading edge extension for the current wind tunnel model design are evaluated. Hardware constraints of the current model parts prevent obtaining any significant performance improvement due to a modified nacelle contouring. A new aspect ratio wing design for an up outboard rotation turboprop installation is defined, and an advanced contoured nacelle is provided.

Segmentation of radiographic images under topological constraints: application to the femur.

PubMed

Gamage, Pavan; Xie, Sheng Quan; Delmas, Patrice; Xu, Wei Liang

2010-09-01

A framework for radiographic image segmentation under topological control based on two-dimensional (2D) image analysis was developed. The system is intended for use in common radiological tasks including fracture treatment analysis, osteoarthritis diagnostics and osteotomy management planning. The segmentation framework utilizes a generic three-dimensional (3D) model of the bone of interest to define the anatomical topology. Non-rigid registration is performed between the projected contours of the generic 3D model and extracted edges of the X-ray image to achieve the segmentation. For fractured bones, the segmentation requires an additional step where a region-based active contours curve evolution is performed with a level set Mumford-Shah method to obtain the fracture surface edge. The application of the segmentation framework to analysis of human femur radiographs was evaluated. The proposed system has two major innovations. First, definition of the topological constraints does not require a statistical learning process, so the method is generally applicable to a variety of bony anatomy segmentation problems. Second, the methodology is able to handle both intact and fractured bone segmentation. Testing on clinical X-ray images yielded an average root mean squared distance (between the automatically segmented femur contour and the manual segmented ground truth) of 1.10 mm with a standard deviation of 0.13 mm. The proposed point correspondence estimation algorithm was benchmarked against three state-of-the-art point matching algorithms, demonstrating successful non-rigid registration for the cases of interest. A topologically constrained automatic bone contour segmentation framework was developed and tested, providing robustness to noise, outliers, deformations and occlusions.

3D intrathoracic region definition and its application to PET-CT analysis

NASA Astrophysics Data System (ADS)

Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W.; Higgins, William E.

2014-03-01

Recently developed integrated PET-CT scanners give co-registered multimodal data sets that offer complementary three-dimensional (3D) digital images of the chest. PET (positron emission tomography) imaging gives highly specific functional information of suspect cancer sites, while CT (X-ray computed tomography) gives associated anatomical detail. Because the 3D CT and PET scans generally span the body from the eyes to the knees, accurate definition of the intrathoracic region is vital for focusing attention to the central-chest region. In this way, diagnostically important regions of interest (ROIs), such as central-chest lymph nodes and cancer nodules, can be more efficiently isolated. We propose a method for automatic segmentation of the intrathoracic region from a given co-registered 3D PET-CT study. Using the 3D CT scan as input, the method begins by finding an initial intrathoracic region boundary for a given 2D CT section. Next, active contour analysis, driven by a cost function depending on local image gradient, gradient-direction, and contour shape features, iteratively estimates the contours spanning the intrathoracic region on neighboring 2D CT sections. This process continues until the complete region is defined. We next present an interactive system that employs the segmentation method for focused 3D PET-CT chest image analysis. A validation study over a series of PET-CT studies reveals that the segmentation method gives a Dice index accuracy of less than 98%. In addition, further results demonstrate the utility of the method for focused 3D PET-CT chest image analysis, ROI definition, and visualization.

Automatic fault tracing of active faults in the Sutlej valley (NW-Himalayas, India)

NASA Astrophysics Data System (ADS)

Janda, C.; Faber, R.; Hager, C.; Grasemann, B.

2003-04-01

In the Sutlej Valley the Lesser Himalayan Crystalline Sequence (LHCS) is actively extruding between the Munsiari Thrust (MT) at the base, and the Karcham Normal Fault (KNF) at the top. The clear evidences for ongoing deformation are brittle faults in Holocene lake deposits, hot springs activity near the faults and dramatically younger cooling ages within the LHCS (Vannay and Grasemann, 2001). Because these brittle fault zones obviously influence the morphology in the field we developed a new method for automatically tracing the intersections of planar fault geometries with digital elevation models (Faber, 2002). Traditional mapping techniques use structure contours (i.e. lines or curves connecting points of equal elevation on a geological structure) in order to construct intersections of geological structures with topographic maps. However, even if the geological structure is approximated by a plane and therefore structure contours are equally spaced lines, this technique is rather time consuming and inaccurate, because errors are cumulative. Drawing structure contours by hand makes it also impossible to slightly change the azimuth and dip direction of the favoured plane without redrawing everything from the beginning on. However, small variations of the fault position which are easily possible by either inaccuracies of measurement in the field or small local variations in the trend and/or dip of the fault planes can have big effects on the intersection with topography. The developed method allows to interactively view intersections in a 2D and 3D mode. Unlimited numbers of planes can be moved separately in 3 dimensions (translation and rotation) and intersections with the topography probably following morphological features can be mapped. Besides the increase of efficiency this method underlines the shortcoming of classical lineament extraction ignoring the dip of planar structures. Using this method, areas of active faulting influencing the morphology, can be mapped near the MT and the KNF suggesting that the most active zones are restricted to the Sutlej Valley. Faber R., 2002: WinGeol - Software for Analyzing and Visualization of Geological data, Department of Geological Sciences, University of Vienna. Vannay, J.-C., Grasemann, B., 2001. Himalayan inverted metamorphism and syn-convergence extension as a consequence of a general shear extrusion. Geol. Mag. 138 (3), 253-276.

Interactive semiautomatic contour delineation using statistical conditional random fields framework.

PubMed

Hu, Yu-Chi; Grossberg, Michael D; Wu, Abraham; Riaz, Nadeem; Perez, Carmen; Mageras, Gig S

2012-07-01

Contouring a normal anatomical structure during radiation treatment planning requires significant time and effort. The authors present a fast and accurate semiautomatic contour delineation method to reduce the time and effort required of expert users. Following an initial segmentation on one CT slice, the user marks the target organ and nontarget pixels with a few simple brush strokes. The algorithm calculates statistics from this information that, in turn, determines the parameters of an energy function containing both boundary and regional components. The method uses a conditional random field graphical model to define the energy function to be minimized for obtaining an estimated optimal segmentation, and a graph partition algorithm to efficiently solve the energy function minimization. Organ boundary statistics are estimated from the segmentation and propagated to subsequent images; regional statistics are estimated from the simple brush strokes that are either propagated or redrawn as needed on subsequent images. This greatly reduces the user input needed and speeds up segmentations. The proposed method can be further accelerated with graph-based interpolation of alternating slices in place of user-guided segmentation. CT images from phantom and patients were used to evaluate this method. The authors determined the sensitivity and specificity of organ segmentations using physician-drawn contours as ground truth, as well as the predicted-to-ground truth surface distances. Finally, three physicians evaluated the contours for subjective acceptability. Interobserver and intraobserver analysis was also performed and Bland-Altman plots were used to evaluate agreement. Liver and kidney segmentations in patient volumetric CT images show that boundary samples provided on a single CT slice can be reused through the entire 3D stack of images to obtain accurate segmentation. In liver, our method has better sensitivity and specificity (0.925 and 0.995) than region growing (0.897 and 0.995) and level set methods (0.912 and 0.985) as well as shorter mean predicted-to-ground truth distance (2.13 mm) compared to regional growing (4.58 mm) and level set methods (8.55 mm and 4.74 mm). Similar results are observed in kidney segmentation. Physician evaluation of ten liver cases showed that 83% of contours did not need any modification, while 6% of contours needed modifications as assessed by two or more evaluators. In interobserver and intraobserver analysis, Bland-Altman plots showed our method to have better repeatability than the manual method while the delineation time was 15% faster on average. Our method achieves high accuracy in liver and kidney segmentation and considerably reduces the time and labor required for contour delineation. Since it extracts purely statistical information from the samples interactively specified by expert users, the method avoids heuristic assumptions commonly used by other methods. In addition, the method can be expanded to 3D directly without modification because the underlying graphical framework and graph partition optimization method fit naturally with the image grid structure.

[The automatic iris map overlap technology in computer-aided iridiagnosis].

PubMed

He, Jia-feng; Ye, Hu-nian; Ye, Miao-yuan

2002-11-01

In the paper, iridology and computer-aided iridiagnosis technologies are briefly introduced and the extraction method of the collarette contour is then investigated. The iris map can be overlapped on the original iris image based on collarette contour extraction. The research on collarette contour extraction and iris map overlap is of great importance to computer-aided iridiagnosis technologies.

Fractal active contour model for segmenting the boundary of man-made target in nature scenes

NASA Astrophysics Data System (ADS)

Li, Min; Tang, Yandong; Wang, Lidi; Shi, Zelin

2006-02-01

In this paper, a novel geometric active contour model based on the fractal dimension feature to extract the boundary of man-made target in nature scenes is presented. In order to suppress the nature clutters, an adaptive weighting function is defined using the fractal dimension feature. Then the weighting function is introduced into the geodesic active contour model to detect the boundary of man-made target. Curve driven by our proposed model can evolve gradually from the initial position to the boundary of man-made target without being disturbed by nature clutters, even if the initial curve is far away from the true boundary. Experimental results validate the effectiveness and feasibility of our model.

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

Gaffney, David K., E-mail: david.gaffney@hci.utah.edu; King, Bronwyn; Viswanathan, Akila N.

Purpose: The purpose of this study was to develop a radiation therapy (RT) contouring atlas and recommendations for women with postoperative and locally advanced vulvar carcinoma. Methods and Materials: An international committee of 35 expert gynecologic radiation oncologists completed a survey of the treatment of vulvar carcinoma. An initial set of recommendations for contouring was discussed and generated by consensus. Two cases, 1 locally advanced and 1 postoperative, were contoured by 14 physicians. Contours were compared and analyzed using an expectation-maximization algorithm for simultaneous truth and performance level estimation (STAPLE), and a 95% confidence interval contour was developed. The levelmore » of agreement among contours was assessed using a kappa statistic. STAPLE contours underwent full committee editing to generate the final atlas consensus contours. Results: Analysis of the 14 contours showed substantial agreement, with kappa statistics of 0.69 and 0.64 for cases 1 and 2, respectively. There was high specificity for both cases (≥99%) and only moderate sensitivity of 71.3% and 64.9% for cases 1 and 2, respectively. Expert review and discussion generated consensus recommendations for contouring target volumes and treatment for postoperative and locally advanced vulvar cancer. Conclusions: These consensus recommendations for contouring and treatment of vulvar cancer identified areas of complexity and controversy. Given the lack of clinical research evidence in vulvar cancer radiation therapy, the committee advocates a conservative and consistent approach using standardized recommendations.« less

Determination of volume-time curves for the right ventricle and its outflow tract for functional analyses.

PubMed

Gabbert, Dominik D; Entenmann, Andreas; Jerosch-Herold, Michael; Frettlöh, Felicitas; Hart, Christopher; Voges, Inga; Pham, Minh; Andrade, Ana; Pardun, Eileen; Wegner, P; Hansen, Traudel; Kramer, Hans-Heiner; Rickers, Carsten

2013-12-01

The determination of right ventricular volumes and function is of increasing interest for the postoperative care of patients with congenital heart defects. The presentation of volumetry data in terms of volume-time curves allows a comprehensive functional assessment. By using manual contour tracing, the generation of volume-time curves is exceedingly time-consuming. This study describes a fast and precise method for determining volume-time curves for the right ventricle and for the right ventricular outflow tract. The method applies contour detection and includes a feature for identifying the right ventricular outflow tract volume. The segregation of the outflow tract is performed by four-dimensional curved smooth boundary surfaces defined by prespecified anatomical landmarks. The comparison with manual contour tracing demonstrates that the method is accurate and improves the precision of the measurement. Compared to manual contour tracing the bias is <0.1% ± 4.1% (right ventricle) and -2.6% ± 20.0% (right ventricular outflow tract). The standard deviations of inter- and intraobserver variabilities for determining the volume of the right ventricular outflow tract are reduced to less than half the values of manual contour tracing. The time consumption per patient is reduced from 341 ± 80 min (right ventricle) and 56 ± 11 min (right ventricular outflow tract) using manual contour tracing to 46 ± 9 min for a combined analysis of right ventricle and right ventricular outflow tract. The analysis of volume-time curves for the right ventricle and its outflow tract discloses new evaluation methods in clinical routine and science. Copyright © 2013 Wiley Periodicals, Inc.

Accurate and Fully Automatic Hippocampus Segmentation Using Subject-Specific 3D Optimal Local Maps Into a Hybrid Active Contour Model

PubMed Central

Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-01-01

Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866

Esophagus segmentation in CT via 3D fully convolutional neural network and random walk.

PubMed

Fechter, Tobias; Adebahr, Sonja; Baltas, Dimos; Ben Ayed, Ismail; Desrosiers, Christian; Dolz, Jose

2017-12-01

Precise delineation of organs at risk is a crucial task in radiotherapy treatment planning for delivering high doses to the tumor while sparing healthy tissues. In recent years, automated segmentation methods have shown an increasingly high performance for the delineation of various anatomical structures. However, this task remains challenging for organs like the esophagus, which have a versatile shape and poor contrast to neighboring tissues. For human experts, segmenting the esophagus from CT images is a time-consuming and error-prone process. To tackle these issues, we propose a random walker approach driven by a 3D fully convolutional neural network (CNN) to automatically segment the esophagus from CT images. First, a soft probability map is generated by the CNN. Then, an active contour model (ACM) is fitted to the CNN soft probability map to get a first estimation of the esophagus location. The outputs of the CNN and ACM are then used in conjunction with a probability model based on CT Hounsfield (HU) values to drive the random walker. Training and evaluation were done on 50 CTs from two different datasets, with clinically used peer-reviewed esophagus contours. Results were assessed regarding spatial overlap and shape similarity. The esophagus contours generated by the proposed algorithm showed a mean Dice coefficient of 0.76 ± 0.11, an average symmetric square distance of 1.36 ± 0.90 mm, and an average Hausdorff distance of 11.68 ± 6.80, compared to the reference contours. These results translate to a very good agreement with reference contours and an increase in accuracy compared to existing methods. Furthermore, when considering the results reported in the literature for the publicly available Synapse dataset, our method outperformed all existing approaches, which suggests that the proposed method represents the current state-of-the-art for automatic esophagus segmentation. We show that a CNN can yield accurate estimations of esophagus location, and that the results of this model can be refined by a random walk step taking pixel intensities and neighborhood relationships into account. One of the main advantages of our network over previous methods is that it performs 3D convolutions, thus fully exploiting the 3D spatial context and performing an efficient volume-wise prediction. The whole segmentation process is fully automatic and yields esophagus delineations in very good agreement with the gold standard, showing that it can compete with previously published methods. © 2017 American Association of Physicists in Medicine.

SU-E-E-05: Improving Contouring Precision and Consistency for Physicians-In-Training with Simple Lab Experiments

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

Ma, L; Larson, D A

2015-06-15

Purpose: Target contouring for high-dose treatments such as radiosurgery of brain metastases is highly critical in eliminating marginal failure and reducing complications as shown by recent clinical studies. In order to improve contouring accuracy and practice consistency for the procedure, we introduced a self-assessed physics lab practice for the physicians-in-training. Methods: A set of commercially acquired high-precision PMMA plastic spheres were randomly embedded in a Styrofoam block and then scanned with the CT/MR via the clinical procedural imaging protocol. A group of first-year physicians-in-training (n=6) from either neurosurgery or radiation oncology department were asked to contour the scanned objects (diametermore » ranged from 0.4 cm to 3.8 cm). These user-defined contours were then compared with the ideal contour sets of object shape for self assessments to determine the maximum areas of the observed discrepancies and method of improvements. Results: The largest discrepancies from initial practice were consistently found to be located near the extreme longitudinal portions of the target for all the residents. Discrepancy was especially prominent when contouring small objects < 1.0 cm in diameters. For example, the mean volumes rendered from the initial contour data set differed from the ideal data set by 7.7%±6.6% for the participants (p> 0.23 suggesting agreement cannot be established). However, when incorporating a secondary imaging scan such as reconstructed coronal or sagittal images in a repeat practice, the agreement was dramatically improved yielding p<0.02 in agreement with the reference data set for all the participants. Conclusion: A simple physics lab revealed a common pitfall in contouring small metastatic brain tumors for radiosurgical procedures and provided a systematic tool for physicians-in-training in improving their clinical contouring skills. Dr Ma is current a board member of international stereotactic radiosurgical society.« less

SU-E-J-101: Improved CT to CBCT Deformable Registration Accuracy by Incorporating Multiple CBCTs

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

Godley, A; Stephans, K; Olsen, L Sheplan

2015-06-15

Purpose: Combining prior day CBCT contours with STAPLE was previously shown to improve automated prostate contouring. These accurate STAPLE contours are now used to guide the planning CT to pre-treatment CBCT deformable registration. Methods: Six IGRT prostate patients with daily kilovoltage CBCT had their original planning CT and 9 CBCTs contoured by the same physician. These physician contours for the planning CT and each prior CBCT are deformed to match the current CBCT anatomy, producing multiple contour sets. These sets are then combined using STAPLE into one optimal set (e.g. for day 3 CBCT, combine contours produced using the planmore » plus day 1 and 2 CBCTs). STAPLE computes a probabilistic estimate of the true contour from this collection of contours by maximizing sensitivity and specificity. The deformation field from planning CT to CBCT registration is then refined by matching its deformed contours to the STAPLE contours. ADMIRE (Elekta Inc.) was used for this. The refinement does not force perfect agreement of the contours, typically Dice’s Coefficient (DC) of > 0.9 is obtained, and the image difference metric remains in the optimization of the deformable registration. Results: The average DC between physician delineated CBCT contours and deformed planning CT contours for the bladder, rectum and prostate was 0.80, 0.79 and 0.75, respectively. The accuracy significantly improved to 0.89, 0.84 and 0.84 (P<0.001 for all) when using the refined deformation field. The average time to run STAPLE with five scans and refine the planning CT deformation was 66 seconds on a Telsa K20c GPU. Conclusion: Accurate contours generated from multiple CBCTs provided guidance for CT to CBCT deformable registration, significantly improving registration accuracy as measured by contour DC. A more accurate deformation field is now available for transferring dose or electron density to the CBCT for adaptive planning. Research grant from Elekta.« less

Isolating contour information from arbitrary images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1989-01-01

Aspects of natural vision (physiological and perceptual) serve as a basis for attempting the development of a general processing scheme for contour extraction. Contour information is assumed to be central to visual recognition skills. While the scheme must be regarded as highly preliminary, initial results do compare favorably with the visual perception of structure. The scheme pays special attention to the construction of a smallest scale circular difference-of-Gaussian (DOG) convolution, calibration of multiscale edge detection thresholds with the visual perception of grayscale boundaries, and contour/texture discrimination methods derived from fundamental assumptions of connectivity and the characteristics of printed text. Contour information is required to fall between a minimum connectivity limit and maximum regional spatial density limit at each scale. Results support the idea that contour information, in images possessing good image quality, is (centered at about 10 cyc/deg and 30 cyc/deg). Further, lower spatial frequency channels appear to play a major role only in contour extraction from images with serious global image defects.

Interactive contour delineation and refinement in treatment planning of image‐guided radiation therapy

PubMed Central

Zhou, Wu

2014-01-01

The accurate contour delineation of the target and/or organs at risk (OAR) is essential in treatment planning for image‐guided radiation therapy (IGRT). Although many automatic contour delineation approaches have been proposed, few of them can fulfill the necessities of applications in terms of accuracy and efficiency. Moreover, clinicians would like to analyze the characteristics of regions of interests (ROI) and adjust contours manually during IGRT. Interactive tool for contour delineation is necessary in such cases. In this work, a novel approach of curve fitting for interactive contour delineation is proposed. It allows users to quickly improve contours by a simple mouse click. Initially, a region which contains interesting object is selected in the image, then the program can automatically select important control points from the region boundary, and the method of Hermite cubic curves is used to fit the control points. Hence, the optimized curve can be revised by moving its control points interactively. Meanwhile, several curve fitting methods are presented for the comparison. Finally, in order to improve the accuracy of contour delineation, the process of the curve refinement based on the maximum gradient magnitude is proposed. All the points on the curve are revised automatically towards the positions with maximum gradient magnitude. Experimental results show that Hermite cubic curves and the curve refinement based on the maximum gradient magnitude possess superior performance on the proposed platform in terms of accuracy, robustness, and time calculation. Experimental results of real medical images demonstrate the efficiency, accuracy, and robustness of the proposed process in clinical applications. PACS number: 87.53.Tf PMID:24423846

The Topography Tub Learning Activity

NASA Astrophysics Data System (ADS)

Glesener, G. B.

2014-12-01

Understanding the basic elements of a topographic map (i.e. contour lines and intervals) is just a small part of learning how to use this abstract representational system as a resource in geologic mapping. Interpretation of a topographic map and matching its features with real-world structures requires that the system is utilized for visualizing the shapes of these structures and their spatial orientation. To enrich students' skills in visualizing topography from topographic maps a spatial training activity has been developed that uses 3D objects of various shapes and sizes, a sighting tool, a plastic basin, water, and transparencies. In the first part of the activity, the student is asked to draw a topographic map of one of the 3D objects. Next, the student places the object into a plastic tub in which water is added to specified intervals of height. The shoreline at each interval is used to reference the location of the contour line the student draws on a plastic inkjet transparency directly above the object. A key part of this activity is the use of a sighting tool by the student to assist in keeping the pencil mark directly above the shoreline. It (1) ensures the accurate positioning of the contour line and (2) gives the learner experience with using a sight before going out into the field. Finally, after the student finishes drawing the contour lines onto the transparency, the student can compare and contrast the two maps in order to discover where improvements in their visualization of the contours can be made. The teacher and/or peers can also make suggestions on ways to improve. A number of objects with various shapes and sizes are used in this exercise to produce contour lines representing the different types of topography the student may encounter while field mapping. The intended outcome from using this visualization training activity is improvement in performance of visualizing topography as the student moves between the topographic representation and corresponding topography in the field.

Assessing the Importance of Lexical Tone Contour to Sentence Perception in Mandarin-Speaking Children with Normal Hearing

ERIC Educational Resources Information Center

Zhu, Shufeng; Wong, Lena L. N.; Wang, Bin; Chen, Fei

2017-01-01

Purpose: The aim of the present study was to evaluate the influence of lexical tone contour and age on sentence perception in quiet and in noise conditions in Mandarin-speaking children ages 7 to 11 years with normal hearing. Method: Test materials were synthesized Mandarin sentences, each word with a manipulated lexical contour, that is, normal…

Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy

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

Stützer, Kristin; Haase, Robert; Exner, Florian

2016-09-15

Purpose: Rating both a lung segmentation algorithm and a deformable image registration (DIR) algorithm for subsequent lung computed tomography (CT) images by different evaluation techniques. Furthermore, investigating the relative performance and the correlation of the different evaluation techniques to address their potential value in a clinical setting. Methods: Two to seven subsequent CT images (69 in total) of 15 lung cancer patients were acquired prior, during, and after radiochemotherapy. Automated lung segmentations were compared to manually adapted contours. DIR between the first and all following CT images was performed with a fast algorithm specialized for lung tissue registration, requiring themore » lung segmentation as input. DIR results were evaluated based on landmark distances, lung contour metrics, and vector field inconsistencies in different subvolumes defined by eroding the lung contour. Correlations between the results from the three methods were evaluated. Results: Automated lung contour segmentation was satisfactory in 18 cases (26%), failed in 6 cases (9%), and required manual correction in 45 cases (66%). Initial and corrected contours had large overlap but showed strong local deviations. Landmark-based DIR evaluation revealed high accuracy compared to CT resolution with an average error of 2.9 mm. Contour metrics of deformed contours were largely satisfactory. The median vector length of inconsistency vector fields was 0.9 mm in the lung volume and slightly smaller for the eroded volumes. There was no clear correlation between the three evaluation approaches. Conclusions: Automatic lung segmentation remains challenging but can assist the manual delineation process. Proven by three techniques, the inspected DIR algorithm delivers reliable results for the lung CT data sets acquired at different time points. Clinical application of DIR demands a fast DIR evaluation to identify unacceptable results, for instance, by combining different automated DIR evaluation methods.« less

Contour temperature programmed desorption for monitoring multiple chemical reaction products

NASA Astrophysics Data System (ADS)

Chusuei, C. C.; de la Peña, J. V.; Schreifels, J. A.

1999-09-01

A simple method for obtaining a comprehensive overview of major compounds desorbing from the surface during temperature programmed desorption (TPD) experiments is outlined. Standard commercially available equipment is used to perform the experiment. The method is particularly valuable when high molecular mass compounds are being studied. The acquisition of contour temperature programmed desorption (CTPD) spectra, sampling 50-dalton mass ranges at a time in the thermal desorption experiments, is described and demonstrated for the interaction of benzotriazole adsorbed on a Ni(111) surface. Conventional two-dimensional TPD spectra can be extracted from the CTPD by taking vertical slices of the contour.

A Method for Identifying Contours in Processing Digital Images from Computer Tomograph

NASA Astrophysics Data System (ADS)

Roşu, Şerban; Pater, Flavius; Costea, Dan; Munteanu, Mihnea; Roşu, Doina; Fratila, Mihaela

2011-09-01

The first step in digital processing of two-dimensional computed tomography images is to identify the contour of component elements. This paper deals with the collective work of specialists in medicine and applied mathematics in computer science on elaborating new algorithms and methods in medical 2D and 3D imagery.

A Novel Method for Reconstructing Broken Contour Lines Extracted from Scanned Topographic Maps

NASA Astrophysics Data System (ADS)

Wang, Feng; Liu, Pingzhi; Yang, Yun; Wei, Haiping; An, Xiaoya

2018-05-01

It is known that after segmentation and morphological operations on scanned topographic maps, gaps occur in contour lines. It is also well known that filling these gaps and reconstruction of contour lines with high accuracy and completeness is not an easy problem. In this paper, a novel method is proposed dedicated in automatic or semiautomatic filling up caps and reconstructing broken contour lines in binary images. The key part of end points' auto-matching and reconnecting is deeply discussed after introducing the procedure of reconstruction, in which some key algorithms and mechanisms are presented and realized, including multiple incremental backing trace to get weighted average direction angle of end points, the max constraint angle control mechanism based on the multiple gradient ranks, combination of weighted Euclidean distance and deviation angle to determine the optimum matching end point, bidirectional parabola control, etc. Lastly, experimental comparisons based on typically samples are complemented between proposed method and the other representative method, the results indicate that the former holds higher accuracy and completeness, better stability and applicability.

Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators

PubMed Central

Demongeot, Jacques; Fouquet, Yannick; Tayyab, Muhammad; Vuillerme, Nicolas

2009-01-01

Background Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. Methodology First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. Conclusions We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery. PMID:19547712

Re-Dimensional Thinking in Earth Science: From 3-D Virtual Reality Panoramas to 2-D Contour Maps

ERIC Educational Resources Information Center

Park, John; Carter, Glenda; Butler, Susan; Slykhuis, David; Reid-Griffin, Angelia

2008-01-01

This study examines the relationship of gender and spatial perception on student interactivity with contour maps and non-immersive virtual reality. Eighteen eighth-grade students elected to participate in a six-week activity-based course called "3-D GeoMapping." The course included nine days of activities related to topographic mapping.…

Wiring assembly and method of forming a channel in a wiring assembly for receiving conductor and providing separate regions of conductor contact with the channel

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

Stelzer, Gerald; Meinke, Rainer; Senti, Mark

A conductor assembly and method for constructing an assembly of the type which, when conducting current, generates a magnetic field or which, in the presence of a changing magnetic field, induces a voltage. In one embodiment the method provides a first insulative layer tubular in shape and including a surface along which a conductor segment may be positioned. A channel formed in the surface of the insulative layer defines a first conductor path and includes a surface of first contour in cross section along a first plane transverse to the conductor path. A segment of conductor having a surface ofmore » second contour in cross section is positioned at least partly in the channel and extends along the conductor path. Along the first plane, contact between the conductor surface of second contour and the channel surface of first contour includes at least two separate regions of contact.« less

Computer assisted holographic moire contouring

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.

2000-01-01

Theoretical analyses and experimental results on holographic moire contouring on diffusely reflecting objects are presented. The sensitivity and limitations of the method are discussed. Particular emphasis is put on computer-assisted data retrieval, processing, and recording.

Hearing and Seeing Tone through Color: An Efficacy Study of Web-Based, Multimodal Chinese Tone Perception Training

ERIC Educational Resources Information Center

Godfroid, Aline; Lin, Chin-Hsi; Ryu, Catherine

2017-01-01

Multimodal approaches have been shown to be effective for many learning tasks. In this study, we compared the effectiveness of five multimodal methods for second language (L2) Mandarin tone perception training: three single-cue methods (number, pitch contour, color) and two dual-cue methods (color and number, color and pitch contour). A total of…

Extracting contours of oval-shaped objects by Hough transform and minimal path algorithms

NASA Astrophysics Data System (ADS)

Tleis, Mohamed; Verbeek, Fons J.

2014-04-01

Circular and oval-like objects are very common in cell and micro biology. These objects need to be analyzed, and to that end, digitized images from the microscope are used so as to come to an automated analysis pipeline. It is essential to detect all the objects in an image as well as to extract the exact contour of each individual object. In this manner it becomes possible to perform measurements on these objects, i.e. shape and texture features. Our measurement objective is achieved by probing contour detection through dynamic programming. In this paper we describe a method that uses Hough transform and two minimal path algorithms to detect contours of (ovoid-like) objects. These algorithms are based on an existing grey-weighted distance transform and a new algorithm to extract the circular shortest path in an image. The methods are tested on an artificial dataset of a 1000 images, with an F1-score of 0.972. In a case study with yeast cells, contours from our methods were compared with another solution using Pratt's figure of merit. Results indicate that our methods were more precise based on a comparison with a ground-truth dataset. As far as yeast cells are concerned, the segmentation and measurement results enable, in future work, to retrieve information from different developmental stages of the cell using complex features.

Synchronous activity in cat visual cortex encodes collinear and cocircular contours.

PubMed

Samonds, Jason M; Zhou, Zhiyi; Bernard, Melanie R; Bonds, A B

2006-04-01

We explored how contour information in primary visual cortex might be embedded in the simultaneous activity of multiple cells recorded with a 100-electrode array. Synchronous activity in cat visual cortex was more selective and predictable in discriminating between drifting grating and concentric ring stimuli than changes in firing rate. Synchrony was found even between cells with wholly different orientation preferences when their receptive fields were circularly aligned, and membership in synchronous groups was orientation and curvature dependent. The existence of synchrony between cocircular cells reinforces its role as a general mechanism for contour integration and shape detection as predicted by association field concepts. Our data suggest that cortical synchrony results from common and synchronous input from earlier visual areas and that it could serve to shape extrastriate response selectivity.

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Automatic bone outer contour extraction from B-modes ultrasound images based on local phase symmetry and quadratic polynomial fitting

NASA Astrophysics Data System (ADS)

Karlita, Tita; Yuniarno, Eko Mulyanto; Purnama, I. Ketut Eddy; Purnomo, Mauridhi Hery

2017-06-01

Analyzing ultrasound (US) images to get the shapes and structures of particular anatomical regions is an interesting field of study since US imaging is a non-invasive method to capture internal structures of a human body. However, bone segmentation of US images is still challenging because it is strongly influenced by speckle noises and it has poor image quality. This paper proposes a combination of local phase symmetry and quadratic polynomial fitting methods to extract bone outer contour (BOC) from two dimensional (2D) B-modes US image as initial steps of three-dimensional (3D) bone surface reconstruction. By using local phase symmetry, the bone is initially extracted from US images. BOC is then extracted by scanning one pixel on the bone boundary in each column of the US images using first phase features searching method. Quadratic polynomial fitting is utilized to refine and estimate the pixel location that fails to be detected during the extraction process. Hole filling method is then applied by utilize the polynomial coefficients to fill the gaps with new pixel. The proposed method is able to estimate the new pixel position and ensures smoothness and continuity of the contour path. Evaluations are done using cow and goat bones by comparing the resulted BOCs with the contours produced by manual segmentation and contours produced by canny edge detection. The evaluation shows that our proposed methods produces an excellent result with average MSE before and after hole filling at the value of 0.65.

Spiral Light Beams and Contour Image Processing

NASA Astrophysics Data System (ADS)

Kishkin, Sergey A.; Kotova, Svetlana P.; Volostnikov, Vladimir G.

Spiral beams of light are characterized by their ability to remain structurally unchanged at propagation. They may have the shape of any closed curve. In the present paper a new approach is proposed within the framework of the contour analysis based on a close cooperation of modern coherent optics, theory of functions and numerical methods. An algorithm for comparing contours is presented and theoretically justified, which allows convincing of whether two contours are similar or not to within the scale factor and/or rotation. The advantages and disadvantages of the proposed approach are considered; the results of numerical modeling are presented.

Deep learning and shapes similarity for joint segmentation and tracing single neurons in SEM images

NASA Astrophysics Data System (ADS)

Rao, Qiang; Xiao, Chi; Han, Hua; Chen, Xi; Shen, Lijun; Xie, Qiwei

2017-02-01

Extracting the structure of single neurons is critical for understanding how they function within the neural circuits. Recent developments in microscopy techniques, and the widely recognized need for openness and standardization provide a community resource for automated reconstruction of dendritic and axonal morphology of single neurons. In order to look into the fine structure of neurons, we use the Automated Tape-collecting Ultra Microtome Scanning Electron Microscopy (ATUM-SEM) to get images sequence of serial sections of animal brain tissue that densely packed with neurons. Different from other neuron reconstruction method, we propose a method that enhances the SEM images by detecting the neuronal membranes with deep convolutional neural network (DCNN) and segments single neurons by active contour with group shape similarity. We joint the segmentation and tracing together and they interact with each other by alternate iteration that tracing aids the selection of candidate region patch for active contour segmentation while the segmentation provides the neuron geometrical features which improve the robustness of tracing. The tracing model mainly relies on the neuron geometrical features and is updated after neuron being segmented on the every next section. Our method enables the reconstruction of neurons of the drosophila mushroom body which is cut to serial sections and imaged under SEM. Our method provides an elementary step for the whole reconstruction of neuronal networks.

A novel geometry-dosimetry label fusion method in multi-atlas segmentation for radiotherapy: a proof-of-concept study

NASA Astrophysics Data System (ADS)

Chang, Jina; Tian, Zhen; Lu, Weiguo; Gu, Xuejun; Chen, Mingli; Jiang, Steve B.

2017-05-01

Multi-atlas segmentation (MAS) has been widely used to automate the delineation of organs at risk (OARs) for radiotherapy. Label fusion is a crucial step in MAS to cope with the segmentation variabilities among multiple atlases. However, most existing label fusion methods do not consider the potential dosimetric impact of the segmentation result. In this proof-of-concept study, we propose a novel geometry-dosimetry label fusion method for MAS-based OAR auto-contouring, which evaluates the segmentation performance in terms of both geometric accuracy and the dosimetric impact of the segmentation accuracy on the resulting treatment plan. Differently from the original selective and iterative method for performance level estimation (SIMPLE), we evaluated and rejected the atlases based on both Dice similarity coefficient and the predicted error of the dosimetric endpoints. The dosimetric error was predicted using our previously developed geometry-dosimetry model. We tested our method in MAS-based rectum auto-contouring on 20 prostate cancer patients. The accuracy in the rectum sub-volume close to the planning tumor volume (PTV), which was found to be a dosimetric sensitive region of the rectum, was greatly improved. The mean absolute distance between the obtained contour and the physician-drawn contour in the rectum sub-volume 2 mm away from PTV was reduced from 3.96 mm to 3.36 mm on average for the 20 patients, with the maximum decrease found to be from 9.22 mm to 3.75 mm. We also compared the dosimetric endpoints predicted for the obtained contours with those predicted for the physician-drawn contours. Our method led to smaller dosimetric endpoint errors than the SIMPLE method in 15 patients, comparable errors in 2 patients, and slightly larger errors in 3 patients. These results indicated the efficacy of our method in terms of considering both geometric accuracy and dosimetric impact during label fusion. Our algorithm can be applied to different tumor sites and radiation treatments, given a specifically trained geometry-dosimetry model.

A novel geometry-dosimetry label fusion method in multi-atlas segmentation for radiotherapy: a proof-of-concept study.

PubMed

Chang, Jina; Tian, Zhen; Lu, Weiguo; Gu, Xuejun; Chen, Mingli; Jiang, Steve B

2017-05-07

Multi-atlas segmentation (MAS) has been widely used to automate the delineation of organs at risk (OARs) for radiotherapy. Label fusion is a crucial step in MAS to cope with the segmentation variabilities among multiple atlases. However, most existing label fusion methods do not consider the potential dosimetric impact of the segmentation result. In this proof-of-concept study, we propose a novel geometry-dosimetry label fusion method for MAS-based OAR auto-contouring, which evaluates the segmentation performance in terms of both geometric accuracy and the dosimetric impact of the segmentation accuracy on the resulting treatment plan. Differently from the original selective and iterative method for performance level estimation (SIMPLE), we evaluated and rejected the atlases based on both Dice similarity coefficient and the predicted error of the dosimetric endpoints. The dosimetric error was predicted using our previously developed geometry-dosimetry model. We tested our method in MAS-based rectum auto-contouring on 20 prostate cancer patients. The accuracy in the rectum sub-volume close to the planning tumor volume (PTV), which was found to be a dosimetric sensitive region of the rectum, was greatly improved. The mean absolute distance between the obtained contour and the physician-drawn contour in the rectum sub-volume 2 mm away from PTV was reduced from 3.96 mm to 3.36 mm on average for the 20 patients, with the maximum decrease found to be from 9.22 mm to 3.75 mm. We also compared the dosimetric endpoints predicted for the obtained contours with those predicted for the physician-drawn contours. Our method led to smaller dosimetric endpoint errors than the SIMPLE method in 15 patients, comparable errors in 2 patients, and slightly larger errors in 3 patients. These results indicated the efficacy of our method in terms of considering both geometric accuracy and dosimetric impact during label fusion. Our algorithm can be applied to different tumor sites and radiation treatments, given a specifically trained geometry-dosimetry model.

Computer-assisted framework for machine-learning-based delineation of GTV regions on datasets of planning CT and PET/CT images.

PubMed

Ikushima, Koujiro; Arimura, Hidetaka; Jin, Ze; Yabu-Uchi, Hidetake; Kuwazuru, Jumpei; Shioyama, Yoshiyuki; Sasaki, Tomonari; Honda, Hiroshi; Sasaki, Masayuki

2017-01-01

We have proposed a computer-assisted framework for machine-learning-based delineation of gross tumor volumes (GTVs) following an optimum contour selection (OCS) method. The key idea of the proposed framework was to feed image features around GTV contours (determined based on the knowledge of radiation oncologists) into a machine-learning classifier during the training step, after which the classifier produces the 'degree of GTV' for each voxel in the testing step. Initial GTV regions were extracted using a support vector machine (SVM) that learned the image features inside and outside each tumor region (determined by radiation oncologists). The leave-one-out-by-patient test was employed for training and testing the steps of the proposed framework. The final GTV regions were determined using the OCS method that can be used to select a global optimum object contour based on multiple active delineations with a LSM around the GTV. The efficacy of the proposed framework was evaluated in 14 lung cancer cases [solid: 6, ground-glass opacity (GGO): 4, mixed GGO: 4] using the 3D Dice similarity coefficient (DSC), which denotes the degree of region similarity between the GTVs contoured by radiation oncologists and those determined using the proposed framework. The proposed framework achieved an average DSC of 0.777 for 14 cases, whereas the OCS-based framework produced an average DSC of 0.507. The average DSCs for GGO and mixed GGO were 0.763 and 0.701, respectively, obtained by the proposed framework. The proposed framework can be employed as a tool to assist radiation oncologists in delineating various GTV regions. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Differential contribution of early visual areas to the perceptual process of contour processing.

PubMed

Schira, Mark M; Fahle, Manfred; Donner, Tobias H; Kraft, Antje; Brandt, Stephan A

2004-04-01

We investigated contour processing and figure-ground detection within human retinotopic areas using event-related functional magnetic resonance imaging (fMRI) in 6 healthy and naïve subjects. A figure (6 degrees side length) was created by a 2nd-order texture contour. An independent and demanding foveal letter-discrimination task prevented subjects from noticing this more peripheral contour stimulus. The contour subdivided our stimulus into a figure and a ground. Using localizers and retinotopic mapping stimuli we were able to subdivide each early visual area into 3 eccentricity regions corresponding to 1) the central figure, 2) the area along the contour, and 3) the background. In these subregions we investigated the hemodynamic responses to our stimuli and compared responses with or without the contour defining the figure. No contour-related blood oxygenation level-dependent modulation in early visual areas V1, V3, VP, and MT+ was found. Significant signal modulation in the contour subregions of V2v, V2d, V3a, and LO occurred. This activation pattern was different from comparable studies, which might be attributable to the letter-discrimination task reducing confounding attentional modulation. In V3a, but not in any other retinotopic area, signal modulation corresponding to the central figure could be detected. Such contextual modulation will be discussed in light of the recurrent processing hypothesis and the role of visual awareness.

Earthquake Potential of the St. Louis District

DTIC Science & Technology

1981-02-01

The trends of the fault plane solutions strike northwest, northeast, and north-south indicating a complex generating mechanism . The focal depth for...thrust, strike-slip, oblique) is of prime importance in understanding seismic activity. Focal Mechanism Studies: A common method of obtaining regional... focal mechanisms , and to better understand magnitude-recurrence relations. Gravity and Magnetics: Gravity and magnetic contours may be used to

Accurate Morphology Preserving Segmentation of Overlapping Cells based on Active Contours

PubMed Central

Molnar, Csaba; Jermyn, Ian H.; Kato, Zoltan; Rahkama, Vesa; Östling, Päivi; Mikkonen, Piia; Pietiäinen, Vilja; Horvath, Peter

2016-01-01

The identification of fluorescently stained cell nuclei is the basis of cell detection, segmentation, and feature extraction in high content microscopy experiments. The nuclear morphology of single cells is also one of the essential indicators of phenotypic variation. However, the cells used in experiments can lose their contact inhibition, and can therefore pile up on top of each other, making the detection of single cells extremely challenging using current segmentation methods. The model we present here can detect cell nuclei and their morphology even in high-confluency cell cultures with many overlapping cell nuclei. We combine the “gas of near circles” active contour model, which favors circular shapes but allows slight variations around them, with a new data model. This captures a common property of many microscopic imaging techniques: the intensities from superposed nuclei are additive, so that two overlapping nuclei, for example, have a total intensity that is approximately double the intensity of a single nucleus. We demonstrate the power of our method on microscopic images of cells, comparing the results with those obtained from a widely used approach, and with manual image segmentations by experts. PMID:27561654

Digital modeling of end-mill cutting tools for FEM applications from the active cutting contour

NASA Astrophysics Data System (ADS)

Salguero, Jorge; Marcos, M.; Batista, M.; Gómez, A.; Mayuet, P.; Bienvenido, R.

2012-04-01

A very current technique in the research field of machining by material removal is the use of simulations using the Finite Element Method (FEM). Nevertheless, and although is widely used in processes that allows approximations to orthogonal cutting, such as shaping, is scarcely used in more complexes processes, such as milling. This fact is due principally to the complex geometry of the cutting tools in these processes, and the need to realize the studi es in an oblique cutting configuration. This paper shows a methodology for the geometrical characterization of commercial endmill cutting tools, by the extraction of the cutting tool contour, making use of optical metrology, and using this geometry to model the active cutting zone with a 3D CAD software. This model is easily exportable to different CAD formats, such as IGES or STEP, and importable from FEM software, where is possible to study the behavior in service of the same ones.

Investigation of anticancer properties of caffeinated complexes via computational chemistry methods

NASA Astrophysics Data System (ADS)

Sayin, Koray; Üngördü, Ayhan

2018-03-01

Computational investigations were performed for 1,3,7-trimethylpurine-2,6-dione, 3,7-dimethylpurine-2,6-dione, their Ru(II) and Os(III) complexes. B3LYP/6-311 ++G(d,p)(LANL2DZ) level was used in numerical calculations. Geometric parameters, IR spectrum, 1H-, 13C and 15N NMR spectrum were examined in detail. Additionally, contour diagram of frontier molecular orbitals (FMOs), molecular electrostatic potential (MEP) maps, MEP contour and some quantum chemical descriptors were used in the determination of reactivity rankings and active sites. The electron density on the surface was similar to each other in studied complexes. Quantum chemical descriptors were investigated and the anticancer activity of complexes were more than cisplatin and their ligands. Additionally, molecular docking calculations were performed in water between related complexes and a protein (ID: 3WZE). The most interact complex was found as Os complex. The interaction energy was calculated as 342.9 kJ/mol.

Wavelet energy-guided level set-based active contour: a segmentation method to segment highly similar regions.

PubMed

Achuthan, Anusha; Rajeswari, Mandava; Ramachandram, Dhanesh; Aziz, Mohd Ezane; Shuaib, Ibrahim Lutfi

2010-07-01

This paper introduces an approach to perform segmentation of regions in computed tomography (CT) images that exhibit intra-region intensity variations and at the same time have similar intensity distributions with surrounding/adjacent regions. In this work, we adapt a feature computed from wavelet transform called wavelet energy to represent the region information. The wavelet energy is embedded into a level set model to formulate the segmentation model called wavelet energy-guided level set-based active contour (WELSAC). The WELSAC model is evaluated using several synthetic and CT images focusing on tumour cases, which contain regions demonstrating the characteristics of intra-region intensity variations and having high similarity in intensity distributions with the adjacent regions. The obtained results show that the proposed WELSAC model is able to segment regions of interest in close correspondence with the manual delineation provided by the medical experts and to provide a solution for tumour detection. Copyright 2010 Elsevier Ltd. All rights reserved.

Venus: radar determination of gravity potential.

PubMed

Shapiro, I I; Pettengill, G H; Sherman, G N; Rogers, A E; Ingalls, R P

1973-02-02

We describe a method for the determination of the gravity potential of Venus from multiple-frequency radar measurements. The method is based on the strong frequency dependence of the absorption of radio waves in Venus' atmosphere. Comparison of the differing radar reflection intensities at several frequencies yields the height of the surface relative to a reference pressure contour; combination with measurements of round-trip echo delays allows the pressure, and hence the gravity potential contour, to be mapped relative to the mean planet radius. Since calibration data from other frequencies are unavailable, the absorption-sensitive Haystack Observatory data have been analyzed under the assumption of uniform surface reflectivity to yield a gravity equipotential contour for the equatorial region and a tentative upper bound of 6 x 10(-4) on the fractional difference of Venus' principal equatorial moments of inertia. The minima in the equipotential contours appear to be associated with topographic minima.

Direct imaging of isofrequency contours in photonic structures

DOE PAGES

Regan, E. C.; Igarashi, Y.; Zhen, B.; ...

2016-11-25

The isofrequency contours of a photonic crystal are important for predicting and understanding exotic optical phenomena that are not apparent from high-symmetry band structure visualizations. We demonstrate a method to directly visualize the isofrequency contours of high-quality photonic crystal slabs that show quantitatively good agreement with numerical results throughout the visible spectrum. Our technique relies on resonance-enhanced photon scattering from generic fabrication disorder and surface roughness, so it can be applied to general photonic and plasmonic crystals or even quasi-crystals. We also present an analytical model of the scattering process, which explains the observation of isofrequency contours in our technique.more » Furthermore, the isofrequency contours provide information about the characteristics of the disorder and therefore serve as a feedback tool to improve fabrication processes.« less

Detection and visualization of endoleaks in CT data for monitoring of thoracic and abdominal aortic aneurysm stents

NASA Astrophysics Data System (ADS)

Lu, J.; Egger, J.; Wimmer, A.; Großkopf, S.; Freisleben, B.

2008-03-01

In this paper we present an efficient algorithm for the segmentation of the inner and outer boundary of thoratic and abdominal aortic aneurysms (TAA & AAA) in computed tomography angiography (CTA) acquisitions. The aneurysm segmentation includes two steps: first, the inner boundary is segmented based on a grey level model with two thresholds; then, an adapted active contour model approach is applied to the more complicated outer boundary segmentation, with its initialization based on the available inner boundary segmentation. An opacity image, which aims at enhancing important features while reducing spurious structures, is calculated from the CTA images and employed to guide the deformation of the model. In addition, the active contour model is extended by a constraint force that prevents intersections of the inner and outer boundary and keeps the outer boundary at a distance, given by the thrombus thickness, to the inner boundary. Based upon the segmentation results, we can measure the aneurysm size at each centerline point on the centerline orthogonal multiplanar reformatting (MPR) plane. Furthermore, a 3D TAA or AAA model is reconstructed from the set of segmented contours, and the presence of endoleaks is detected and highlighted. The implemented method has been evaluated on nine clinical CTA data sets with variations in anatomy and location of the pathology and has shown promising results.

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

Lamichhane, N; Johnson, P; Chinea, F

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference.more » Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of contour accuracy based purely on image feature analysis.« less

Retroperitoneal Sarcoma Target Volume and Organ at Risk Contour Delineation Agreement Among NRG Sarcoma Radiation Oncologists

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

Baldini, Elizabeth H., E-mail: ebaldini@partners.org; Abrams, Ross A.; Bosch, Walter

Purpose: The purpose of this study was to evaluate the variability in target volume and organ at risk (OAR) contour delineation for retroperitoneal sarcoma (RPS) among 12 sarcoma radiation oncologists. Methods and Materials: Radiation planning computed tomography (CT) scans for 2 cases of RPS were distributed among 12 sarcoma radiation oncologists with instructions for contouring gross tumor volume (GTV), clinical target volume (CTV), high-risk CTV (HR CTV: area judged to be at high risk of resulting in positive margins after resection), and OARs: bowel bag, small bowel, colon, stomach, and duodenum. Analysis of contour agreement was performed using the simultaneousmore » truth and performance level estimation (STAPLE) algorithm and kappa statistics. Results: Ten radiation oncologists contoured both RPS cases, 1 contoured only RPS1, and 1 contoured only RPS2 such that each case was contoured by 11 radiation oncologists. The first case (RPS 1) was a patient with a de-differentiated (DD) liposarcoma (LPS) with a predominant well-differentiated (WD) component, and the second case (RPS 2) was a patient with DD LPS made up almost entirely of a DD component. Contouring agreement for GTV and CTV contours was high. However, the agreement for HR CTVs was only moderate. For OARs, agreement for stomach, bowel bag, small bowel, and colon was high, but agreement for duodenum (distorted by tumor in one of these cases) was fair to moderate. Conclusions: For preoperative treatment of RPS, sarcoma radiation oncologists contoured GTV, CTV, and most OARs with a high level of agreement. HR CTV contours were more variable. Further clarification of this volume with the help of sarcoma surgical oncologists is necessary to reach consensus. More attention to delineation of the duodenum is also needed.« less

Retroperitoneal Sarcoma Target Volume and Organ at Risk Contour Delineation Agreement Among NRG Sarcoma Radiation Oncologists

PubMed Central

Baldini, Elizabeth H.; Abrams, Ross A.; Bosch, Walter; Roberge, David; Haas, Rick L.M.; Catton, Charles N.; Indelicato, Daniel J.; Olsen, Jeffrey R.; Deville, Curtiland; Chen, Yen-Lin; Finkelstein, Steven E.; DeLaney, Thomas F.; Wang, Dian

2015-01-01

Purpose The purpose of this study was to evaluate the variability in target volume and organ at risk (OAR) contour delineation for retroperitoneal sarcoma (RPS) among 12 sarcoma radiation oncologists. Methods and Materials Radiation planning computed tomography (CT) scans for 2 cases of RPS were distributed among 12 sarcoma radiation oncologists with instructions for contouring gross tumor volume (GTV), clinical target volume (CTV), high-risk CTV (HR CTV: area judged to be at high risk of resulting in positive margins after resection), and OARs: bowel bag, small bowel, colon, stomach, and duodenum. Analysis of contour agreement was performed using the simultaneous truth and performance level estimation (STAPLE) algorithm and kappa statistics. Results Ten radiation oncologists contoured both RPS cases, 1 contoured only RPS1, and 1 contoured only RPS2 such that each case was contoured by 11 radiation oncologists. The first case (RPS 1) was a patient with a de-differentiated (DD) liposarcoma (LPS) with a predominant well-differentiated (WD) component, and the second case (RPS 2) was a patient with DD LPS made up almost entirely of a DD component. Contouring agreement for GTV and CTV contours was high. However, the agreement for HR CTVs was only moderate. For OARs, agreement for stomach, bowel bag, small bowel, and colon was high, but agreement for duodenum (distorted by tumor in one of these cases) was fair to moderate. Conclusions For preoperative treatment of RPS, sarcoma radiation oncologists contoured GTV, CTV, and most OARs with a high level of agreement. HR CTV contours were more variable. Further clarification of this volume with the help of sarcoma surgical oncologists is necessary to reach consensus. More attention to delineation of the duodenum is also needed. PMID:26194680

Deformable medical image registration of pleural cavity for photodynamic therapy by using finite-element based method

NASA Astrophysics Data System (ADS)

Penjweini, Rozhin; Kim, Michele M.; Dimofte, Andrea; Finlay, Jarod C.; Zhu, Timothy C.

2016-03-01

When the pleural cavity is opened during the surgery portion of pleural photodynamic therapy (PDT) of malignant mesothelioma, the pleural volume will deform. This impacts the delivered dose when using highly conformal treatment techniques. To track the anatomical changes and contour the lung and chest cavity, an infrared camera-based navigation system (NDI) is used during PDT. In the same patient, a series of computed tomography (CT) scans of the lungs are also acquired before the surgery. The reconstructed three-dimensional contours from both NDI and CTs are imported into COMSOL Multiphysics software, where a finite element-based (FEM) deformable image registration is obtained. The CT contour is registered to the corresponding NDI contour by overlapping the center of masses and aligning their orientations. The NDI contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Deformed Geometry model is applied in COMSOL to obtain a deformed target contour. The distortion of the volume at X, Y and Z is mapped to illustrate the transformation of the target contour. The initial assessment shows that FEM-based image deformable registration can fuse images acquired by different modalities. It provides insights into the deformation of anatomical structures along X, Y and Z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting three-dimensional deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery.

Extraction of breast lesions from ultrasound imagery: Bhattacharyya gradient flow approach

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Sandhu, Romeil; Tannenbaum, Allen

2018-03-01

Breast cancer is one of the most commonly diagnosed neoplasms among American women and the second leading cause of death among women all over the world. In order to reduce the mortality rate and cost of treatment, early diagnosis and treatment are essential. Accurate and reliable diagnosis is required in order to ensure the most effective treatment and a second opinion is often advisable. In this paper, we address the problem of breast lesion detection from ultrasound imagery by means of active contours, whose evolution is driven by maximizing the Bhattacharyya distance1 between the probability density functions (PDFs). The proposed method was applied to ultrasound breast imagery, and the lesion boundary was obtained by maximizing the distance-based energy functional such that the maximum (optimal contour) is attained at the boundary of the potential lesion. We compared the results of the proposed method quantitatively using the Dice coefficient (similarity index)2 to well-known GrowCut segmentation method3 and demonstrated that Bhattacharyya approach outperforms GrowCut in most of the cases.

TU-AB-303-02: A Novel Surrogate to Identify Anatomical Changes During Radiotherapy of Head and Neck Cancer Patients

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

Gros, S; Roeske, J; Surucu, M

Purpose: To develop a novel method to monitor external anatomical changes in head and neck cancer patients in order to help guide adaptive radiotherapy decisions. Methods: The method, developed in MATLAB, reveals internal anatomical changes based on variations observed in external anatomy. Weekly kV-CBCT scans from 11 Head and neck patients were retrospectively analyzed. The pre-processing step first corrects each CBCT for artifacts and removes pixels from the immobilization mask to produce an accurate external contour of the patient’s skin. After registering the CBCTs to the initial planning CT, the external contours from each CBCT (CBCTn) are transferred to themore » first week — reference — CBCT{sub 1}. Contour radii, defined as the distances between an external contour and the central pixel of each CBCT slice, are calculated for each scan at angular increments of 1 degree. The changes in external anatomy are then quantified by the difference in radial distance between the external contours of CBCT1 and CBCTn. The radial difference is finally displayed on a 2D intensity map (angle vs radial distance difference) in order to highlight regions of interests with significant changes. Results: The 2D radial difference maps provided qualitative and quantitative information, such as the location and the magnitude of external contour divergences and the rate at which these deviations occur. With this method, anatomical changes due to tumor volume shrinkage and patient weight loss were clearly identified and could be correlated with the under-dosage of targets or over-dosage of OARs. Conclusion: This novel method provides an efficient tool to visualize 3D external anatomical modification on a single 2D map. It quickly pinpoints the location of differences in anatomy during the course of radiotherapy, which can help determine if a treatment plan needs to be adapted.« less

Cardiac output by pulse contour analysis does not match the increase measured by rebreathing during human spaceflight.

PubMed

Hughson, Richard L; Peterson, Sean D; Yee, Nicholas J; Greaves, Danielle K

2017-11-01

Pulse contour analysis of the noninvasive finger arterial pressure waveform provides a convenient means to estimate cardiac output (Q̇). The method has been compared with standard methods under a range of conditions but never before during spaceflight. We compared pulse contour analysis with the Modelflow algorithm to estimates of Q̇ obtained by rebreathing during preflight baseline testing and during the final month of long-duration spaceflight in nine healthy male astronauts. By Modelflow analysis, stroke volume was greater in supine baseline than seated baseline or inflight. Heart rate was reduced in supine baseline so that there were no differences in Q̇ by Modelflow estimate between the supine (7.02 ± 1.31 l/min, means ± SD), seated (6.60 ± 1.95 l/min), or inflight (5.91 ± 1.15 l/min) conditions. In contrast, rebreathing estimates of Q̇ increased from seated baseline (4.76 ± 0.67 l/min) to inflight (7.00 ± 1.39 l/min, significant interaction effect of method and spaceflight, P < 0.001). Pulse contour analysis utilizes a three-element Windkessel model that incorporates parameters dependent on aortic pressure-area relationships that are assumed to represent the entire circulation. We propose that a large increase in vascular compliance in the splanchnic circulation invalidates the model under conditions of spaceflight. Future spaceflight research measuring cardiac function needs to consider this important limitation for assessing absolute values of Q̇ and stroke volume. NEW & NOTEWORTHY Noninvasive assessment of cardiac function during human spaceflight is an important tool to monitor astronaut health. This study demonstrated that pulse contour analysis of finger arterial blood pressure to estimate cardiac output failed to track the 46% increase measured by a rebreathing method. These results strongly suggest that alternative methods not dependent on pulse contour analysis are required to track cardiac function in spaceflight. Copyright © 2017 the American Physiological Society.

On-line and Mobil Learning Activities

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Whittaker, T. M.; Jasmin, T.; Mooney, M. E.

2012-12-01

Introductory college-level science courses for non-majors are critical gateways to imparting not only discipline-specific information, but also the basics of the scientific method and how science influences society. They are also indispensable for student success to degree. On-line, web-based homework (whether on computers or mobile devices) is a rapidly growing use of the Internet and is becoming a major component of instruction in science, replacing delayed feedback from a few major exams. Web delivery and grading of traditional textbook-type questions is equally effective as having students write them out for hand grading, as measured by student performance on conceptual and problem solving exams. During this presentation we will demonstrate some of the interactive on-line activities used to teach concepts and how scientists approach problem solving, and how these activities have impacted student learning. Evaluation of the activities, including formative and summative, will be discussed and provide evidence that these interactive activities significantly enhance understanding of introductory meteorological concepts in a college-level science course. More advanced interactive activities are also used in our courses for department majors, some of these will be discussed and demonstrated. Bring your mobile devices to play along! Here is an example on teaching contouring: http://profhorn.aos.wisc.edu/wxwise/contour/index.html

Three-dimensional adult male head and skull contours.

PubMed

Lee, Calvin; Loyd, Andre M; Nightingale, Roger; Myers, Barry S; Damon, Andrew; Bass, Cameron R

2014-01-01

Traumatic brain injury (TBI) is a major public health issue, affecting millions of people annually. Anthropomorphic test devices (ATDs) and finite element models (FEMs) provide a means of understanding factors leading to TBI, potentially reducing the occurrence. Thus, there is a need to ensure that these tools accurately model humans. For example, the Hybrid III was not based on 3-dimensional human head shape data. The objective of this study is to produce average head and skull contours for an average U.S. male that can be used for ATDs and FEMs. Computed tomography (CT) scans of adult male heads were obtained from a database provided by the University of Virginia Center for Applied Biomechanics. An orthographic viewer was used to extract head and skull contours from the CT scans. Landmarks were measured graphically using HyperMesh (Altair, HyperWorks). To determine the head occipital condyle (OC) centroid, surface meshes of the OCs were made and the centroid of the surfaces was calculated. The Hybrid III contour was obtained using a MicroScribe Digitizer (Solution Technologies, Inc., Oella, MD). Comparisons of the average male and ATD contours were performed using 2 methods: (1) the midsagittal and midcoronal ATD contours relative to the OC centroid were compared to the corresponding 1 SD range of the average male contours; (2) the ATD sagittal contour was translated relative to the average male sagittal contour to minimize the area between the 2 contours. Average male head and skull contours were created. Landmark measurements were made for the dorsum sellae, nasion skin, nasion bone, infraorbital foramen, and external auditory meatus, all relative to the OC centroid. The Hybrid III midsagittal contour was outside the 1 SD range for 15.2 percent of the average male head contour but only by a maximum distance of 1.5 mm, whereas the Hybrid III midcoronal head contour was outside the 1 SD range for 12.2 percent of the average male head contour by a maximum distance of 2 mm. Minimization of the area between the midsagittal contours resulted in only 2.3 mm of translation, corroborating the good correlation between the contours established by initial comparison. Three-dimensional average male head and skull contours were created and measurements of landmark locations were made. It was found that the 50th percentile male Hybrid III corresponds well to the average male head contour and validated its 3D shape. Average adult head and skull contours and landmark data are available for public research use at http://biomechanics.pratt.duke.edu/data .

On a program manifold's stability of one contour automatic control systems

NASA Astrophysics Data System (ADS)

Zumatov, S. S.

2017-12-01

Methodology of analysis of stability is expounded to the one contour systems automatic control feedback in the presence of non-linearities. The methodology is based on the use of the simplest mathematical models of the nonlinear controllable systems. Stability of program manifolds of one contour automatic control systems is investigated. The sufficient conditions of program manifold's absolute stability of one contour automatic control systems are obtained. The Hurwitz's angle of absolute stability was determined. The sufficient conditions of program manifold's absolute stability of control systems by the course of plane in the mode of autopilot are obtained by means Lyapunov's second method.

Segmenting breast cancerous regions in thermal images using fuzzy active contours

PubMed Central

Ghayoumi Zadeh, Hossein; Haddadnia, Javad; Rahmani Seryasat, Omid; Mostafavi Isfahani, Sayed Mohammad

2016-01-01

Breast cancer is the main cause of death among young women in developing countries. The human body temperature carries critical medical information related to the overall body status. Abnormal rise in total and regional body temperature is a natural symptom in diagnosing many diseases. Thermal imaging (Thermography) utilizes infrared beams which are fast, non-invasive, and non-contact and the output created images by this technique are flexible and useful to monitor the temperature of the human body. In some clinical studies and biopsy tests, it is necessary for the clinician to know the extent of the cancerous area. In such cases, the thermal image is very useful. In the same line, to detect the cancerous tissue core, thermal imaging is beneficial. This paper presents a fully automated approach to detect the thermal edge and core of the cancerous area in thermography images. In order to evaluate the proposed method, 60 patients with an average age of 44/9 were chosen. These cases were suspected of breast tissue disease. These patients referred to Tehran Imam Khomeini Imaging Center. Clinical examinations such as ultrasound, biopsy, questionnaire, and eventually thermography were done precisely on these individuals. Finally, the proposed model is applied for segmenting the proved abnormal area in thermal images. The proposed model is based on a fuzzy active contour designed by fuzzy logic. The presented method can segment cancerous tissue areas from its borders in thermal images of the breast area. In order to evaluate the proposed algorithm, Hausdorff and mean distance between manual and automatic method were used. Estimation of distance was conducted to accurately separate the thermal core and edge. Hausdorff distance between the proposed and the manual method for thermal core and edge was 0.4719 ± 0.4389, 0.3171 ± 0.1056 mm respectively, and the average distance between the proposed and the manual method for core and thermal edge was 0.0845 ± 0.0619, 0.0710 ± 0.0381 mm respectively. Furthermore, the sensitivity in recognizing the thermal pattern in breast tissue masses is 85 % and its accuracy is 91.98 %.A thermal imaging system has been proposed that is able to recognize abnormal breast tissue masses. This system utilizes fuzzy active contours to extract the abnormal regions automatically. PMID:28096784

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Boundary fitting based segmentation of fluorescence microscopy images

NASA Astrophysics Data System (ADS)

Lee, Soonam; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2015-03-01

Segmentation is a fundamental step in quantifying characteristics, such as volume, shape, and orientation of cells and/or tissue. However, quantification of these characteristics still poses a challenge due to the unique properties of microscopy volumes. This paper proposes a 2D segmentation method that utilizes a combination of adaptive and global thresholding, potentials, z direction refinement, branch pruning, end point matching, and boundary fitting methods to delineate tubular objects in microscopy volumes. Experimental results demonstrate that the proposed method achieves better performance than an active contours based scheme.

SU-E-J-124: FDG PET Metrics Analysis in the Context of An Adaptive PET Protocol for Node Positive Gynecologic Cancer Patients

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

Nawrocki, J; Chino, J; Light, K

2014-06-01

Purpose: To compare PET extracted metrics and investigate the role of a gradient-based PET segmentation tool, PET Edge (MIM Software Inc., Cleveland, OH), in the context of an adaptive PET protocol for node positive gynecologic cancer patients. Methods: An IRB approved protocol enrolled women with gynecological, PET visible malignancies. A PET-CT was obtained for treatment planning prescribed to 45–50.4Gy with a 55– 70Gy boost to the PET positive nodes. An intra-treatment PET-CT was obtained between 30–36Gy, and all volumes re-contoured. Standard uptake values (SUVmax, SUVmean, SUVmedian) and GTV volumes were extracted from the clinician contoured GTVs on the pre- andmore » intra-treament PET-CT for primaries and nodes and compared with a two tailed Wilcoxon signed-rank test. The differences between primary and node GTV volumes contoured in the treatment planning system and those volumes generated using PET Edge were also investigated. Bland-Altman plots were used to describe significant differences between the two contouring methods. Results: Thirteen women were enrolled in this study. The median baseline/intra-treatment primary (SUVmax, mean, median) were (30.5, 9.09, 7.83)/( 16.6, 4.35, 3.74), and nodes were (20.1, 4.64, 3.93)/( 6.78, 3.13, 3.26). The p values were all < 0.001. The clinical contours were all larger than the PET Edge generated ones, with mean difference of +20.6 ml for primary, and +23.5 ml for nodes. The Bland-Altman revealed changes between clinician/PET Edge contours to be mostly within the margins of the coefficient of variability. However, there was a proportional trend, i.e. the larger the GTV, the larger the clinical contours as compared to PET Edge contours. Conclusion: Primary and node SUV values taken from the intratreament PET-CT can be used to assess the disease response and to design an adaptive plan. The PET Edge tool can streamline the contouring process and lead to smaller, less user-dependent contours.« less

Estimation of uncertainty for contour method residual stress measurements

DOE PAGES

Olson, Mitchell D.; DeWald, Adrian T.; Prime, Michael B.; ...

2014-12-03

This paper describes a methodology for the estimation of measurement uncertainty for the contour method, where the contour method is an experimental technique for measuring a two-dimensional map of residual stress over a plane. Random error sources including the error arising from noise in displacement measurements and the smoothing of the displacement surfaces are accounted for in the uncertainty analysis. The output is a two-dimensional, spatially varying uncertainty estimate such that every point on the cross-section where residual stress is determined has a corresponding uncertainty value. Both numerical and physical experiments are reported, which are used to support the usefulnessmore » of the proposed uncertainty estimator. The uncertainty estimator shows the contour method to have larger uncertainty near the perimeter of the measurement plane. For the experiments, which were performed on a quenched aluminum bar with a cross section of 51 × 76 mm, the estimated uncertainty was approximately 5 MPa (σ/E = 7 · 10⁻⁵) over the majority of the cross-section, with localized areas of higher uncertainty, up to 10 MPa (σ/E = 14 · 10⁻⁵).« less

In Situ 3D Monitoring of Geometric Signatures in the Powder-Bed-Fusion Additive Manufacturing Process via Vision Sensing Methods

PubMed Central

Li, Zhongwei; Liu, Xingjian; Wen, Shifeng; He, Piyao; Zhong, Kai; Wei, Qingsong; Shi, Yusheng; Liu, Sheng

2018-01-01

Lack of monitoring of the in situ process signatures is one of the challenges that has been restricting the improvement of Powder-Bed-Fusion Additive Manufacturing (PBF AM). Among various process signatures, the monitoring of the geometric signatures is of high importance. This paper presents the use of vision sensing methods as a non-destructive in situ 3D measurement technique to monitor two main categories of geometric signatures: 3D surface topography and 3D contour data of the fusion area. To increase the efficiency and accuracy, an enhanced phase measuring profilometry (EPMP) is proposed to monitor the 3D surface topography of the powder bed and the fusion area reliably and rapidly. A slice model assisted contour detection method is developed to extract the contours of fusion area. The performance of the techniques is demonstrated with some selected measurements. Experimental results indicate that the proposed method can reveal irregularities caused by various defects and inspect the contour accuracy and surface quality. It holds the potential to be a powerful in situ 3D monitoring tool for manufacturing process optimization, close-loop control, and data visualization. PMID:29649171

Automated detection of abnormalities in paranasal sinus on dental panoramic radiographs by using contralateral subtraction technique based on mandible contour

NASA Astrophysics Data System (ADS)

Mori, Shintaro; Hara, Takeshi; Tagami, Motoki; Muramatsu, Chicako; Kaneda, Takashi; Katsumata, Akitoshi; Fujita, Hiroshi

2013-02-01

Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is important for the early treatment, but general dentists may not recognize the findings because they focus on teeth treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.

A level-set method for pathology segmentation in fluorescein angiograms and en face retinal images of patients with age-related macular degeneration

NASA Astrophysics Data System (ADS)

Mohammad, Fatimah; Ansari, Rashid; Shahidi, Mahnaz

2013-03-01

The visibility and continuity of the inner segment outer segment (ISOS) junction layer of the photoreceptors on spectral domain optical coherence tomography images is known to be related to visual acuity in patients with age-related macular degeneration (AMD). Automatic detection and segmentation of lesions and pathologies in retinal images is crucial for the screening, diagnosis, and follow-up of patients with retinal diseases. One of the challenges of using the classical level-set algorithms for segmentation involves the placement of the initial contour. Manually defining the contour or randomly placing it in the image may lead to segmentation of erroneous structures. It is important to be able to automatically define the contour by using information provided by image features. We explored a level-set method which is based on the classical Chan-Vese model and which utilizes image feature information for automatic contour placement for the segmentation of pathologies in fluorescein angiograms and en face retinal images of the ISOS layer. This was accomplished by exploiting a priori knowledge of the shape and intensity distribution allowing the use of projection profiles to detect the presence of pathologies that are characterized by intensity differences with surrounding areas in retinal images. We first tested our method by applying it to fluorescein angiograms. We then applied our method to en face retinal images of patients with AMD. The experimental results included demonstrate that the proposed method provided a quick and improved outcome as compared to the classical Chan-Vese method in which the initial contour is randomly placed, thus indicating the potential to provide a more accurate and detailed view of changes in pathologies due to disease progression and treatment.

Semi-automated contour recognition using DICOMautomaton

NASA Astrophysics Data System (ADS)

Clark, H.; Wu, J.; Moiseenko, V.; Lee, R.; Gill, B.; Duzenli, C.; Thomas, S.

2014-03-01

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

Fringe-shifting single-projector moiré topography application for cotyle implantate abrasion measurement

NASA Astrophysics Data System (ADS)

Rössler, Tomáš; Hrabovský, Miroslav; Pluháček, František

2005-08-01

The cotyle implantate is abraded in the body of patient and its shape changes. Information about the magnitude of abrasion is contained in the result contour map of the implantate. The locations and dimensions of abraded areas can be computed from the contours deformation. The method called the single-projector moire topography was used for the contour lines determination. The theoretical description of method is given at first. The design of the experimental set-up follows. The light grating projector was developed to realize the periodic structure on the measured surface. The method of fringe-shifting was carried out to increase the data quantity. The description of digital processing applied to the moire grating images is introduced at the end together with the examples of processed images.

Color and Contour Based Identification of Stem of Coconut Bunch

NASA Astrophysics Data System (ADS)

Kannan Megalingam, Rajesh; Manoharan, Sakthiprasad K.; Reddy, Rajesh G.; Sriteja, Gone; Kashyap, Ashwin

2017-08-01

Vision is the key component of Artificial Intelligence and Automated Robotics. Sensors or Cameras are the sight organs for a robot. Only through this, they are able to locate themselves or identify the shape of a regular or an irregular object. This paper presents the method of Identification of an object based on color and contour recognition using a camera through digital image processing techniques for robotic applications. In order to identify the contour, shape matching technique is used, which takes the input data from the database provided, and uses it to identify the contour by checking for shape match. The shape match is based on the idea of iterating through each contour of the threshold image. The color is identified on HSV Scale, by approximating the desired range of values from the database. HSV data along with iteration is used for identifying a quadrilateral, which is our required contour. This algorithm could also be used in a non-deterministic plane, which only uses HSV values exclusively.

On the Application of Contour Bumps for Transonic Drag Reduction(Invited)

NASA Technical Reports Server (NTRS)

Milholen, William E., II; Owens, Lewis R.

2005-01-01

The effect of discrete contour bumps on reducing the transonic drag at off-design conditions on an airfoil have been examined. The research focused on fully-turbulent flow conditions, at a realistic flight chord Reynolds number of 30 million. State-of-the-art computational fluid dynamics methods were used to design a new baseline airfoil, and a family of fixed contour bumps. The new configurations were experimentally evaluated in the 0.3-m Transonic Cryogenic Tunnel at the NASA Langley Research center, which utilizes an adaptive wall test section to minimize wall interference. The computational study showed that transonic drag reduction, on the order of 12% - 15%, was possible using a surface contour bump to spread a normal shock wave. The computational study also indicated that the divergence drag Mach number was increased for the contour bump applications. Preliminary analysis of the experimental data showed a similar contour bump effect, but this data needed to be further analyzed for residual wall interference corrections.

SU-C-BRA-02: Gradient Based Method of Target Delineation On PET/MR Image of Head and Neck Cancer Patients

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

Dance, M; Chera, B; Falchook, A

2015-06-15

Purpose: Validate the consistency of a gradient-based segmentation tool to facilitate accurate delineation of PET/CT-based GTVs in head and neck cancers by comparing against hybrid PET/MR-derived GTV contours. Materials and Methods: A total of 18 head and neck target volumes (10 primary and 8 nodal) were retrospectively contoured using a gradient-based segmentation tool by two observers. Each observer independently contoured each target five times. Inter-observer variability was evaluated via absolute percent differences. Intra-observer variability was examined by percentage uncertainty. All target volumes were also contoured using the SUV percent threshold method. The thresholds were explored case by case so itsmore » derived volume matched with the gradient-based volume. Dice similarity coefficients (DSC) were calculated to determine overlap of PET/CT GTVs and PET/MR GTVs. Results: The Levene’s test showed there was no statistically significant difference of the variances between the observer’s gradient-derived contours. However, the absolute difference between the observer’s volumes was 10.83%, with a range from 0.39% up to 42.89%. PET-avid regions with qualitatively non-uniform shapes and intensity levels had a higher absolute percent difference near 25%, while regions with uniform shapes and intensity levels had an absolute percent difference of 2% between observers. The average percentage uncertainty between observers was 4.83% and 7%. As the volume of the gradient-derived contours increased, the SUV threshold percent needed to match the volume decreased. Dice coefficients showed good agreement of the PET/CT and PET/MR GTVs with an average DSC value across all volumes at 0.69. Conclusion: Gradient-based segmentation of PET volume showed good consistency in general but can vary considerably for non-uniform target shapes and intensity levels. PET/CT-derived GTV contours stemming from the gradient-based tool show good agreement with the anatomically and metabolically more accurate PET/MR-derived GTV contours, but tumor delineation accuracy can be further improved with the use PET/MR.« less

SU-F-J-171: Robust Atlas Based Segmentation of the Prostate and Peripheral Zone Regions On MRI Utilizing Multiple MRI System Vendors

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

Padgett, K; Pollack, A; Stoyanova, R

Purpose: Automatically generated prostate MRI contours can be used to aid in image registration with CT or ultrasound and to reduce the burden of contouring for radiation treatment planning. In addition, prostate and zonal contours can assist to automate quantitative imaging features extraction and the analyses of longitudinal MRI studies. These potential gains are limited if the solutions are not compatible across different MRI vendors. The goal of this study is to characterize an atlas based automatic segmentation procedure of the prostate collected on MRI systems from multiple vendors. Methods: The prostate and peripheral zone (PZ) were manually contoured bymore » an expert radiation oncologist on T2-weighted scans acquired on both GE (n=31) and Siemens (n=33) 3T MRI systems. A leave-one-out approach was utilized where the target subject is removed from the atlas before the segmentation algorithm is initiated. The atlas-segmentation method finds the best nine matched atlas subjects and then performs a normalized intensity-based free-form deformable registration of these subjects to the target subject. These nine contours are then merged into a single contour using Simultaneous Truth and Performance Level Estimation (STAPLE). Contour comparisons were made using Dice similarity coefficients (DSC) and Hausdorff distances. Results: Using the T2 FatSat (FS) GE datasets the atlas generated contours resulted in an average DSC of 0.83±0.06 for prostate, 0.57±0.12 for PZ and 0.75±0.09 for CG. Similar results were found when using the Siemens data with a DSC of 0.79±0.14 for prostate, 0.54±0.16 and 0.70±0.9. Contrast between prostate and surrounding anatomy and between the PZ and CG contours for both vendors demonstrated superior contrast separation; significance was found for all comparisons p-value < 0.0001. Conclusion: Atlas-based segmentation yielded promising results for all contours compared to expertly defined contours in both Siemens and GE 3T systems providing fast and automatic segmentation of the prostate. Funding Support, Disclosures, and Conflict of Interest: AS Nelson is a partial owner of MIM Software, Inc. AS Nelson, and A Swallen are current employees at MIM Software, Inc.« less

BOREAS HYD-8 DEM Data Over the NSA-MSA and SSA-MSA in the UTM Projection

NASA Technical Reports Server (NTRS)

Wang, Xue-Wen; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Band, L. E.; Smith, David E. (Technical Monitor)

2000-01-01

The BOREAS HYD-8 team focused on describing the scaling behavior of water and carbon flux processes at local and regional scales. These DEMs were produced from digitized contours at a cell resolution of 100 meters. Vector contours of the area were used as input to a software package that interpolates between contours to create a DEM representing the terrain surface. The vector contours had a contour interval of 25 feet. The data cover the BOREAS MSAs of the SSA and NSA and are given in a UTM map projection. Most of the elevation data from which the DEM was produced were collected in the 1970s or 1980s. The data are stored in binary, image format files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

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.

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness.

PubMed

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations ( R 2 = 0.61-0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis ( R 2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design.

High-Throughput Field Phenotyping of Leaves, Leaf Sheaths, Culms and Ears of Spring Barley Cultivars at Anthesis and Dough Ripeness

PubMed Central

Barmeier, Gero; Schmidhalter, Urs

2017-01-01

To optimize plant architecture (e.g., photosynthetic active leaf area, leaf-stem ratio), plant physiologists and plant breeders rely on destructively and tediously harvested biomass samples. A fast and non-destructive method for obtaining information about different plant organs could be vehicle-based spectral proximal sensing. In this 3-year study, the mobile phenotyping platform PhenoTrac 4 was used to compare the measurements from active and passive spectral proximal sensors of leaves, leaf sheaths, culms and ears of 34 spring barley cultivars at anthesis and dough ripeness. Published vegetation indices (VI), partial least square regression (PLSR) models and contour map analysis were compared to assess these traits. Contour maps are matrices consisting of coefficients of determination for all of the binary combinations of wavelengths and the biomass parameters. The PLSR models of leaves, leaf sheaths and culms showed strong correlations (R2 = 0.61–0.76). Published vegetation indices depicted similar coefficients of determination; however, their RMSEs were higher. No wavelength combination could be found by the contour map analysis to improve the results of the PLSR or published VIs. The best results were obtained for the dry weight and N uptake of leaves and culms. The PLSR models yielded satisfactory relationships for leaf sheaths at anthesis (R2 = 0.69), whereas only a low performance for all of sensors and methods was observed at dough ripeness. No relationships with ears were observed. Active and passive sensors performed comparably, with slight advantages observed for the passive spectrometer. The results indicate that tractor-based proximal sensing in combination with optimized spectral indices or PLSR models may represent a suitable tool for plant breeders to assess relevant morphological traits, allowing for a better understanding of plant architecture, which is closely linked to the physiological performance. Further validation of PLSR models is required in independent studies. Organ specific phenotyping represents a first step toward breeding by design. PMID:29163629

A Multiphase Validation of Atlas-Based Automatic and Semiautomatic Segmentation Strategies for Prostate MRI

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

Martin, Spencer; Rodrigues, George, E-mail: george.rodrigues@lhsc.on.ca; Department of Epidemiology/Biostatistics, University of Western Ontario, London

2013-01-01

Purpose: To perform a rigorous technological assessment and statistical validation of a software technology for anatomic delineations of the prostate on MRI datasets. Methods and Materials: A 3-phase validation strategy was used. Phase I consisted of anatomic atlas building using 100 prostate cancer MRI data sets to provide training data sets for the segmentation algorithms. In phase II, 2 experts contoured 15 new MRI prostate cancer cases using 3 approaches (manual, N points, and region of interest). In phase III, 5 new physicians with variable MRI prostate contouring experience segmented the same 15 phase II datasets using 3 approaches: manual,more » N points with no editing, and full autosegmentation with user editing allowed. Statistical analyses for time and accuracy (using Dice similarity coefficient) endpoints used traditional descriptive statistics, analysis of variance, analysis of covariance, and pooled Student t test. Results: In phase I, average (SD) total and per slice contouring time for the 2 physicians was 228 (75), 17 (3.5), 209 (65), and 15 seconds (3.9), respectively. In phase II, statistically significant differences in physician contouring time were observed based on physician, type of contouring, and case sequence. The N points strategy resulted in superior segmentation accuracy when initial autosegmented contours were compared with final contours. In phase III, statistically significant differences in contouring time were observed based on physician, type of contouring, and case sequence again. The average relative timesaving for N points and autosegmentation were 49% and 27%, respectively, compared with manual contouring. The N points and autosegmentation strategies resulted in average Dice values of 0.89 and 0.88, respectively. Pre- and postedited autosegmented contours demonstrated a higher average Dice similarity coefficient of 0.94. Conclusion: The software provided robust contours with minimal editing required. Observed time savings were seen for all physicians irrespective of experience level and baseline manual contouring speed.« less

Data integrity systems for organ contours in radiation therapy planning.

PubMed

Shah, Veeraj P; Lakshminarayanan, Pranav; Moore, Joseph; Tran, Phuoc T; Quon, Harry; Deville, Curtiland; McNutt, Todd R

2018-06-12

The purpose of this research is to develop effective data integrity models for contoured anatomy in a radiotherapy workflow for both real-time and retrospective analysis. Within this study, two classes of contour integrity models were developed: data driven models and contiguousness models. The data driven models aim to highlight contours which deviate from a gross set of contours from similar disease sites and encompass the following regions of interest (ROI): bladder, femoral heads, spinal cord, and rectum. The contiguousness models, which individually analyze the geometry of contours to detect possible errors, are applied across many different ROI's and are divided into two metrics: Extent and Region Growing over volume. After analysis, we found that 70% of detected bladder contours were verified as suspicious. The spinal cord and rectum models verified that 73% and 80% of contours were suspicious respectively. The contiguousness models were the most accurate models and the Region Growing model was the most accurate submodel. 100% of the detected noncontiguous contours were verified as suspicious, but in the cases of spinal cord, femoral heads, bladder, and rectum, the Region Growing model detected additional two to five suspicious contours that the Extent model failed to detect. When conducting a blind review to detect false negatives, it was found that all the data driven models failed to detect all suspicious contours. The Region Growing contiguousness model produced zero false negatives in all regions of interest other than prostate. With regards to runtime, the contiguousness via extent model took an average of 0.2 s per contour. On the other hand, the region growing method had a longer runtime which was dependent on the number of voxels in the contour. Both contiguousness models have potential for real-time use in clinical radiotherapy while the data driven models are better suited for retrospective use. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Orthosis-Shaped Sandals Are as Efficacious as In-Shoe Orthoses and Better than Flat Sandals for Plantar Heel Pain: A Randomized Control Trial.

PubMed

Vicenzino, Bill; McPoil, Thomas G; Stephenson, Aoife; Paul, Sanjoy K

2015-01-01

To investigate efficacy of a contoured sandal being marketed for plantar heel pain with comparison to a flat flip-flop and contoured in-shoe insert/orthosis. 150 volunteers aged 50 (SD: 12) years with plantar heel pain (>4 weeks) were enrolled after responding to advertisements and eligibility determined by telephone and at first visit. Participants were randomly allocated to receive commercially available contoured sandals (n = 49), flat flip-flops (n = 50) or over the counter, pre-fabricated full-length foot orthotics (n = 51). Primary outcomes were a 15-point Global Rating of Change scale (GROC: 1 = a very great deal worse, 15 = a very great deal better), 13 to 15 representing an improvement and the 20-item Lower Extremity Function Scale (LEFS) on which participants rate 20 common weight bearing activities and activities of daily living on a 5-point scale (0 = extreme difficulty, 4 = no difficulty). Secondary outcomes were worst level of heel pain in the preceding week, and the foot and ankle ability measure. Outcomes were collected blind to allocation. Analyses were done on an intention to treat basis with 12 weeks being the primary outcome time of interest. The contoured sandal was 68% more likely to report improvement in terms of GROC compared to flat flip-flop. On the LEFS the contoured sandal was 61% more likely than flat flip-flop to report improvement. The secondary outcomes in the main reflected the primary outcomes, and there were no differences between contoured sandal and shoe insert. Physicians can have confidence in supporting a patient's decision to wear contoured sandals or in-shoe orthoses as one of the first and simple strategies to manage their heel pain. The Australian New Zealand Clinical Trials Registry ACTRN12612000463875.

Modified Inverse First Order Reliability Method (I-FORM) for Predicting Extreme Sea States.

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

Eckert-Gallup, Aubrey Celia; Sallaberry, Cedric Jean-Marie; Dallman, Ann Renee

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulation s as a part of the stand ard current practice for designing marine structure s to survive extreme sea states. Such environmental contours are characterized by combinations of significant wave height ( ) and energy period ( ) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first - order reliability method (IFORM) i s standard design practice for generating environmental contours.more » In this paper, the traditional appli cation of the IFORM to generating environmental contours representing extreme sea states is described in detail and its merits and drawbacks are assessed. The application of additional methods for analyzing sea state data including the use of principal component analysis (PCA) to create an uncorrelated representation of the data under consideration is proposed. A reexamination of the components of the IFORM application to the problem at hand including the use of new distribution fitting techniques are shown to contribute to the development of more accurate a nd reasonable representations of extreme sea states for use in survivability analysis for marine struc tures. Keywords: In verse FORM, Principal Component Analysis , Environmental Contours, Extreme Sea State Characteri zation, Wave Energy Converters« less

Rapid Contour-based Segmentation for 18F-FDG PET Imaging of Lung Tumors by Using ITK-SNAP: Comparison to Expert-based Segmentation.

PubMed

Besson, Florent L; Henry, Théophraste; Meyer, Céline; Chevance, Virgile; Roblot, Victoire; Blanchet, Elise; Arnould, Victor; Grimon, Gilles; Chekroun, Malika; Mabille, Laurence; Parent, Florence; Seferian, Andrei; Bulifon, Sophie; Montani, David; Humbert, Marc; Chaumet-Riffaud, Philippe; Lebon, Vincent; Durand, Emmanuel

2018-04-03

Purpose To assess the performance of the ITK-SNAP software for fluorodeoxyglucose (FDG) positron emission tomography (PET) segmentation of complex-shaped lung tumors compared with an optimized, expert-based manual reference standard. Materials and Methods Seventy-six FDG PET images of thoracic lesions were retrospectively segmented by using ITK-SNAP software. Each tumor was manually segmented by six raters to generate an optimized reference standard by using the simultaneous truth and performance level estimate algorithm. Four raters segmented 76 FDG PET images of lung tumors twice by using ITK-SNAP active contour algorithm. Accuracy of ITK-SNAP procedure was assessed by using Dice coefficient and Hausdorff metric. Interrater and intrarater reliability were estimated by using intraclass correlation coefficients of output volumes. Finally, the ITK-SNAP procedure was compared with currently recommended PET tumor delineation methods on the basis of thresholding at 41% volume of interest (VOI; VOI 41 ) and 50% VOI (VOI 50 ) of the tumor's maximal metabolism intensity. Results Accuracy estimates for the ITK-SNAP procedure indicated a Dice coefficient of 0.83 (95% confidence interval: 0.77, 0.89) and a Hausdorff distance of 12.6 mm (95% confidence interval: 9.82, 15.32). Interrater reliability was an intraclass correlation coefficient of 0.94 (95% confidence interval: 0.91, 0.96). The intrarater reliabilities were intraclass correlation coefficients above 0.97. Finally, VOI 41 and VOI 50 accuracy metrics were as follows: Dice coefficient, 0.48 (95% confidence interval: 0.44, 0.51) and 0.34 (95% confidence interval: 0.30, 0.38), respectively, and Hausdorff distance, 25.6 mm (95% confidence interval: 21.7, 31.4) and 31.3 mm (95% confidence interval: 26.8, 38.4), respectively. Conclusion ITK-SNAP is accurate and reliable for active-contour-based segmentation of heterogeneous thoracic PET tumors. ITK-SNAP surpassed the recommended PET methods compared with ground truth manual segmentation. © RSNA, 2018.

Impact of contour on aesthetic judgments and approach-avoidance decisions in architecture

PubMed Central

Vartanian, Oshin; Navarrete, Gorka; Chatterjee, Anjan; Fich, Lars Brorson; Leder, Helmut; Modroño, Cristián; Nadal, Marcos; Rostrup, Nicolai; Skov, Martin

2013-01-01

On average, we urban dwellers spend about 90% of our time indoors, and share the intuition that the physical features of the places we live and work in influence how we feel and act. However, there is surprisingly little research on how architecture impacts behavior, much less on how it influences brain function. To begin closing this gap, we conducted a functional magnetic resonance imaging study to examine how systematic variation in contour impacts aesthetic judgments and approach-avoidance decisions, outcome measures of interest to both architects and users of spaces alike. As predicted, participants were more likely to judge spaces as beautiful if they were curvilinear than rectilinear. Neuroanatomically, when contemplating beauty, curvilinear contour activated the anterior cingulate cortex exclusively, a region strongly responsive to the reward properties and emotional salience of objects. Complementing this finding, pleasantness—the valence dimension of the affect circumplex—accounted for nearly 60% of the variance in beauty ratings. Furthermore, activation in a distributed brain network known to underlie the aesthetic evaluation of different types of visual stimuli covaried with beauty ratings. In contrast, contour did not affect approach-avoidance decisions, although curvilinear spaces activated the visual cortex. The results suggest that the well-established effect of contour on aesthetic preference can be extended to architecture. Furthermore, the combination of our behavioral and neural evidence underscores the role of emotion in our preference for curvilinear objects in this domain. PMID:23754408

Expert consensus contouring guidelines for IMRT in esophageal and gastroesophageal junction cancer

PubMed Central

Wu, Abraham J.; Bosch, Walter R.; Chang, Daniel T.; Hong, Theodore S.; Jabbour, Salma K.; Kleinberg, Lawrence R.; Mamon, Harvey J.; Thomas, Charles R.; Goodman, Karyn A.

2015-01-01

Purpose/Objective(s) Current guidelines for esophageal cancer contouring are derived from traditional two-dimensional fields based on bony landmarks, and do not provide sufficient anatomical detail to ensure consistent contouring for more conformal radiotherapy techniques such as intensity-modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials Eight expert academically-based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform CT simulation datasets and an accompanying diagnostic PET-CT were distributed to each expert, and he/she was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results Kappa statistics indicated substantial agreement between panelists for each of the three test cases. A consensus CTV atlas was generated for the three test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets utilizing these guidelines may require modification in the future. PMID:26104943

Expert Consensus Contouring Guidelines for Intensity Modulated Radiation Therapy in Esophageal and Gastroesophageal Junction Cancer

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

Wu, Abraham J., E-mail: wua@mskcc.org; Bosch, Walter R.; Chang, Daniel T.

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophagealmore » cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future.« less

WE-AB-BRA-05: Fully Automatic Segmentation of Male Pelvic Organs On CT Without Manual Intervention

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

Gao, Y; Lian, J; Chen, R

Purpose: We aim to develop a fully automatic tool for accurate contouring of major male pelvic organs in CT images for radiotherapy without any manual initialization, yet still achieving superior performance than the existing tools. Methods: A learning-based 3D deformable shape model was developed for automatic contouring. Specifically, we utilized a recent machine learning method, random forest, to jointly learn both image regressor and classifier for each organ. In particular, the image regressor is trained to predict the 3D displacement from each vertex of the 3D shape model towards the organ boundary based on the local image appearance around themore » location of this vertex. The predicted 3D displacements are then used to drive the 3D shape model towards the target organ. Once the shape model is deformed close to the target organ, it is further refined by an organ likelihood map estimated by the learned classifier. As the organ likelihood map provides good guideline for the organ boundary, the precise contouring Result could be achieved, by deforming the 3D shape model locally to fit boundaries in the organ likelihood map. Results: We applied our method to 29 previously-treated prostate cancer patients, each with one planning CT scan. Compared with manually delineated pelvic organs, our method obtains overlap ratios of 85.2%±3.74% for the prostate, 94.9%±1.62% for the bladder, and 84.7%±1.97% for the rectum, respectively. Conclusion: This work demonstrated feasibility of a novel machine-learning based approach for accurate and automatic contouring of major male pelvic organs. It shows the potential to replace the time-consuming and inconsistent manual contouring in the clinic. Also, compared with the existing works, our method is more accurate and also efficient since it does not require any manual intervention, such as manual landmark placement. Moreover, our method obtained very similar contouring results as the clinical experts. Project is partially support by a grant from NCI 1R01CA140413.« less

Pelvic Normal Tissue Contouring Guidelines for Radiation Therapy: A Radiation Therapy Oncology Group Consensus Panel Atlas

PubMed Central

Gay, Hiram A.; Barthold, H. Joseph; O’Meara, Elizabeth; Bosch, Walter R.; El Naqa, Issam; Al-Lozi, Rawan; Rosenthal, Seth A.; Lawton, Colleen; Lee, W. Robert; Sandler, Howard; Zietman, Anthony; Myerson, Robert; Dawson, Laura A.; Willett, Christopher; Kachnic, Lisa A.; Jhingran, Anuja; Portelance, Lorraine; Ryu, Janice; Small, William; Gaffney, David; Viswanathan, Akila N.; Michalski, Jeff M.

2012-01-01

Purpose To define a male and female pelvic normal tissue contouring atlas for Radiation Therapy Oncology Group (RTOG) trials. Methods and Materials One male pelvis computed tomography (CT) data set and one female pelvis CT data set were shared via the Image-Guided Therapy QA Center. A total of 16 radiation oncologists participated. The following organs at risk were contoured in both CT sets: anus, anorectum, rectum (gastrointestinal and genitourinary definitions), bowel NOS (not otherwise specified), small bowel, large bowel, and proximal femurs. The following were contoured in the male set only: bladder, prostate, seminal vesicles, and penile bulb. The following were contoured in the female set only: uterus, cervix, and ovaries. A computer program used the binomial distribution to generate 95% group consensus contours. These contours and definitions were then reviewed by the group and modified. Results The panel achieved consensus definitions for pelvic normal tissue contouring in RTOG trials with these standardized names: Rectum, AnoRectum, SmallBowel, Colon, BowelBag, Bladder, UteroCervix, Adnexa_R, Adnexa_L, Prostate, SeminalVesc, PenileBulb, Femur_R, and Femur_L. Two additional normal structures whose purpose is to serve as targets in anal and rectal cancer were defined: AnoRectumSig and Mesorectum. Detailed target volume contouring guidelines and images are discussed. Conclusions Consensus guidelines for pelvic normal tissue contouring were reached and are available as a CT image atlas on the RTOG Web site. This will allow uniformity in defining normal tissues for clinical trials delivering pelvic radiation and will facilitate future normal tissue complication research. PMID:22483697

Speech Intonation and Melodic Contour Recognition in Children with Cochlear Implants and with Normal Hearing

PubMed Central

See, Rachel L.; Driscoll, Virginia D.; Gfeller, Kate; Kliethermes, Stephanie; Oleson, Jacob

2013-01-01

Background Cochlear implant (CI) users have difficulty perceiving some intonation cues in speech and melodic contours because of poor frequency selectivity in the cochlear implant signal. Objectives To assess perceptual accuracy of normal hearing (NH) children and pediatric CI users on speech intonation (prosody), melodic contour, and pitch ranking, and to determine potential predictors of outcomes. Hypothesis Does perceptual accuracy for speech intonation or melodic contour differ as a function of auditory status (NH, CI), perceptual category (falling vs. rising intonation/contour), pitch perception, or individual differences (e.g., age, hearing history)? Method NH and CI groups were tested on recognition of falling intonation/contour vs. rising intonation/contour presented in both spoken and melodic (sung) conditions. Pitch ranking was also tested. Outcomes were correlated with variables of age, hearing history, HINT, and CNC scores. Results The CI group was significantly less accurate than the NH group in spoken (CI, M=63.1 %; NH, M=82.1%) and melodic (CI, M=61.6%; NH, M=84.2%) conditions. The CI group was more accurate in recognizing rising contour in the melodic condition compared with rising intonation in the spoken condition. Pitch ranking was a significant predictor of outcome for both groups in falling intonation and rising melodic contour; age at testing and hearing history variables were not predictive of outcomes. Conclusions Children with CIs were less accurate than NH children in perception of speech intonation, melodic contour, and pitch ranking. However, the larger pitch excursions of the melodic condition may assist in recognition of the rising inflection associated with the interrogative form. PMID:23442568

Collinear facilitation and contour integration in autism: evidence for atypical visual integration.

PubMed

Jachim, Stephen; Warren, Paul A; McLoughlin, Niall; Gowen, Emma

2015-01-01

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction, atypical communication and a restricted repertoire of interests and activities. Altered sensory and perceptual experiences are also common, and a notable perceptual difference between individuals with ASD and controls is their superior performance in visual tasks where it may be beneficial to ignore global context. This superiority may be the result of atypical integrative processing. To explore this claim we investigated visual integration in adults with ASD (diagnosed with Asperger's Syndrome) using two psychophysical tasks thought to rely on integrative processing-collinear facilitation and contour integration. We measured collinear facilitation at different flanker orientation offsets and contour integration for both open and closed contours. Our results indicate that compared to matched controls, ASD participants show (i) reduced collinear facilitation, despite equivalent performance without flankers; and (ii) less benefit from closed contours in contour integration. These results indicate weaker visuospatial integration in adults with ASD and suggest that further studies using these types of paradigms would provide knowledge on how contextual processing is altered in ASD.

2D segmentation of intervertebral discs and its degree of degeneration from T2-weighted magnetic resonance images

NASA Astrophysics Data System (ADS)

Castro-Mateos, Isaac; Pozo, José Maria; Lazary, Aron; Frangi, Alejandro F.

2014-03-01

Low back pain (LBP) is a disorder suffered by a large population around the world. A key factor causing this illness is Intervertebral Disc (IVD) degeneration, whose early diagnosis could help in preventing this widespread condition. Clinicians base their diagnosis on visual inspection of 2D slices of Magnetic Resonance (MR) images, which is subject to large interobserver variability. In this work, an automatic classification method is presented, which provides the Pfirrmann degree of degeneration from a mid-sagittal MR slice. The proposed method utilizes Active Contour Models, with a new geometrical energy, to achieve an initial segmentation, which is further improved using fuzzy C-means. Then, IVDs are classified according to their degree of degeneration. This classification is attained by employing Adaboost on five specific features: the mean and the variance of the probability map of the nucleus using two different approaches and the eccentricity of the fitting ellipse to the contour of the IVD. The classification method was evaluated using a cohort of 150 intervertebral discs assessed by three experts, resulting in a mean specificity (93%) and sensitivity (83%) similar to the one provided by every expert with respect to the most voted value. The segmentation accuracy was evaluated using the Dice Similarity Index (DSI) and Root Mean Square Error (RMSE) of the point-to-contour distance. The mean DSI ± 2 standard deviation was 91:7% ±5:6%, the mean RMSE was 0:82mm and the 95 percentile was 1:36mm. These results were found accurate when compared to the state-of-the-art.

A contour for the entanglement entropies in harmonic lattices

NASA Astrophysics Data System (ADS)

Coser, Andrea; De Nobili, Cristiano; Tonni, Erik

2017-08-01

We construct a contour function for the entanglement entropies in generic harmonic lattices. In one spatial dimension, numerical analysis are performed by considering harmonic chains with either periodic or Dirichlet boundary conditions. In the massless regime and for some configurations where the subsystem is a single interval, the numerical results for the contour function are compared to the inverse of the local weight function which multiplies the energy-momentum tensor in the corresponding entanglement hamiltonian, found through conformal field theory methods, and a good agreement is observed. A numerical analysis of the contour function for the entanglement entropy is performed also in a massless harmonic chain for a subsystem made by two disjoint intervals.

3D Actin Network Centerline Extraction with Multiple Active Contours

PubMed Central

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2013-01-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

SU-E-J-108: Solving the Chinese Postman Problem for Effective Contour Deformation

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

Yang, J; Zhang, L; Balter, P

2015-06-15

Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points.more » It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes no matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and research applications. This work was partially supported by Cancer Prevention & Research Institute of Texas (CPRIT) RP110562.« less

In Vivo Precision of Digital Topological Skeletonization Based Individual Trabecula Segmentation (ITS) Analysis of Trabecular Microstructure at the Distal Radius and Tibia by HR-pQCT.

PubMed

Zhou, Bin; Zhang, Zhendong; Wang, Ji; Yu, Y Eric; Liu, Xiaowei Sherry; Nishiyama, Kyle K; Rubin, Mishaela R; Shane, Elizabeth; Bilezikian, John P; Guo, X Edward

2016-06-01

Trabecular plate and rod microstructure plays a dominant role in the apparent mechanical properties of trabecular bone. With high-resolution computed tomography (CT) images, digital topological analysis (DTA) including skeletonization and topological classification was applied to transform the trabecular three-dimensional (3D) network into surface and curve skeletons. Using the DTA-based topological analysis and a new reconstruction/recovery scheme, individual trabecula segmentation (ITS) was developed to segment individual trabecular plates and rods and quantify the trabecular plate- and rod-related morphological parameters. High-resolution peripheral quantitative computed tomography (HR-pQCT) is an emerging in vivo imaging technique to visualize 3D bone microstructure. Based on HR-pQCT images, ITS was applied to various HR-pQCT datasets to examine trabecular plate- and rod-related microstructure and has demonstrated great potential in cross-sectional and longitudinal clinical applications. However, the reproducibility of ITS has not been fully determined. The aim of the current study is to quantify the precision errors of ITS plate-rod microstructural parameters. In addition, we utilized three different frequently used contour techniques to separate trabecular and cortical bone and to evaluate their effect on ITS measurements. Overall, good reproducibility was found for the standard HR-pQCT parameters with precision errors for volumetric BMD and bone size between 0.2%-2.0%, and trabecular bone microstructure between 4.9%-6.7% at the radius and tibia. High reproducibility was also achieved for ITS measurements using all three different contour techniques. For example, using automatic contour technology, low precision errors were found for plate and rod trabecular number (pTb.N, rTb.N, 0.9% and 3.6%), plate and rod trabecular thickness (pTb.Th, rTb.Th, 0.6% and 1.7%), plate trabecular surface (pTb.S, 3.4%), rod trabecular length (rTb.ℓ, 0.8%), and plate-plate junction density (P-P Junc.D, 2.3%) at the tibia. The precision errors at the radius were similar to those at the tibia. In addition, precision errors were affected by the contour technique. At the tibia, precision error by the manual contour method was significantly different from automatic and standard contour methods for pTb.N, rTb.N and rTb.Th. Precision error using the manual contour method was also significantly different from the standard contour method for rod trabecular number (rTb.N), rod trabecular thickness (rTb.Th), rod-rod and plate-rod junction densities (R-R Junc.D and P-R Junc.D) at the tibia. At the radius, the precision error was similar between the three different contour methods. Image quality was also found to significantly affect the ITS reproducibility. We concluded that ITS parameters are highly reproducible, giving assurance that future cross-sectional and longitudinal clinical HR-pQCT studies are feasible in the context of limited sample sizes.

Determination of Multiple Near-Surface Residual Stress Components in Laser Peened Aluminum Alloy via the Contour Method

NASA Astrophysics Data System (ADS)

Toparli, M. Burak; Fitzpatrick, Michael E.; Gungor, Salih

2015-09-01

In this study, residual stress fields, including the near-surface residual stresses, were determined for an Al7050-T7451 sample after laser peening. The contour method was applied to measure one component of the residual stress, and the relaxed stresses on the cut surfaces were then measured by X-ray diffraction. This allowed calculation of the three orthogonal stress components using the superposition principle. The near-surface results were validated with results from incremental hole drilling and conventional X-ray diffraction. The results demonstrate that multiple residual stress components can be determined using a combination of the contour method and another technique. If the measured stress components are congruent with the principal stress axes in the sample, then this allows for determination of the complete stress tensor.

Photomask quality evaluation using lithography simulation and precision SEM image contour data

NASA Astrophysics Data System (ADS)

Murakawa, Tsutomu; Fukuda, Naoki; Shida, Soichi; Iwai, Toshimichi; Matsumoto, Jun; Nakamura, Takayuki; Hagiwara, Kazuyuki; Matsushita, Shohei; Hara, Daisuke; Adamov, Anthony

2012-11-01

To evaluate photomask quality, the current method uses spatial imaging by optical inspection tools. This technique at 1Xnm node has a resolution limit because small defects will be difficult to extract. To simulate the mask error-enhancement factor (MEEF) influence for aggressive OPC in 1Xnm node, wide FOV contour data and tone information are derived from high precision SEM images. For this purpose we have developed a new contour data extraction algorithm with sub-nanometer accuracy resulting in a wide Field of View (FOV) SEM image: (for example, more than 10um x 10um square). We evaluated MEEF influence of high-end photomask pattern using the wide FOV contour data of "E3630 MVM-SEMTM" and lithography simulator "TrueMaskTM DS" of D2S, Inc. As a result, we can detect the "invisible defect" as the MEEF influence using the wide FOV contour data and lithography simulator.

New method of contour image processing based on the formalism of spiral light beams

NASA Astrophysics Data System (ADS)

Volostnikov, Vladimir G.; Kishkin, S. A.; Kotova, S. P.

2013-07-01

The possibility of applying the mathematical formalism of spiral light beams to the problems of contour image recognition is theoretically studied. The advantages and disadvantages of the proposed approach are evaluated; the results of numerical modelling are presented.

SU-E-J-111: Finite Element-Based Deformable Image Registration of Pleural Cavity for Photodynamic Therapy

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

Penjweini, R; Zhu, T

Purpose: The pleural volumes will deform during surgery portion of the pleural photodynamic therapy (PDT) of lung cancer when the pleural cavity is opened. This impact the delivered dose when using highly conformal treatment techniques. In this study, a finite element-based (FEM) deformable image registration is used to quantify the anatomical variation between the contours for the pleural cavities obtained in the operating room and those determined from pre-surgery computed tomography (CT) scans. Methods: An infrared camera-based navigation system (NDI) is used during PDT to track the anatomical changes and contour the lung and chest cavity. A series of CTsmore » of the lungs, in the same patient, are also acquired before the surgery. The structure contour of lung and the CTs are processed and contoured in Matlab and MeshLab. Then, the contours are imported into COMSOL Multiphysics 5.0, where the FEM-based deformable image registration is obtained using the deformed mesh - moving mesh (ALE) model. The NDI acquired lung contour is considered as the reference contour, and the CT contour is used as the target one, which will be deformed. Results: The reconstructed three-dimensional contours from both NDI and CT can be converted to COMSOL so that a three-dimensional ALE model can be developed. The contours can be registered using COMSOL ALE moving mesh model, which takes into account the deformation along x, y and z-axes. The deformed contour has good matches to the reference contour after the dynamic matching process. The resulting 3D deformation map can be used to obtain the locations of other critical anatomic structures, e.g., heart, during surgery. Conclusion: Deformable image registration can fuse images acquired by different modalities. It provides insights into the development of phenomenon and variation in normal anatomical structures over time. The initial assessments of three-dimensional registration show good agreement.« less

Method and apparatus for measuring surface contour on parts with elevated temperatures

DOEpatents

Horvath, Mark S.; Nance, Roy A.; Cohen, George H.; Fodor, George

1991-01-01

The invention is directed to a method and apparatus for measuring the surface contour of a test piece, such as the bow of a radioactive fuel rod, which is completely immersed in water. The invention utilizes ultrasonic technology and is capable of measuring surface contours of test pieces which are at a higher temperature than the surrounding water. The presence of a test piece at a higher temperature adversely affects the distance measurements by causing thermal variations in the water near the surface of the test piece. The contour measurements depend upon a constant temperature of the water in the path of the ultrasonic wave to provide a constant acoustical velocity (the measurement is made by the time of flight measurement for an ultrasonic wave). Therefore, any variations of water temperature near the surface will introduce errors degrading the measurement. The present invention overcomes these problems by assuring that the supply of water through which the ultrasonic waves travel is at a predetermined and constant temperature.

Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

PubMed Central

2012-01-01

Background While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. Results We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. Conclusions We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work. PMID:22321695

Fast incorporation of optical flow into active polygons.

PubMed

Unal, Gozde; Krim, Hamid; Yezzi, Anthony

2005-06-01

In this paper, we first reconsider, in a different light, the addition of a prediction step to active contour-based visual tracking using an optical flow and clarify the local computation of the latter along the boundaries of continuous active contours with appropriate regularizers. We subsequently detail our contribution of computing an optical flow-based prediction step directly from the parameters of an active polygon, and of exploiting it in object tracking. This is in contrast to an explicitly separate computation of the optical flow and its ad hoc application. It also provides an inherent regularization effect resulting from integrating measurements along polygon edges. As a result, we completely avoid the need of adding ad hoc regularizing terms to the optical flow computations, and the inevitably arbitrary associated weighting parameters. This direct integration of optical flow into the active polygon framework distinguishes this technique from most previous contour-based approaches, where regularization terms are theoretically, as well as practically, essential. The greater robustness and speed due to a reduced number of parameters of this technique are additional and appealing features.

Wax Reinforces Honeycomb During Machining

NASA Technical Reports Server (NTRS)

Towell, Timothy W.; Fahringer, David T.; Vasquez, Peter; Scheidegger, Alan P.

1995-01-01

Method of machining on conventional metal lathe devised for precise cutting of axisymmetric contours on honeycomb cores made of composite (matrix/fiber) materials. Wax filling reinforces honeycomb walls against bending and tearing while honeycomb being contoured on lathe. Innovative method of machining on lathe involves preparation in which honeycomb is placed in appropriate fixture and the fixture is then filled with molten water-soluble wax. Number of different commercial waxes have been tried.

Pedestrian Validation in Infrared Images by Means of Active Contours and Neural Networks

DTIC Science & Technology

2010-01-01

Research Article Pedestrian Validation in Infrared Images byMeans of Active Contours and Neural Networks Massimo Bertozzi,1 Pietro Cerri,1 Mirko Felisa,1...Stefano Ghidoni,2 andMichael Del Rose3 1VisLab, Dipartimento di Ingegneria dell’Informazione, Università di Parma, 43124 Parma, Italy 2 IAS-Lab...Dipartimento di Ingegneria dell’Informazione, Università di Padova, 35131 Padova, Italy 3Vetronics Research Center, U. S. Army TARDEC, MI 48397, USA

[Medical image segmentation based on the minimum variation snake model].

PubMed

Zhou, Changxiong; Yu, Shenglin

2007-02-01

It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

SU-F-19A-09: Propagation of Organ at Risk Contours for High Dose Rate Brachytherapy Planning for Cervical Cancer: A Deformable Image Registration Comparison

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

Bellon, M; Kumarasiri, A; Kim, J

Purpose: To compare the performance of two deformable image registration (DIR) algorithms for contour propagation and to evaluate the accuracy of DIR for use with high dose rate (HDR) brachytherapy planning for cervical cancer. Methods: Five patients undergoing HDR ring and tandem brachytherapy were included in this retrospective study. All patients underwent CT simulation and replanning prior to each fraction (3–5 fractions total). CT-to-CT DIR was performed using two commercially available software platforms: SmartAdapt, Varian Medical Systems (Demons) and Velocity AI, Velocity Medical Solutions (B-spline). Fraction 1 contours were deformed and propagated to each subsequent image set and compared tomore » contours manually drawn by an expert clinician. Dice similarity coefficients (DSC), defined as, DSC(A,B)=2(AandB)/(A+B) were calculated to quantify spatial overlap between manual (A) and deformed (B) contours. Additionally, clinician-assigned visual scores were used to describe and compare the performance of each DIR method and ultimately evaluate which was more clinically acceptable. Scoring was based on a 1–5 scale—with 1 meaning, “clinically acceptable with no contour changes” and 5 meaning, “clinically unacceptable”. Results: Statistically significant differences were not observed between the two DIR algorithms. The average DSC for the bladder, rectum and rectosigmoid were 0.82±0.08, 0.67±0.13 and 0.48±0.18, respectively. The poorest contour agreement was observed for the rectosigmoid due to limited soft tissue contrast and drastic anatomical changes, i.e., organ shape/filling. Two clinicians gave nearly equivalent average scores of 2.75±0.91 for SmartAdapt and 2.75±0.94 for Velocity AI—indicating that for a majority of the cases, more than one of the three contours evaluated required major modifications. Conclusion: Limitations of both DIR algorithms resulted in inaccuracies in contour propagation in the pelvic region, thus hampering the clinical utility of this technology. Further work is required to optimize these algorithms and take advantage of the potential of DIR for HDR brachytherapy planning.« less

SU-E-J-103: Propagation of Rectum and Bladder Contours for Tandem and Ring (T&R) HDR Treatment Using Deformable Image Registration

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

Yuan, Y; Chao, M; Sheu, R

2015-06-15

Purpose: To investigate the feasibility of using DIR to propagate the manually contoured rectum and bladder from the 1st insertion to the new CT images on subsequent insertions and evaluate the segmentation performance. Methods: Ten cervical cancer patients, who were treated by T&R brachytherapy in 3–4 insertions, were retrospectively collected. In each insertion, rectum and bladder were manually delineated on the planning CT by a physicist and verified by a radiation oncologist. Using VelocityAI (Velocity Medical Solutions, Atlanta, GA), a rigid registration was firstly employed to match the bony structures between the first insertion and each of the following insertions,more » then a multi-pass B-spine DIR was carried out to further map the sub volume that encompasses rectum and bladder. The resultant deformation fields propagated contours, and dice similarity coefficient (DSC) was used to quantitatively evaluate the agreement between the propagated contours and the manually-delineated organs. For the 3rd insertion, we also evaluated if the segmentation performance could be improved by propagating the contours from the most recent insertion, i.e., the 2nd insertion. Results: On average, the contour propagation took about 1 minute. The average and standard deviation of DSC over all insertions and patients was 0.67±0.10 (range: 0.44–0.81) for rectum, and 0.78±0.07 (range: 0.63–0.87) for bladder. For the 3rd insertion, propagating contours from the 2nd insertion could improve the segmentation performance in terms of DSC from 0.63±0.10 to 0.72±0.08 for rectum, and from 0.77±0.07 to 0.79±0.06 for bladder. A Wilcoxon signed rank test indicated that the improvement was statistically significant for rectum (p = 0.004). Conclusion: The preliminary results demonstrate that deformable image registration could efficiently and accurately propagate rectum and bladder contours between CT images in different T&R brachytherapy fractions. We are incorporating the propagated contours into our learning-based method to further segment these organs.« less

SU-F-J-81: Evaluation of Automated Deformable Registration Between Planning Computed Tomography (CT) and Daily Cone Beam CT Images Over the Course of Prostate Cancer Radiotherapy

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

Matney, J; Hammers, J; Kaidar-Person, O

2016-06-15

Purpose: To compute daily dose delivered during radiotherapy, deformable registration needs to be relatively fast, automated, and accurate. The aim of this study was to evaluate the performance of commercial deformable registration software for deforming between two modalities: planning computed tomography (pCT) images acquired for treatment planning and cone beam (CB) CT images acquired prior to each fraction of prostate cancer radiotherapy. Methods: A workflow was designed using MIM Software™ that aligned and deformed pCT into daily CBCT images in two steps: (1) rigid shifts applied after daily CBCT imaging to align patient anatomy to the pCT and (2) normalizedmore » intensity-based deformable registration to account for interfractional anatomical variations. The physician-approved CTV and organ and risk (OAR) contours were deformed from the pCT to daily CBCT over the course of treatment. The same structures were delineated on each daily CBCT by a radiation oncologist. Dice similarity coefficient (DSC) mean and standard deviations were calculated to quantify the deformable registration quality for prostate, bladder, rectum and femoral heads. Results: To date, contour comparisons have been analyzed for 31 daily fractions of 2 of 10 of the cohort. Interim analysis shows that right and left femoral head contours demonstrate the highest agreement (DSC: 0.96±0.02) with physician contours. Additionally, deformed bladder (DSC: 0.81±0.09) and prostate (DSC: 0.80±0.07) have good agreement with physician-defined daily contours. Rectum contours have the highest variations (DSC: 0.66±0.10) between the deformed and physician-defined contours on daily CBCT imaging. Conclusion: For structures with relatively high contrast boundaries on CBCT, the MIM automated deformable registration provided accurate representations of the daily contours during treatment delivery. These findings will permit subsequent investigations to automate daily dose computation from CBCT. However, improved methods need to be investigated to improve deformable results for rectum contours.« less

Novel Digital Driving Method Using Dual Scan for Active Matrix Organic Light-Emitting Diode Displays

NASA Astrophysics Data System (ADS)

Jung, Myoung Hoon; Choi, Inho; Chung, Hoon-Ju; Kim, Ohyun

2008-11-01

A new digital driving method has been developed for low-temperature polycrystalline silicon, transistor-driven, active-matrix organic light-emitting diode (AM-OLED) displays by time-ratio gray-scale expression. This driving method effectively increases the emission ratio and the number of subfields by inserting another subfield set into nondisplay periods in the conventional digital driving method. By employing the proposed modified gravity center coding, this method can be used to effectively compensate for dynamic false contour noise. The operation and performance were verified by current measurement and image simulation. The simulation results using eight test images show that the proposed approach improves the average peak signal-to-noise ratio by 2.61 dB, and the emission ratio by 20.5%, compared with the conventional digital driving method.

Visual Tracking Using 3D Data and Region-Based Active Contours

DTIC Science & Technology

2016-09-28

adaptive control strategies which explicitly take uncertainty into account. Filtering methods ranging from the classical Kalman filters valid for...linear systems to the much more general particle filters also fit into this framework in a very natural manner. In particular, the particle filtering ...the number of samples required for accurate filtering increases with the dimension of the system noise. In our approach, we approximate curve

SU-E-J-131: Augmenting Atlas-Based Segmentation by Incorporating Image Features Proximal to the Atlas Contours

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

Li, Dengwang; Liu, Li; Kapp, Daniel S.

2015-06-15

Purpose: For facilitating the current automatic segmentation, in this work we propose a narrow-shell strategy to enhance the information of each contour in the library and to improve the accuracy of the exiting atlas-based approach. Methods: In setting up an atlas-based library, we include not only the coordinates of contour points, but also the image features adjacent to the contour. 139 planning CT scans with normal appearing livers obtained during their radiotherapy treatment planning were used to construct the library. The CT images within the library were registered each other using affine registration. A nonlinear narrow shell with the regionalmore » thickness determined by the distance between two vertices alongside the contour. The narrow shell was automatically constructed both inside and outside of the liver contours. The common image features within narrow shell between a new case and a library case were first selected by a Speed-up Robust Features (SURF) strategy. A deformable registration was then performed using a thin plate splines (TPS) technique. The contour associated with the library case was propagated automatically onto the images of the new patient by exploiting the deformation field vectors. The liver contour was finally obtained by employing level set based energy function within the narrow shell. The performance of the proposed method was evaluated by comparing quantitatively the auto-segmentation results with that delineated by a physician. Results: Application of the technique to 30 liver cases suggested that the technique was capable of reliably segment organs such as the liver with little human intervention. Compared with the manual segmentation results by a physician, the average and discrepancies of the volumetric overlap percentage (VOP) was found to be 92.43%+2.14%. Conclusion: Incorporation of image features into the library contours improves the currently available atlas-based auto-contouring techniques and provides a clinically practical solution for auto-segmentation. This work is supported by NIH/NIBIB (1R01-EB016777), National Natural Science Foundation of China (No.61471226 and No.61201441), Research funding from Shandong Province (No.BS2012DX038 and No.J12LN23), and Research funding from Jinan City (No.201401221 and No.20120109)« less

CT Urography: Segmentation of Urinary Bladder using CLASS with Local Contour Refinement

PubMed Central

Cha, Kenny; Hadjiiski, Lubomir; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Zhou, Chuan

2016-01-01

Purpose We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer. Methods The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy. Results For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2±11.4%, 8.2±17.4%, 13.0±14.1%, 3.5±1.9 mm, 78.8±11.6%, respectively, for the training set and 78.0±14.7%, 16.4±16.9%, 18.2±15.0%, 3.8±2.3 mm, 73.8±13.4% respectively, for the test set. With CLASS only, the corresponding values were 75.1±13.2%, 18.7±19.5%, 22.5±14.9%, 4.3±2.2 mm, 71.0±12.6%, respectively, for the training set and 67.3±14.3%, 29.3±15.9%, 29.4±15.6%, 4.9±2.6 mm, 65.0±13.3%, respectively, for the test set. The differences between the two methods for all five measures were statistically significant (p<0.001) for both the training and test sets. Conclusions The results demonstrate the potential of CLASS with LCR for segmentation of the bladder. PMID:24801066

Automatic Delineation of the Myocardial Wall from CT Images via Shape Segmentation and Variational Region Growing

PubMed Central

Zhu, Liangjia; Gao, Yi; Appia, Vikram; Yezzi, Anthony; Arepalli, Chesnal; Faber, Tracy; Stillman, Arthur; Tannenbaum, Allen

2014-01-01

Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this work, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images. PMID:23744658

Myocardial Iron Loading Assessment by Automatic Left Ventricle Segmentation with Morphological Operations and Geodesic Active Contour on T2* images

NASA Astrophysics Data System (ADS)

Luo, Yun-Gang; Ko, Jacky Kl; Shi, Lin; Guan, Yuefeng; Li, Linong; Qin, Jing; Heng, Pheng-Ann; Chu, Winnie Cw; Wang, Defeng

2015-07-01

Myocardial iron loading thalassemia patients could be identified using T2* magnetic resonance images (MRI). To quantitatively assess cardiac iron loading, we proposed an effective algorithm to segment aligned free induction decay sequential myocardium images based on morphological operations and geodesic active contour (GAC). Nine patients with thalassemia major were recruited (10 male and 16 female) to undergo a thoracic MRI scan in the short axis view. Free induction decay images were registered for T2* mapping. The GAC were utilized to segment aligned MR images with a robust initialization. Segmented myocardium regions were divided into sectors for a region-based quantification of cardiac iron loading. Our proposed automatic segmentation approach achieve a true positive rate at 84.6% and false positive rate at 53.8%. The area difference between manual and automatic segmentation was 25.5% after 1000 iterations. Results from T2* analysis indicated that regions with intensity lower than 20 ms were suffered from heavy iron loading in thalassemia major patients. The proposed method benefited from abundant edge information of the free induction decay sequential MRI. Experiment results demonstrated that the proposed method is feasible in myocardium segmentation and was clinically applicable to measure myocardium iron loading.

Development and evaluation of a new contoured cushion system with an optimized normalization algorithm.

PubMed

Li, Sujiao; Zhang, Zhengxiang; Wang, Jue

2014-01-01

Prevention of pressure sores remains a significant problem confronting spinal cord injury patients and the elderly with limited mobility. One vital aspect of this subject concerns the development of cushions to decrease pressure ulcers for seated patients, particularly those bound by wheelchairs. Here, we present a novel cushion system that employs interface pressure distribution between the cushion and the buttocks to design custom contoured foam cushion. An optimized normalization algorithm was proposed, with which interface pressure distribution was transformed into the carving depth of foam cushions according to the biomechanical characteristics of the foam. The shape and pressure-relief performance of the custom contoured foam cushions was investigated. The outcomes showed that the contoured shape of personalized cushion matched the buttock contour very well. Moreover, the custom contoured cushion could alleviate pressure under buttocks and increase subjective comfort and stability significantly. Furthermore, the fabricating method not only decreased the unit production cost but also simplified the procedure for manufacturing. All in all, this prototype seat cushion would be an effective and economical way to prevent pressure ulcers.

In-situ determination of residual specific activity in activated concrete walls of a PET-cyclotron room

NASA Astrophysics Data System (ADS)

Matsumura, H.; Toyoda, A.; Masumoto, K.; Yoshida, G.; Yagishita, T.; Nakabayashi, T.; Sasaki, H.; Matsumura, K.; Yamaya, Y.; Miyazaki, Y.

2018-06-01

In the decommissioning work for concrete walls of PET-cyclotron rooms, an in-situ measurement is expected to be useful for obtaining a contour map of the specific activity on the walls without destroying the structure. In this study, specific activities of γ-ray-emitting radionuclides in concrete walls were determined by using an in-situ measurement method employing a portable Ge semiconductor detector, and compared with the specific activity obtained using the sampling measurement method, at the Medical and Pharmacological Research Center Foundation in Hakui, Ishikawa, Japan. Accordingly, the specific activity could be determined by the in-situ determination method. Since there is a clear correlation between the total specific activity of γ-ray-emitting radionuclides and contact dose rate, the specific activity can be determined approximately by contact dose-rate measurement using a NaI scintillation survey meter. The specific activity of each γ-ray-emitting radionuclide can also be estimated from the contact dose rate using a NaI scintillation survey meter. The in-situ measurement method is a powerful tool for the decommissioning of the PET cyclotron room.

Optimum aim point biasing in case of a planetary quarantine constraint.

NASA Technical Reports Server (NTRS)

Gedeon, G. S.; Dvornychenko, V. N.

1972-01-01

It is assumed that the probability of impact for each maneuver is the same, and that the aspects of orbit determination and execution errors of each maneuver affect only the targeting. An approximation of the equal probability of impact contour is derived. It is assumed that the quarantine constraint is satisfied if the aim point is not inside the impact contour. A method is devised to find on each contour the optimum aim point which minimizes the so-called bias velocity which is required to bring back the spacecraft from the biased aim point to the originally desired aim point. The method is an improvement over the approach presented by Light (1965), and Craven and Wolfson (1967).

Focusators for laser-branding

NASA Astrophysics Data System (ADS)

Doskolovich, L. L.; Kazanskiy, N. L.; Kharitonov, S. I.; Uspleniev, G. V.

A new method is investigated for synthesis of computer-generated optical elements: focusators that are able to focus the radial-symmetrical laser beam into complex focal contours, in particular into alphanumeric symbols. The method is based on decomposition of the focal contour into segments of straight lines and semi-circles, following corresponding spacing out of the focusator on elementary segments (concentric rings or sectors) and solution of the inverse task of focusing from focusator segments into corresponding elements of the focal contour. The results of numerical computing of the field from synthesized focusators into the letters are presented. The theoretical efficiency of the focusators discussed is no less than 85%. The amplitude masks and the results of operational studies of synthesized focusators are presented.

Pelvic Normal Tissue Contouring Guidelines for Radiation Therapy: A Radiation Therapy Oncology Group Consensus Panel Atlas

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

Gay, Hiram A., E-mail: hgay@radonc.wustl.edu; Barthold, H. Joseph; Beth Israel Deaconess Medical Center, Boston, MA

2012-07-01

Purpose: To define a male and female pelvic normal tissue contouring atlas for Radiation Therapy Oncology Group (RTOG) trials. Methods and Materials: One male pelvis computed tomography (CT) data set and one female pelvis CT data set were shared via the Image-Guided Therapy QA Center. A total of 16 radiation oncologists participated. The following organs at risk were contoured in both CT sets: anus, anorectum, rectum (gastrointestinal and genitourinary definitions), bowel NOS (not otherwise specified), small bowel, large bowel, and proximal femurs. The following were contoured in the male set only: bladder, prostate, seminal vesicles, and penile bulb. The followingmore » were contoured in the female set only: uterus, cervix, and ovaries. A computer program used the binomial distribution to generate 95% group consensus contours. These contours and definitions were then reviewed by the group and modified. Results: The panel achieved consensus definitions for pelvic normal tissue contouring in RTOG trials with these standardized names: Rectum, AnoRectum, SmallBowel, Colon, BowelBag, Bladder, UteroCervix, Adnexa{sub R}, Adnexa{sub L}, Prostate, SeminalVesc, PenileBulb, Femur{sub R}, and Femur{sub L}. Two additional normal structures whose purpose is to serve as targets in anal and rectal cancer were defined: AnoRectumSig and Mesorectum. Detailed target volume contouring guidelines and images are discussed. Conclusions: Consensus guidelines for pelvic normal tissue contouring were reached and are available as a CT image atlas on the RTOG Web site. This will allow uniformity in defining normal tissues for clinical trials delivering pelvic radiation and will facilitate future normal tissue complication research.« less

Atlas-Based Segmentation Improves Consistency and Decreases Time Required for Contouring Postoperative Endometrial Cancer Nodal Volumes

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

Young, Amy V.; Department of Radiation Oncology, St. Luke's-Roosevelt Hospital, New York, NY; Wortham, Angela

2011-03-01

Purpose: Accurate target delineation of the nodal volumes is essential for three-dimensional conformal and intensity-modulated radiotherapy planning for endometrial cancer adjuvant therapy. We hypothesized that atlas-based segmentation ('autocontouring') would lead to time savings and more consistent contours among physicians. Methods and Materials: A reference anatomy atlas was constructed using the data from 15 postoperative endometrial cancer patients by contouring the pelvic nodal clinical target volume on the simulation computed tomography scan according to the Radiation Therapy Oncology Group 0418 trial using commercially available software. On the simulation computed tomography scans from 10 additional endometrial cancer patients, the nodal clinical targetmore » volume autocontours were generated. Three radiation oncologists corrected the autocontours and delineated the manual nodal contours under timed conditions while unaware of the other contours. The time difference was determined, and the overlap of the contours was calculated using Dice's coefficient. Results: For all physicians, manual contouring of the pelvic nodal target volumes and editing the autocontours required a mean {+-} standard deviation of 32 {+-} 9 vs. 23 {+-} 7 minutes, respectively (p = .000001), a 26% time savings. For each physician, the time required to delineate the manual contours vs. correcting the autocontours was 30 {+-} 3 vs. 21 {+-} 5 min (p = .003), 39 {+-} 12 vs. 30 {+-} 5 min (p = .055), and 29 {+-} 5 vs. 20 {+-} 5 min (p = .0002). The mean overlap increased from manual contouring (0.77) to correcting the autocontours (0.79; p = .038). Conclusion: The results of our study have shown that autocontouring leads to increased consistency and time savings when contouring the nodal target volumes for adjuvant treatment of endometrial cancer, although the autocontours still required careful editing to ensure that the lymph nodes at risk of recurrence are properly included in the target volume.« less

Comfort and pressure distribution in a human contour shaped aircraft seat (developed with 3D scans of the human body).

PubMed

Smulders, M; Berghman, K; Koenraads, M; Kane, J A; Krishna, K; Carter, T K; Schultheis, U

2016-08-12

The concept of comfort is one way for the growing airline market to differentiate and build customer loyalty. This work follows the idea that increasing the contact area between human and seat can have a positive effect on comfort [5, 6, 7]. To improve comfort, reduce weight and optimise space used, a human contour shaped seat shell and cushioning was developed. First the most common activities, the corresponding postures and seat inclination angles were defined. The imprints of these postures on a rescue mat were 3D scanned and an average human contour curve was defined. The outcome was transferred to a prototype seat that was used to test the effect on perceived comfort/discomfort and pressure distribution. The resulting human contour based prototype seat has comfort and discomfort scores comparable to a traditional seat. The prototype seat had a significantly lower average pressure between subjects' buttocks and the seat pan over a traditional seat. This study shows that it is possible to design a seat pan and backrest based on the different contours of study subjects using 3D scan technology. However, translating the 3D scans into a prototype seat also showed that this can only be seen as a first step; additionally biomechanical information and calculations are needed to create ergonomic seats. Furthermore, it is not possible to capture all different human shapes and postures and translate these into one human contour shape that fits all activities and all human sizes.

SU-C-BRB-05: Determining the Adequacy of Auto-Contouring Via Probabilistic Assessment of Ensuing Treatment Plan Metrics in Comparison with Manual Contours

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

Nourzadeh, H; Watkins, W; Siebers, J

Purpose: To determine if auto-contour and manual-contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT. Methods: Manual and auto-contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto-contouring was completed utilizing Pinnacle’s Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7-beam IMRT plans are created; PD with drawn ROIs, PAS with auto-contoured ROIs, and PM with auto-contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampledmore » systematic errors for each simulation and a different sampled random error for each fraction were performed using our in-house GPU-accelerated robustness analyzer tool which reports the statistical probability of achieving dose-volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto-contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross-evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose-volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D-PD). Results: We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV’s D95 and Dmin objectives are small for AS-PM, AS-PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS-PM, AS-PD sustain variations up to %6 compared to other evaluated pairs. Conclusion: No significant probabilistic differences are observed in the metrics when auto-contoured OARs are used. The prostate auto-contour needs improvement to achieve clinically equivalent plans.« less

Recurrent V1-V2 interaction in early visual boundary processing.

PubMed

Neumann, H; Sepp, W

1999-11-01

A majority of cortical areas are connected via feedforward and feedback fiber projections. In feedforward pathways we mainly observe stages of feature detection and integration. The computational role of the descending pathways at different stages of processing remains mainly unknown. Based on empirical findings we suggest that the top-down feedback pathways subserve a context-dependent gain control mechanism. We propose a new computational model for recurrent contour processing in which normalized activities of orientation selective contrast cells are fed forward to the next processing stage. There, the arrangement of input activation is matched against local patterns of contour shape. The resulting activities are subsequently fed back to the previous stage to locally enhance those initial measurements that are consistent with the top-down generated responses. In all, we suggest a computational theory for recurrent processing in the visual cortex in which the significance of local measurements is evaluated on the basis of a broader visual context that is represented in terms of contour code patterns. The model serves as a framework to link physiological with perceptual data gathered in psychophysical experiments. It handles a variety of perceptual phenomena, such as the local grouping of fragmented shape outline, texture surround and density effects, and the interpolation of illusory contours.

Simple computer method provides contours for radiological images

NASA Technical Reports Server (NTRS)

Newell, J. D.; Keller, R. A.; Baily, N. A.

1975-01-01

Computer is provided with information concerning boundaries in total image. Gradient of each point in digitized image is calculated with aid of threshold technique; then there is invoked set of algorithms designed to reduce number of gradient elements and to retain only major ones for definition of contour.

An Improved Snake Model for Refinement of Lidar-Derived Building Roof Contours Using Aerial Images

NASA Astrophysics Data System (ADS)

Chen, Qi; Wang, Shugen; Liu, Xiuguo

2016-06-01

Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas) has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

Left ventricle segmentation via graph cut distribution matching.

PubMed

Ben Ayed, Ismail; Punithakumar, Kumaradevan; Li, Shuo; Islam, Ali; Chong, Jaron

2009-01-01

We present a discrete kernel density matching energy for segmenting the left ventricle cavity in cardiac magnetic resonance sequences. The energy and its graph cut optimization based on an original first-order approximation of the Bhattacharyya measure have not been proposed previously, and yield competitive results in nearly real-time. The algorithm seeks a region within each frame by optimization of two priors, one geometric (distance-based) and the other photometric, each measuring a distribution similarity between the region and a model learned from the first frame. Based on global rather than pixelwise information, the proposed algorithm does not require complex training and optimization with respect to geometric transformations. Unlike related active contour methods, it does not compute iterative updates of computationally expensive kernel densities. Furthermore, the proposed first-order analysis can be used for other intractable energies and, therefore, can lead to segmentation algorithms which share the flexibility of active contours and computational advantages of graph cuts. Quantitative evaluations over 2280 images acquired from 20 subjects demonstrated that the results correlate well with independent manual segmentations by an expert.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation.

PubMed

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-08-19

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions.

In Situ 3D Segmentation of Individual Plant Leaves Using a RGB-D Camera for Agricultural Automation

PubMed Central

Xia, Chunlei; Wang, Longtan; Chung, Bu-Keun; Lee, Jang-Myung

2015-01-01

In this paper, we present a challenging task of 3D segmentation of individual plant leaves from occlusions in the complicated natural scene. Depth data of plant leaves is introduced to improve the robustness of plant leaf segmentation. The low cost RGB-D camera is utilized to capture depth and color image in fields. Mean shift clustering is applied to segment plant leaves in depth image. Plant leaves are extracted from the natural background by examining vegetation of the candidate segments produced by mean shift. Subsequently, individual leaves are segmented from occlusions by active contour models. Automatic initialization of the active contour models is implemented by calculating the center of divergence from the gradient vector field of depth image. The proposed segmentation scheme is tested through experiments under greenhouse conditions. The overall segmentation rate is 87.97% while segmentation rates for single and occluded leaves are 92.10% and 86.67%, respectively. Approximately half of the experimental results show segmentation rates of individual leaves higher than 90%. Nevertheless, the proposed method is able to segment individual leaves from heavy occlusions. PMID:26295395

Topological methods for the comparison of structures using LDR-brachytherapy of the prostate as an example.

PubMed

Schiefer, H; von Toggenburg, F; Seelentag, W W; Plasswilm, L; Ries, G; Schmid, H-P; Leippold, T; Krusche, B; Roth, J; Engeler, D

2009-08-21

The dose coverage of low dose rate (LDR)-brachytherapy for localized prostate cancer is monitored 4-6 weeks after intervention by contouring the prostate on computed tomography and/or magnetic resonance imaging sets. Dose parameters for the prostate (V100, D90 and D80) provide information on the treatment quality. Those depend strongly on the delineation of the prostate contours. We therefore systematically investigated the contouring process for 21 patients with five examiners. The prostate structures were compared with one another using topological procedures based on Boolean algebra. The coincidence number C(V) measures the agreement between a set of structures. The mutual coincidence C(i, j) measures the agreement between two structures i and j, and the mean coincidence C(i) compares a selected structure i with the remaining structures in a set. All coincidence parameters have a value of 1 for complete coincidence of contouring and 0 for complete absence. The five patients with the lowest C(V) values were discussed, and rules for contouring the prostate have been formulated. The contouring and assessment were repeated after 3 months for the same five patients. All coincidence parameters have been improved after instruction. This shows objectively that training resulted in more consistent contouring across examiners.

System and method for measuring residual stress

DOEpatents

Prime, Michael B.

2002-01-01

The present invention is a method and system for determining the residual stress within an elastic object. In the method, an elastic object is cut along a path having a known configuration. The cut creates a portion of the object having a new free surface. The free surface then deforms to a contour which is different from the path. Next, the contour is measured to determine how much deformation has occurred across the new free surface. Points defining the contour are collected in an empirical data set. The portion of the object is then modeled in a computer simulator. The points in the empirical data set are entered into the computer simulator. The computer simulator then calculates the residual stress along the path which caused the points within the object to move to the positions measured in the empirical data set. The calculated residual stress is then presented in a useful format to an analyst.

User-initialized active contour segmentation and golden-angle real-time cardiovascular magnetic resonance enable accurate assessment of LV function in patients with sinus rhythm and arrhythmias.

PubMed

Contijoch, Francisco; Witschey, Walter R T; Rogers, Kelly; Rears, Hannah; Hansen, Michael; Yushkevich, Paul; Gorman, Joseph; Gorman, Robert C; Han, Yuchi

2015-05-21

Data obtained during arrhythmia is retained in real-time cardiovascular magnetic resonance (rt-CMR), but there is limited and inconsistent evidence to show that rt-CMR can accurately assess beat-to-beat variation in left ventricular (LV) function or during an arrhythmia. Multi-slice, short axis cine and real-time golden-angle radial CMR data was collected in 22 clinical patients (18 in sinus rhythm and 4 patients with arrhythmia). A user-initialized active contour segmentation (ACS) software was validated via comparison to manual segmentation on clinically accepted software. For each image in the 2D acquisitions, slice volume was calculated and global LV volumes were estimated via summation across the LV using multiple slices. Real-time imaging data was reconstructed using different image exposure times and frame rates to evaluate the effect of temporal resolution on measured function in each slice via ACS. Finally, global volumetric function of ectopic and non-ectopic beats was measured using ACS in patients with arrhythmias. ACS provides global LV volume measurements that are not significantly different from manual quantification of retrospectively gated cine images in sinus rhythm patients. With an exposure time of 95.2 ms and a frame rate of > 89 frames per second, golden-angle real-time imaging accurately captures hemodynamic function over a range of patient heart rates. In four patients with frequent ectopic contractions, initial quantification of the impact of ectopic beats on hemodynamic function was demonstrated. User-initialized active contours and golden-angle real-time radial CMR can be used to determine time-varying LV function in patients. These methods will be very useful for the assessment of LV function in patients with frequent arrhythmias.

3D-QSAR and Molecular Docking Studies on Derivatives of MK-0457, GSK1070916 and SNS-314 as Inhibitors against Aurora B Kinase

PubMed Central

Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi

2010-01-01

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q2 = 0.605, r2pred = 0.826), (q2 = 0.52, r2pred = 0.798) and (q2 = 0.582, r2pred = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors. PMID:21151441

3D-QSAR and molecular docking studies on derivatives of MK-0457, GSK1070916 and SNS-314 as inhibitors against Aurora B kinase.

PubMed

Zhang, Baidong; Li, Yan; Zhang, Huixiao; Ai, Chunzhi

2010-11-02

Development of anticancer drugs targeting Aurora B, an important member of the serine/threonine kinases family, has been extensively focused on in recent years. In this work, by applying an integrated computational method, including comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), homology modeling and molecular docking, we investigated the structural determinants of Aurora B inhibitors based on three different series of derivatives of 108 molecules. The resultant optimum 3D-QSAR models exhibited (q(2) = 0.605, r(2) (pred) = 0.826), (q(2) = 0.52, r(2) (pred) = 0.798) and (q(2) = 0.582, r(2) (pred) = 0.971) for MK-0457, GSK1070916 and SNS-314 classes, respectively, and the 3D contour maps generated from these models were analyzed individually. The contour map analysis for the MK-0457 model revealed the relative importance of steric and electrostatic effects for Aurora B inhibition, whereas, the electronegative groups with hydrogen bond donating capacity showed a great impact on the inhibitory activity for the derivatives of GSK1070916. Additionally, the predictive model of the SNS-314 class revealed the great importance of hydrophobic favorable contour, since hydrophobic favorable substituents added to this region bind to a deep and narrow hydrophobic pocket composed of residues that are hydrophobic in nature and thus enhanced the inhibitory activity. Moreover, based on the docking study, a further comparison of the binding modes was accomplished to identify a set of critical residues that play a key role in stabilizing the drug-target interactions. Overall, the high level of consistency between the 3D contour maps and the topographical features of binding sites led to our identification of several key structural requirements for more potency inhibitors. Taken together, the results will serve as a basis for future drug development of inhibitors against Aurora B kinase for various tumors.

Proposed method of producing large optical mirrors Single-point diamond crushing followed by polishing with a small-area tool

NASA Technical Reports Server (NTRS)

Wright, G.; Bryan, J. B.

1986-01-01

Faster production of large optical mirrors may result from combining single-point diamond crushing of the glass with polishing using a small area tool to smooth the surface and remove the damaged layer. Diamond crushing allows a surface contour accurate to 0.5 microns to be generated, and the small area computer-controlled polishing tool allows the surface roughness to be removed without destroying the initial contour. Final contours with an accuracy of 0.04 microns have been achieved.

Perception of English intonation by English, Spanish, and Chinese listeners.

PubMed

Grabe, Esther; Rosner, Burton S; García-Albea, José E; Zhou, Xiaolin

2003-01-01

Native language affects the perception of segmental phonetic structure, of stress, and of semantic and pragmatic effects of intonation. Similarly, native language might influence the perception of similarities and differences among intonation contours. To test this hypothesis, a cross-language experiment was conducted. An English utterance was resynthesized with seven falling and four rising intonation contours. English, Iberian Spanish, and Chinese listeners then rated each pair of nonidentical stimuli for degree of difference. Multidimensional scaling of the results supported the hypothesis. The three groups of listeners produced statistically different perceptual configurations for the falling contours. All groups, however, perceptually separated the falling from the rising contours. This result suggested that the perception of intonation begins with the activation of universal auditory mechanisms that process the direction of relatively slow frequency modulations. A second experiment therefore employed frequency-modulated sine waves that duplicated the fundamental frequency contours of the speech stimuli. New groups of English, Spanish, and Chinese subjects yielded no cross-language differences between the perceptual configurations for these nonspeech stimuli. The perception of similarities and differences among intonation contours calls upon universal auditory mechanisms whose output is molded by experience with one's native language.

Segmentation algorithm on smartphone dual camera: application to plant organs in the wild

NASA Astrophysics Data System (ADS)

Bertrand, Sarah; Cerutti, Guillaume; Tougne, Laure

2018-04-01

In order to identify the species of a tree, the different organs that are the leaves, the bark, the flowers and the fruits, are inspected by botanists. So as to develop an algorithm that identifies automatically the species, we need to extract these objects of interest from their complex natural environment. In this article, we focus on the segmentation of flowers and fruits and we present a new method of segmentation based on an active contour algorithm using two probability maps. The first map is constructed via the dual camera that we can find on the back of the latest smartphones. The second map is made with the help of a multilayer perceptron (MLP). The combination of these two maps to drive the evolution of the object contour allows an efficient segmentation of the organ from a natural background.

SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

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

Ren, X; Gao, H; Sharp, G

2015-06-15

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to eachmore » chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

An accurate and efficient acoustic eigensolver based on a fast multipole BEM and a contour integral method

NASA Astrophysics Data System (ADS)

Zheng, Chang-Jun; Gao, Hai-Feng; Du, Lei; Chen, Hai-Bo; Zhang, Chuanzeng

2016-01-01

An accurate numerical solver is developed in this paper for eigenproblems governed by the Helmholtz equation and formulated through the boundary element method. A contour integral method is used to convert the nonlinear eigenproblem into an ordinary eigenproblem, so that eigenvalues can be extracted accurately by solving a set of standard boundary element systems of equations. In order to accelerate the solution procedure, the parameters affecting the accuracy and efficiency of the method are studied and two contour paths are compared. Moreover, a wideband fast multipole method is implemented with a block IDR (s) solver to reduce the overall solution cost of the boundary element systems of equations with multiple right-hand sides. The Burton-Miller formulation is employed to identify the fictitious eigenfrequencies of the interior acoustic problems with multiply connected domains. The actual effect of the Burton-Miller formulation on tackling the fictitious eigenfrequency problem is investigated and the optimal choice of the coupling parameter as α = i / k is confirmed through exterior sphere examples. Furthermore, the numerical eigenvalues obtained by the developed method are compared with the results obtained by the finite element method to show the accuracy and efficiency of the developed method.

A hybrid approach of using symmetry technique for brain tumor segmentation.

PubMed

Saddique, Mubbashar; Kazmi, Jawad Haider; Qureshi, Kalim

2014-01-01

Tumor and related abnormalities are a major cause of disability and death worldwide. Magnetic resonance imaging (MRI) is a superior modality due to its noninvasiveness and high quality images of both the soft tissues and bones. In this paper we present two hybrid segmentation techniques and their results are compared with well-recognized techniques in this area. The first technique is based on symmetry and we call it a hybrid algorithm using symmetry and active contour (HASA). In HASA, we take refection image, calculate the difference image, and then apply the active contour on the difference image to segment the tumor. To avoid unimportant segmented regions, we improve the results by proposing an enhancement in the form of the second technique, EHASA. In EHASA, we also take reflection of the original image, calculate the difference image, and then change this image into a binary image. This binary image is mapped onto the original image followed by the application of active contouring to segment the tumor region.

Spatiotemporal frequency characteristics of cerebral oscillations during the perception of fundamental frequency contour changes in one-syllable intonation.

PubMed

Ueno, Sanae; Okumura, Eiichi; Remijn, Gerard B; Yoshimura, Yuko; Kikuchi, Mitsuru; Shitamichi, Kiyomi; Nagao, Kikuko; Mochiduki, Masayuki; Haruta, Yasuhiro; Hayashi, Norio; Munesue, Toshio; Tsubokawa, Tsunehisa; Oi, Manabu; Nakatani, Hideo; Higashida, Haruhiro; Minabe, Yoshio

2012-05-02

Accurate perception of fundamental frequency (F0) contour changes in the human voice is important for understanding a speaker's intonation, and consequently also his/her attitude. In this study, we investigated the neural processes involved in the perception of F0 contour changes in the Japanese one-syllable interjection "ne" in 21 native-Japanese listeners. A passive oddball paradigm was applied in which "ne" with a high falling F0 contour, used when urging a reaction from the listener, was randomly presented as a rare deviant among a frequent "ne" syllable with a flat F0 contour (i.e., meaningless intonation). We applied an adaptive spatial filtering method to the neuromagnetic time course recorded by whole-head magnetoencephalography (MEG) and estimated the spatiotemporal frequency dynamics of event-related cerebral oscillatory changes in the oddball paradigm. Our results demonstrated a significant elevation of beta band event-related desynchronization (ERD) in the right temporal and frontal areas, in time windows from 100 to 300 and from 300 to 500 ms after the onset of deviant stimuli (high falling F0 contour). This is the first study to reveal detailed spatiotemporal frequency characteristics of cerebral oscillations during the perception of intonational (not lexical) F0 contour changes in the human voice. The results further confirmed that the right hemisphere is associated with perception of intonational F0 contour information in the human voice, especially in early time windows. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Accurate and ergonomic method of registration for image-guided neurosurgery

NASA Astrophysics Data System (ADS)

Henderson, Jaimie M.; Bucholz, Richard D.

1994-05-01

There has been considerable interest in the development of frameless stereotaxy based upon scalp mounted fiducials. In practice we have experienced difficulty in relating markers to the image data sets in our series of 25 frameless cases, as well as inaccuracy due to scalp movement and the size of the markers. We have developed an alternative system for accurately and conveniently achieving surgical registration for image-guided neurosurgery based on alignment and matching of patient forehead contours. The system consists of a laser contour digitizer which is used in the operating room to acquire forehead contours, editing software for extracting contours from patient image data sets, and a contour-match algorithm for aligning the two contours and performing data set registration. The contour digitizer is tracked by a camera array which relates its position with respect to light emitting diodes placed on the head clamp. Once registered, surgical instrument can be tracked throughout the procedure. Contours can be extracted from either CT or MRI image datasets. The system has proven to be robust in the laboratory setting. Overall error of registration is 1 - 2 millimeters in routine use. Image to patient registration can therefore be achieved quite easily and accurately, without the need for fixation of external markers to the skull, or manually finding markers on the scalp and image datasets. The system is unobtrusive and imposes little additional effort on the neurosurgeon, broadening the appeal of image-guided surgery.

Natural frequencies of thin rectangular plates clamped on contour using the Finite Element Method

NASA Astrophysics Data System (ADS)

(Barboni Haţiegan, L.; Haţiegan, C.; Gillich, G. R.; Hamat, C. O.; Vasile, O.; Stroia, M. D.

2018-01-01

This paper presents the determining of natural frequencies of plates without and with damages using the finite element method of SolidWorks program. The first thirty natural frequencies obtained for thin rectangular rectangular plates clamped on contour without and with central damages a for different dimensions. The relative variation of natural frequency was determined and the obtained results by the finite element method (FEM) respectively relative variation of natural frequency, were graphically represented according to their vibration natural modes. Finally, the obtained results were compared.

Complications from laser-assisted liposuction performed by noncore practitioners.

PubMed

Blum, Craig A; Sasser, Charles G S; Kaplan, Jonathan L

2013-10-01

Liposuction is one of the most commonly performed aesthetic surgery procedures in the United States, and most plastic surgeons perform suction-assisted, ultrasound-assisted, or power-assisted liposuction. The past decade has seen a growing interest in laser-assisted liposuction (LAL) and the proposed advantages of traditional liposuction methods. However, it is performed by a minority of plastic surgeons. In fact, many LAL providers are not trained in aesthetic practice, and many offer LAL as their only body-contouring procedure. When only one method of body contouring is available to a provider, it may lead to inappropriate patient selection with associated poor outcomes. This report discusses the use of laser liposuction in body contouring and the demographics of those performing liposuction, including LAL. Complications from laser-assisted liposuction performed by noncore practitioners are illustrated.

Multi-sensor image registration based on algebraic projective invariants.

PubMed

Li, Bin; Wang, Wei; Ye, Hao

2013-04-22

A new automatic feature-based registration algorithm is presented for multi-sensor images with projective deformation. Contours are firstly extracted from both reference and sensed images as basic features in the proposed method. Since it is difficult to design a projective-invariant descriptor from the contour information directly, a new feature named Five Sequential Corners (FSC) is constructed based on the corners detected from the extracted contours. By introducing algebraic projective invariants, we design a descriptor for each FSC that is ensured to be robust against projective deformation. Further, no gray scale related information is required in calculating the descriptor, thus it is also robust against the gray scale discrepancy between the multi-sensor image pairs. Experimental results utilizing real image pairs are presented to show the merits of the proposed registration method.

SU-F-J-161: Prostate Contouring in Patients with Bilateral Hip Prostheses: Impact of Using Artifact-Reduced CT Images and MRI

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

Elzibak, A; Loblaw, A; Morton, G

Purpose: To investigate the usefulness of metal artifact reduction in CT images of patients with bilateral hip prostheses (BHP) for contouring the prostate and determine if the inclusion of MR images provides additional benefits. Methods: Five patients with BHP were CT scanned using our clinical protocol (140kV, 300mAs, 3mm slices, 1.5mm increment, Philips Medical Systems, OH). Images were reconstructed with the orthopaedic metal artifact reduction (O-MAR) algorithm. MRI scanning was then performed (1.5T, GE Healthcare, WI) with a flat table-top (T{sub 2}-weighted, inherent body coil, FRFSE, 3mm slices with 0mm gap). All images were transferred to Pinnacle (Version 9.2, Philipsmore » Medical Systems). For each patient, two data sets were produced: one containing the O-MAR-corrected CT images and another containing fused MRI and O-MAR-corrected CT images. Four genito-urinary radiation oncologists contoured the prostate of each patient on the O-MAR-corrected CT data. Two weeks later, they contoured the prostate on the fused data set, blinded to all other contours. During each contouring session, the oncologists reported their confidence in the contours (1=very confident, 3=not confident) and the contouring difficulty that they experienced (1=really easy, 4=very challenging). Prostate volumes were computed from the contours and the conformity index was used to evaluate inter-observer variability. Results: Larger prostate volumes were found on the O-MAR-corrected CT set than on the fused set (p< 0.05, median=36.9cm{sup 3} vs. 26.63 cm{sup 3}). No significant differences were noted in the inter-observer variability between the two data sets (p=0.3). Contouring difficulty decreased with the addition of MRI (p<0.05) while the radiation oncologists reported more confidence in their contours when MRI was fused with the O-MAR-corrected CT data (p<0.05). Conclusion: This preliminary work demonstrated that, while O-MAR correction to CT images improves visualization of anatomy, the addition of MRI enhanced the oncologists’ confidence in contouring the prostate in patients with BHP.« less

Microdevice having interior cavity with high aspect ratio surface features and associated methods of manufacture and use

DOEpatents

Morales, Alfredo M.

2002-01-01

A microdevice having interior cavity with high aspect ratio features and ultrasmooth surfaces, and associated method of manufacture and use is described. An LIGA-produced shaped bit is used to contour polish the surface of a sacrificial mandrel. The contoured sacrificial mandrel is subsequently coated with a structural material and the mandrel removed to produce microdevices having micrometer-sized surface features and sub-micrometer RMS surface roughness.

A method for modifying two-dimensional adaptive wind-tunnel walls including analytical and experimental verification

NASA Technical Reports Server (NTRS)

Everhart, J. L.

1983-01-01

The theoretical development of a simple and consistent method for removing the interference in adaptive-wall wind tunnels is reported. A Cauchy integral formulation of the velocities in an imaginary infinite extension of the real wind-tunnel flow is obtained and evaluated on a closed contour dividing the real and imaginary flow. The contour consists of the upper and lower effective wind-tunnel walls (wall plus boundary-layer displacement thickness) and upstream and downstream boundaries perpendicular to the axial tunnel flow. The resulting integral expressions for the streamwise and normal perturbation velocities on the contour are integrated by assuming a linear variation of the velocities between data-measurement stations along the contour. In an iterative process, the velocity components calculated on the upper and lower boundaries are then used to correct the shape of the wall to remove the interference. Convergence of the technique is shown numerically for the cases of a circular cylinder and a lifting and nonlifting NACA 0012 airfoil in incompressible flow. Experimental convergence at a transonic Mach number is demonstrated by using an NACA 0012 airfoil at zero lift.

Can partial coherence interferometry be used to determine retinal shape?

PubMed

Atchison, David A; Charman, W Neil

2011-05-01

To determine likely errors in estimating retinal shape using partial coherence interferometric instruments when no allowance is made for optical distortion. Errors were estimated using Gullstrand no. 1 schematic eye and variants which included a 10 diopter (D) axial myopic eye, an emmetropic eye with a gradient-index lens, and a 10.9 D accommodating eye with a gradient-index lens. Performance was simulated for two commercial instruments, the IOLMaster (Carl Zeiss Meditec) and the Lenstar LS 900 (Haag-Streit AG). The incident beam was directed toward either the center of curvature of the anterior cornea (corneal-direction method) or the center of the entrance pupil (pupil-direction method). Simple trigonometry was used with the corneal intercept and the incident beam angle to estimate retinal contour. Conics were fitted to the estimated contours. The pupil-direction method gave estimates of retinal contour that were much too flat. The cornea-direction method gave similar results for IOLMaster and Lenstar approaches. The steepness of the retinal contour was slightly overestimated, the exact effects varying with the refractive error, gradient index, and accommodation. These theoretical results suggest that, for field angles ≤30°, partial coherence interferometric instruments are of use in estimating retinal shape by the corneal-direction method with the assumptions of a regular retinal shape and no optical distortion. It may be possible to improve on these estimates out to larger field angles by using optical modeling to correct for distortion.

Prostate contouring in MRI guided biopsy.

PubMed

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2009-03-27

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice.

Prostate contouring in MRI guided biopsy

PubMed Central

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2010-01-01

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

Valley and channel networks extraction based on local topographic curvature and k-means clustering of contours

NASA Astrophysics Data System (ADS)

Hooshyar, Milad; Wang, Dingbao; Kim, Seoyoung; Medeiros, Stephen C.; Hagen, Scott C.

2016-10-01

A method for automatic extraction of valley and channel networks from high-resolution digital elevation models (DEMs) is presented. This method utilizes both positive (i.e., convergent topography) and negative (i.e., divergent topography) curvature to delineate the valley network. The valley and ridge skeletons are extracted using the pixels' curvature and the local terrain conditions. The valley network is generated by checking the terrain for the existence of at least one ridge between two intersecting valleys. The transition from unchannelized to channelized sections (i.e., channel head) in each first-order valley tributary is identified independently by categorizing the corresponding contours using an unsupervised approach based on k-means clustering. The method does not require a spatially constant channel initiation threshold (e.g., curvature or contributing area). Moreover, instead of a point attribute (e.g., curvature), the proposed clustering method utilizes the shape of contours, which reflects the entire cross-sectional profile including possible banks. The method was applied to three catchments: Indian Creek and Mid Bailey Run in Ohio and Feather River in California. The accuracy of channel head extraction from the proposed method is comparable to state-of-the-art channel extraction methods.

Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.

PubMed

Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel

2017-01-01

The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images. Copyright © 2016 Elsevier B.V. All rights reserved.

Echo movement and evolution from real-time processing.

NASA Technical Reports Server (NTRS)

Schaffner, M. R.

1972-01-01

Preliminary experimental data on the effectiveness of conventional radars in measuring the movement and evolution of meteorological echoes when the radar is connected to a programmable real-time processor are examined. In the processor programming is accomplished by conceiving abstract machines which constitute the actual programs used in the methods employed. An analysis of these methods, such as the center of gravity method, the contour-displacement method, the method of slope, the cross-section method, the contour crosscorrelation method, the method of echo evolution at each point, and three-dimensional measurements, shows that the motions deduced from them may differ notably (since each method determines different quantities) but the plurality of measurement may give additional information on the characteristics of the precipitation.

Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.

Dentalmaps: Automatic Dental Delineation for Radiotherapy Planning in Head-and-Neck Cancer

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

Thariat, Juliette, E-mail: jthariat@hotmail.com; Ramus, Liliane; INRIA

Purpose: To propose an automatic atlas-based segmentation framework of the dental structures, called Dentalmaps, and to assess its accuracy and relevance to guide dental care in the context of intensity-modulated radiotherapy. Methods and Materials: A multi-atlas-based segmentation, less sensitive to artifacts than previously published head-and-neck segmentation methods, was used. The manual segmentations of a 21-patient database were first deformed onto the query using nonlinear registrations with the training images and then fused to estimate the consensus segmentation of the query. Results: The framework was evaluated with a leave-one-out protocol. The maximum doses estimated using manual contours were considered as groundmore » truth and compared with the maximum doses estimated using automatic contours. The dose estimation error was within 2-Gy accuracy in 75% of cases (with a median of 0.9 Gy), whereas it was within 2-Gy accuracy in 30% of cases only with the visual estimation method without any contour, which is the routine practice procedure. Conclusions: Dose estimates using this framework were more accurate than visual estimates without dental contour. Dentalmaps represents a useful documentation and communication tool between radiation oncologists and dentists in routine practice. Prospective multicenter assessment is underway on patients extrinsic to the database.« less

Model-based Roentgen stereophotogrammetry of orthopaedic implants.

PubMed

Valstar, E R; de Jong, F W; Vrooman, H A; Rozing, P M; Reiber, J H

2001-06-01

Attaching tantalum markers to prostheses for Roentgen stereophotogrammetry (RSA) may be difficult and is sometimes even impossible. In this study, a model-based RSA method that avoids the attachment of markers to prostheses is presented and validated. This model-based RSA method uses a triangulated surface model of the implant. A projected contour of this model is calculated and this calculated model contour is matched onto the detected contour of the actual implant in the RSA radiograph. The difference between the two contours is minimized by variation of the position and orientation of the model. When a minimal difference between the contours is found, an optimal position and orientation of the model has been obtained. The method was validated by means of a phantom experiment. Three prosthesis components were used in this experiment: the femoral and tibial component of an Interax total knee prosthesis (Stryker Howmedica Osteonics Corp., Rutherfort, USA) and the femoral component of a Profix total knee prosthesis (Smith & Nephew, Memphis, USA). For the prosthesis components used in this study, the accuracy of the model-based method is lower than the accuracy of traditional RSA. For the Interax femoral and tibial components, significant dimensional tolerances were found that were probably caused by the casting process and manual polishing of the components surfaces. The largest standard deviation for any translation was 0.19mm and for any rotation it was 0.52 degrees. For the Profix femoral component that had no large dimensional tolerances, the largest standard deviation for any translation was 0.22mm and for any rotation it was 0.22 degrees. From this study we may conclude that the accuracy of the current model-based RSA method is sensitive to dimensional tolerances of the implant. Research is now being conducted to make model-based RSA less sensitive to dimensional tolerances and thereby improving its accuracy.

Processing and Memory of Color, Contour, and Pattern Found in Computer Digitized Color Pictures for Elementary Children.

ERIC Educational Resources Information Center

Marschalek, Douglas G.

1988-01-01

Describes study of children in grades one, three, and five that examined their active processing and short term memory (STM) of color, contour, and interior pattern of shapes found in computer digitized pictures. Age-related differences are examined, and the role of processing visual information in the learning process is discussed. (12…

SU-F-J-140: Using Handheld Stereo Depth Cameras to Extend Medical Imaging for Radiation Therapy Planning

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

Jenkins, C; Xing, L; Yu, S

Purpose: A correct body contour is essential for the accuracy of dose calculation in radiation therapy. While modern medical imaging technologies provide highly accurate representations of body contours, there are times when a patient’s anatomy cannot be fully captured or there is a lack of easy access to CT/MRI scanning. Recently, handheld cameras have emerged that are capable of performing three dimensional (3D) scans of patient surface anatomy. By combining 3D camera and medical imaging data, the patient’s surface contour can be fully captured. Methods: A proof-of-concept system matches a patient surface model, created using a handheld stereo depth cameramore » (DC), to the available areas of a body contour segmented from a CT scan. The matched surface contour is then converted to a DICOM structure and added to the CT dataset to provide additional contour information. In order to evaluate the system, a 3D model of a patient was created by segmenting the body contour with a treatment planning system (TPS) and fabricated with a 3D printer. A DC and associated software were used to create a 3D scan of the printed phantom. The surface created by the camera was then registered to a CT model that had been cropped to simulate missing scan data. The aligned surface was then imported into the TPS and compared with the originally segmented contour. Results: The RMS error for the alignment between the camera and cropped CT models was 2.26 mm. Mean distance between the aligned camera surface and ground truth model was −1.23 +/−2.47 mm. Maximum deviations were < 1 cm and occurred in areas of high concavity or where anatomy was close to the couch. Conclusion: The proof-of-concept study shows an accurate, easy and affordable method to extend medical imaging for radiation therapy planning using 3D cameras without additional radiation. Intel provided the camera hardware used in this study.« less

Optimization of morphological parameters for mitigation pits on rear KDP surface: experiments and numerical modeling.

PubMed

Yang, Hao; Cheng, Jian; Chen, Mingjun; Wang, Jian; Liu, Zhichao; An, Chenhui; Zheng, Yi; Hu, Kehui; Liu, Qi

2017-07-24

In high power laser systems, precision micro-machining is an effective method to mitigate the laser-induced surface damage growth on potassium dihydrogen phosphate (KDP) crystal. Repaired surfaces with smooth spherical and Gaussian contours can alleviate the light field modulation caused by damage site. To obtain the optimal repairing structure parameters, finite element method (FEM) models for simulating the light intensification caused by the mitigation pits on rear KDP surface were established. The light intensity modulation of these repairing profiles was compared by changing the structure parameters. The results indicate the modulation is mainly caused by the mutual interference between the reflected and incident lights on the rear surface. Owing to the total reflection, the light intensity enhancement factors (LIEFs) of the spherical and Gaussian mitigation pits sharply increase when the width-depth ratios are near 5.28 and 3.88, respectively. To achieve the optimal mitigation effect, the width-depth ratios greater than 5.3 and 4.3 should be applied to the spherical and Gaussian repaired contours. Particularly, for the cases of width-depth ratios greater than 5.3, the spherical repaired contour is preferred to achieve lower light intensification. The laser damage test shows that when the width-depth ratios are larger than 5.3, the spherical repaired contour presents higher laser damage resistance than that of Gaussian repaired contour, which agrees well with the simulation results.

Segmentation of lung fields using Chan-Vese active contour model in chest radiographs

NASA Astrophysics Data System (ADS)

Sohn, Kiwon

2011-03-01

A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese active contour model, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

3D-QSAR analysis of MCD inhibitors by CoMFA and CoMSIA.

PubMed

Pourbasheer, Eslam; Aalizadeh, Reza; Ebadi, Amin; Ganjali, Mohammad Reza

2015-01-01

Three-dimensional quantitative structure-activity relationship was developed for the series of compounds as malonyl-CoA decarboxylase antagonists (MCD) using the CoMFA and CoMSIA methods. The statistical parameters for CoMFA (q(2)=0.558, r(2)=0.841) and CoMSIA (q(2)= 0.615, r(2) = 0.870) models were derived based on 38 compounds as training set in the basis of the selected alignment. The external predictive abilities of the built models were evaluated by using the test set of nine compounds. From obtained results, the CoMSIA method was found to have highly predictive capability in comparison with CoMFA method. Based on the given results by CoMSIA and CoMFA contour maps, some features that can enhance the activity of compounds as MCD antagonists were introduced and used to design new compounds with better inhibition activity.

A simple method for the generation of organ and vessel contours from roentgenographic or fluoroscopic images

NASA Technical Reports Server (NTRS)

Newell, J. D.; Keller, R. A.; Baily, N. A.

1974-01-01

A simple method for outlining or contouring any area defined by a change in film density or fluoroscopic screen intensity is described. The entire process, except for the positioning of an electronic window, is accomplished using a small computer having appropriate softwave. The electronic window is operator positioned over the area to be processed. The only requirement is that the window be large enough to encompass the total area to be considered.

Effects of Lexical Tone Contour on Mandarin Sentence Intelligibility

ERIC Educational Resources Information Center

Chen, Fei; Wong, Lena L. N.; Hu, Yi

2014-01-01

Purpose: This study examined the effects of lexical tone contour on the intelligibility of Mandarin sentences in quiet and in noise. Method: A text-to-speech synthesis engine was used to synthesize Mandarin sentences with each word carrying the original lexical tone, flat tone, or a tone randomly selected from the 4 Mandarin lexical tones. The…

Holographic Moire Contouring

NASA Astrophysics Data System (ADS)

Sciammarella, C. A.; Sainov, Ventseslav; Simova, Eli

1990-04-01

Theoretical analysis and experimental results on holographic moire contouring (HMC) of difussely reflecting objects are presented. The sensitivity and application constraints of the method are discussed. A high signal-to-noise ratio and contrast of the fringes is achieved through the use of high quality silver halide holographic plates HP-650. A good agreement between theoretical and experimental results is observed.

Language-dependent changes in pitch-relevant neural activity in the auditory cortex reflect differential weighting of temporal attributes of pitch contours

PubMed Central

Krishnan, Ananthanarayan; Gandour, Jackson T.; Xu, Yi; Suresh, Chandan H.

2016-01-01

There remains a gap in our knowledge base about neural representation of pitch attributes that occur between onset and offset of dynamic, curvilinear pitch contours. The aim is to evaluate how language experience shapes processing of pitch contours as reflected in the amplitude of cortical pitch-specific response components. Responses were elicited from three nonspeech, bidirectional (falling-rising) pitch contours representative of Mandarin Tone 2 varying in location of the turning point with fixed onset and offset. At the frontocentral Fz electrode site, Na–Pb and Pb–Nb amplitude of the Chinese group was larger than the English group for pitch contours exhibiting later location of the turning point relative to the one with the earliest location. Chinese listeners’ amplitude was also greater than that of English in response to those same pitch contours with later turning points. At lateral temporal sites (T7/T8), Na–Pb amplitude was larger in Chinese listeners relative to English over the right temporal site. In addition, Pb–Nb amplitude of the Chinese group showed a rightward asymmetry. The pitch contour with its turning point located about halfway of total duration evoked a rightward asymmetry regardless of group. These findings suggest that neural mechanisms processing pitch in the right auditory cortex reflect experience-dependent modulation of sensitivity to weighted integration of changes in acceleration rates of rising and falling sections and the location of the turning point. PMID:28713201

SU-F-J-96: Comparison of Frame-Based and Mutual Information Registration Techniques for CT and MR Image Sets

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

Popple, R; Bredel, M; Brezovich, I

Purpose: To compare the accuracy of CT-MR registration using a mutual information method with registration using a frame-based localizer box. Methods: Ten patients having the Leksell head frame and scanned with a modality specific localizer box were imported into the treatment planning system. The fiducial rods of the localizer box were contoured on both the MR and CT scans. The skull was contoured on the CT images. The MR and CT images were registered by two methods. The frame-based method used the transformation that minimized the mean square distance of the centroids of the contours of the fiducial rods frommore » a mathematical model of the localizer. The mutual information method used automated image registration tools in the TPS and was restricted to a volume-of-interest defined by the skull contours with a 5 mm margin. For each case, the two registrations were adjusted by two evaluation teams, each comprised of an experienced radiation oncologist and neurosurgeon, to optimize alignment in the region of the brainstem. The teams were blinded to the registration method. Results: The mean adjustment was 0.4 mm (range 0 to 2 mm) and 0.2 mm (range 0 to 1 mm) for the frame and mutual information methods, respectively. The median difference between the frame and mutual information registrations was 0.3 mm, but was not statistically significant using the Wilcoxon signed rank test (p=0.37). Conclusion: The difference between frame and mutual information registration techniques was neither statistically significant nor, for most applications, clinically important. These results suggest that mutual information is equivalent to frame-based image registration for radiosurgery. Work is ongoing to add additional evaluators and to assess the differences between evaluators.« less

Individual tree crown delineation using localized contour tree method and airborne LiDAR data in coniferous forests

NASA Astrophysics Data System (ADS)

Wu, Bin; Yu, Bailang; Wu, Qiusheng; Huang, Yan; Chen, Zuoqi; Wu, Jianping

2016-10-01

Individual tree crown delineation is of great importance for forest inventory and management. The increasing availability of high-resolution airborne light detection and ranging (LiDAR) data makes it possible to delineate the crown structure of individual trees and deduce their geometric properties with high accuracy. In this study, we developed an automated segmentation method that is able to fully utilize high-resolution LiDAR data for detecting, extracting, and characterizing individual tree crowns with a multitude of geometric and topological properties. The proposed approach captures topological structure of forest and quantifies topological relationships of tree crowns by using a graph theory-based localized contour tree method, and finally segments individual tree crowns by analogy of recognizing hills from a topographic map. This approach consists of five key technical components: (1) derivation of canopy height model from airborne LiDAR data; (2) generation of contours based on the canopy height model; (3) extraction of hierarchical structures of tree crowns using the localized contour tree method; (4) delineation of individual tree crowns by segmenting hierarchical crown structure; and (5) calculation of geometric and topological properties of individual trees. We applied our new method to the Medicine Bow National Forest in the southwest of Laramie, Wyoming and the HJ Andrews Experimental Forest in the central portion of the Cascade Range of Oregon, U.S. The results reveal that the overall accuracy of individual tree crown delineation for the two study areas achieved 94.21% and 75.07%, respectively. Our method holds great potential for segmenting individual tree crowns under various forest conditions. Furthermore, the geometric and topological attributes derived from our method provide comprehensive and essential information for forest management.

On Machine Capacitance Dimensional and Surface Profile Measurement System

NASA Technical Reports Server (NTRS)

Resnick, Ralph

1993-01-01

A program was awarded under the Air Force Machine Tool Sensor Improvements Program Research and Development Announcement to develop and demonstrate the use of a Capacitance Sensor System including Capacitive Non-Contact Analog Probe and a Capacitive Array Dimensional Measurement System to check the dimensions of complex shapes and contours on a machine tool or in an automated inspection cell. The manufacturing of complex shapes and contours and the subsequent verification of those manufactured shapes is fundamental and widespread throughout industry. The critical profile of a gear tooth; the overall shape of a graphite EDM electrode; the contour of a turbine blade in a jet engine; and countless other components in varied applications possess complex shapes that require detailed and complex inspection procedures. Current inspection methods for complex shapes and contours are expensive, time-consuming, and labor intensive.

Validation of a Magnetic Resonance Imaging-based Auto-contouring Software Tool for Gross Tumour Delineation in Head and Neck Cancer Radiotherapy Planning.

PubMed

Doshi, T; Wilson, C; Paterson, C; Lamb, C; James, A; MacKenzie, K; Soraghan, J; Petropoulakis, L; Di Caterina, G; Grose, D

2017-01-01

To carry out statistical validation of a newly developed magnetic resonance imaging (MRI) auto-contouring software tool for gross tumour volume (GTV) delineation in head and neck tumours to assist in radiotherapy planning. Axial MRI baseline scans were obtained for 10 oropharyngeal and laryngeal cancer patients. GTV was present on 102 axial slices and auto-contoured using the modified fuzzy c-means clustering integrated with the level set method (FCLSM). Peer-reviewed (C-gold) manual contours were used as the reference standard to validate auto-contoured GTVs (C-auto) and mean manual contours (C-manual) from two expert clinicians (C1 and C2). Multiple geometric metrics, including the Dice similarity coefficient (DSC), were used for quantitative validation. A DSC≥0.7 was deemed acceptable. Inter- and intra-variabilities among the manual contours were also validated. The two-dimensional contours were then reconstructed in three dimensions for GTV volume calculation, comparison and three-dimensional visualisation. The mean DSC between C-gold and C-auto was 0.79. The mean DSC between C-gold and C-manual was 0.79 and that between C1 and C2 was 0.80. The average time for GTV auto-contouring per patient was 8 min (range 6-13 min; mean 45 s per axial slice) compared with 15 min (range 6-23 min; mean 88 s per axial slice) for C1. The average volume concordance between C-gold and C-auto volumes was 86.51% compared with 74.16% between C-gold and C-manual. The average volume concordance between C1 and C2 volumes was 86.82%. This newly designed MRI-based auto-contouring software tool shows initial acceptable results in GTV delineation of oropharyngeal and laryngeal tumours using FCLSM. This auto-contouring software tool may help reduce inter- and intra-variability and can assist clinical oncologists with time-consuming, complex radiotherapy planning. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Computerized Liver Volumetry on MRI by Using 3D Geodesic Active Contour Segmentation

PubMed Central

Huynh, Hieu Trung; Karademir, Ibrahim; Oto, Aytekin; Suzuki, Kenji

2014-01-01

OBJECTIVE Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI. SUBJECTS AND METHODS Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard. RESULTS The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance (p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes (p < 0.001). CONCLUSION The MRI liver volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time. PMID:24370139

Body contouring surgery following bariatric surgery and dietetically induced massive weight reduction: a risk analysis.

PubMed

de Kerviler, S; Hüsler, R; Banic, A; Constantinescu, M A

2009-05-01

This study analyzed the impact of weight reduction method, preoperative, and intraoperative variables on the outcome of reconstructive body contouring surgery following massive weight reduction. All patients presenting with a maximal BMI >/=35 kg/m(2) before weight reduction who underwent body contouring surgery of the trunk following massive weight loss (excess body mass index loss (EBMIL) >/= 30%) between January 2002 and June 2007 were retrospectively analyzed. Incomplete records or follow-up led to exclusion. Statistical analysis focused on weight reduction method and pre-, intra-, and postoperative risk factors. The outcome was compared to current literature results. A total of 104 patients were included (87 female and 17 male; mean age 47.9 years). Massive weight reduction was achieved through bariatric surgery in 62 patients (59.6%) and dietetically in 42 patients (40.4%). Dietetically achieved excess body mass index loss (EBMIL) was 94.20% and in this cohort higher than surgically induced reduction EBMIL 80.80% (p < 0.01). Bariatric surgery did not present increased risks for complications for the secondary body contouring procedures. The observed complications (26.9%) were analyzed for risk factors. Total tissue resection weight was a significant risk factor (p < 0.05). Preoperative BMI had an impact on infections (p < 0.05). No impact on the postoperative outcome was detected in EBMIL, maximal BMI, smoking, hemoglobin, blood loss, body contouring technique or operation time. Corrective procedures were performed in 11 patients (10.6%). The results were compared to recent data. Bariatric surgery does not increase risks for complications in subsequent body contouring procedures when compared to massive dietetic weight reduction.

Application and histology-driven refinement of active contour models to functional region and nerve delineation: towards a digital brainstem atlas

NASA Astrophysics Data System (ADS)

Patel, Nirmal; Sultana, Sharmin; Rashid, Tanweer; Krusienski, Dean; Audette, Michel A.

2015-03-01

This paper presents a methodology for the digital formatting of a printed atlas of the brainstem and the delineation of cranial nerves from this digital atlas. It also describes on-going work on the 3D resampling and refinement of the 2D functional regions and nerve contours. In MRI-based anatomical modeling for neurosurgery planning and simulation, the complexity of the functional anatomy entails a digital atlas approach, rather than less descriptive voxel or surface-based approaches. However, there is an insufficiency of descriptive digital atlases, in particular of the brainstem. Our approach proceeds from a series of numbered, contour-based sketches coinciding with slices of the brainstem featuring both closed and open contours. The closed contours coincide with functionally relevant regions, whereby our objective is to fill in each corresponding label, which is analogous to painting numbered regions in a paint-by-numbers kit. Any open contour typically coincides with a cranial nerve. This 2D phase is needed in order to produce densely labeled regions that can be stacked to produce 3D regions, as well as identifying the embedded paths and outer attachment points of cranial nerves. Cranial nerves are modeled using an explicit contour based technique called 1-Simplex. The relevance of cranial nerves modeling of this project is two-fold: i) this atlas will fill a void left by the brain segmentation communities, as no suitable digital atlas of the brainstem exists, and ii) this atlas is necessary to make explicit the attachment points of major nerves (except I and II) having a cranial origin. Keywords: digital atlas, contour models, surface models

A word by any other intonation: fMRI evidence for implicit memory traces for pitch contours of spoken words in adult brains.

PubMed

Inspector, Michael; Manor, David; Amir, Noam; Kushnir, Tamar; Karni, Avi

2013-01-01

Intonation may serve as a cue for facilitated recognition and processing of spoken words and it has been suggested that the pitch contour of spoken words is implicitly remembered. Thus, using the repetition suppression (RS) effect of BOLD-fMRI signals, we tested whether the same spoken words are differentially processed in language and auditory brain areas depending on whether or not they retain an arbitrary intonation pattern. Words were presented repeatedly in three blocks for passive and active listening tasks. There were three prosodic conditions in each of which a different set of words was used and specific task-irrelevant intonation changes were applied: (i) All words presented in a set flat monotonous pitch contour (ii) Each word had an arbitrary pitch contour that was set throughout the three repetitions. (iii) Each word had a different arbitrary pitch contour in each of its repetition. The repeated presentations of words with a set pitch contour, resulted in robust behavioral priming effects as well as in significant RS of the BOLD signals in primary auditory cortex (BA 41), temporal areas (BA 21 22) bilaterally and in Broca's area. However, changing the intonation of the same words on each successive repetition resulted in reduced behavioral priming and the abolition of RS effects. Intonation patterns are retained in memory even when the intonation is task-irrelevant. Implicit memory traces for the pitch contour of spoken words were reflected in facilitated neuronal processing in auditory and language associated areas. Thus, the results lend support for the notion that prosody and specifically pitch contour is strongly associated with the memory representation of spoken words.

A Word by Any Other Intonation: FMRI Evidence for Implicit Memory Traces for Pitch Contours of Spoken Words in Adult Brains

PubMed Central

Inspector, Michael; Manor, David; Amir, Noam; Kushnir, Tamar; Karni, Avi

2013-01-01

Objectives Intonation may serve as a cue for facilitated recognition and processing of spoken words and it has been suggested that the pitch contour of spoken words is implicitly remembered. Thus, using the repetition suppression (RS) effect of BOLD-fMRI signals, we tested whether the same spoken words are differentially processed in language and auditory brain areas depending on whether or not they retain an arbitrary intonation pattern. Experimental design Words were presented repeatedly in three blocks for passive and active listening tasks. There were three prosodic conditions in each of which a different set of words was used and specific task-irrelevant intonation changes were applied: (i) All words presented in a set flat monotonous pitch contour (ii) Each word had an arbitrary pitch contour that was set throughout the three repetitions. (iii) Each word had a different arbitrary pitch contour in each of its repetition. Principal findings The repeated presentations of words with a set pitch contour, resulted in robust behavioral priming effects as well as in significant RS of the BOLD signals in primary auditory cortex (BA 41), temporal areas (BA 21 22) bilaterally and in Broca's area. However, changing the intonation of the same words on each successive repetition resulted in reduced behavioral priming and the abolition of RS effects. Conclusions Intonation patterns are retained in memory even when the intonation is task-irrelevant. Implicit memory traces for the pitch contour of spoken words were reflected in facilitated neuronal processing in auditory and language associated areas. Thus, the results lend support for the notion that prosody and specifically pitch contour is strongly associated with the memory representation of spoken words. PMID:24391713

Level set method for image segmentation based on moment competition

NASA Astrophysics Data System (ADS)

Min, Hai; Wang, Xiao-Feng; Huang, De-Shuang; Jin, Jing; Wang, Hong-Zhi; Li, Hai

2015-05-01

We propose a level set method for image segmentation which introduces the moment competition and weakly supervised information into the energy functional construction. Different from the region-based level set methods which use force competition, the moment competition is adopted to drive the contour evolution. Here, a so-called three-point labeling scheme is proposed to manually label three independent points (weakly supervised information) on the image. Then the intensity differences between the three points and the unlabeled pixels are used to construct the force arms for each image pixel. The corresponding force is generated from the global statistical information of a region-based method and weighted by the force arm. As a result, the moment can be constructed and incorporated into the energy functional to drive the evolving contour to approach the object boundary. In our method, the force arm can take full advantage of the three-point labeling scheme to constrain the moment competition. Additionally, the global statistical information and weakly supervised information are successfully integrated, which makes the proposed method more robust than traditional methods for initial contour placement and parameter setting. Experimental results with performance analysis also show the superiority of the proposed method on segmenting different types of complicated images, such as noisy images, three-phase images, images with intensity inhomogeneity, and texture images.

Automatic liver contouring for radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

Li, Dengwang; Liu, Li; Kapp, Daniel S.; Xing, Lei

2015-09-01

To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems. The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours. The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group are on an average 2.15-2.57%, 2.96-3.23%, and 91.01-97.21% for the CT images with normal appearing livers, 2.28-3.62%, 3.15-4.33%, and 86.14-93.53% for the CT images with hepatocellular carcinoma or liver metastases, and 2.37-3.96%, 3.25-4.57%, and 82.23-89.44% for the 4D-CT images also with hepatocellular carcinoma or liver metastases, respectively. The proposed three-step method can achieve efficient automatic liver contouring for planning CT and 4D-CT images with follow-up treatment planning and should find widespread applications in future treatment planning systems.

A 3D interactive multi-object segmentation tool using local robust statistics driven active contours.

PubMed

Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

2012-08-01

Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: first, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction-this not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. Copyright © 2012 Elsevier B.V. All rights reserved.

A 3D Interactive Multi-object Segmentation Tool using Local Robust Statistics Driven Active Contours

PubMed Central

Gao, Yi; Kikinis, Ron; Bouix, Sylvain; Shenton, Martha; Tannenbaum, Allen

2012-01-01

Extracting anatomical and functional significant structures renders one of the important tasks for both the theoretical study of the medical image analysis, and the clinical and practical community. In the past, much work has been dedicated only to the algorithmic development. Nevertheless, for clinical end users, a well designed algorithm with an interactive software is necessary for an algorithm to be utilized in their daily work. Furthermore, the software would better be open sourced in order to be used and validated by not only the authors but also the entire community. Therefore, the contribution of the present work is twofolds: First, we propose a new robust statistics based conformal metric and the conformal area driven multiple active contour framework, to simultaneously extract multiple targets from MR and CT medical imagery in 3D. Second, an open source graphically interactive 3D segmentation tool based on the aforementioned contour evolution is implemented and is publicly available for end users on multiple platforms. In using this software for the segmentation task, the process is initiated by the user drawn strokes (seeds) in the target region in the image. Then, the local robust statistics are used to describe the object features, and such features are learned adaptively from the seeds under a non-parametric estimation scheme. Subsequently, several active contours evolve simultaneously with their interactions being motivated by the principles of action and reaction — This not only guarantees mutual exclusiveness among the contours, but also no longer relies upon the assumption that the multiple objects fill the entire image domain, which was tacitly or explicitly assumed in many previous works. In doing so, the contours interact and converge to equilibrium at the desired positions of the desired multiple objects. Furthermore, with the aim of not only validating the algorithm and the software, but also demonstrating how the tool is to be used, we provide the reader reproducible experiments that demonstrate the capability of the proposed segmentation tool on several public available data sets. PMID:22831773

ARCOCT: Automatic detection of lumen border in intravascular OCT images.

PubMed

Cheimariotis, Grigorios-Aris; Chatzizisis, Yiannis S; Koutkias, Vassilis G; Toutouzas, Konstantinos; Giannopoulos, Andreas; Riga, Maria; Chouvarda, Ioanna; Antoniadis, Antonios P; Doulaverakis, Charalambos; Tsamboulatidis, Ioannis; Kompatsiaris, Ioannis; Giannoglou, George D; Maglaveras, Nicos

2017-11-01

Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. ARCOCT allows accurate and fully-automated lumen border detection in OCT images. Copyright © 2017 Elsevier B.V. All rights reserved.

Imitative Production of Rising Speech Intonation in Pediatric Cochlear Implant Recipients

PubMed Central

Peng, Shu-Chen; Tomblin, J. Bruce; Spencer, Linda J.; Hurtig, Richard R.

2011-01-01

Purpose This study investigated the acoustic characteristics of pediatric cochlear implant (CI) recipients' imitative production of rising speech intonation, in relation to the perceptual judgments by listeners with normal hearing (NH). Method Recordings of a yes–no interrogative utterance imitated by 24 prelingually deafened children with a CI were extracted from annual evaluation sessions. These utterances were perceptually judged by adult NH listeners in regard with intonation contour type (non-rise, partial-rise, or full-rise) and contour appropriateness (on a 5-point scale). Fundamental frequency, intensity, and duration properties of each utterance were also acoustically analyzed. Results Adult NH listeners' judgments of intonation contour type and contour appropriateness for each CI participant 's utterances were highly positively correlated. The pediatric CI recipients did not consistently use appropriate intonation contours when imitating a yes–no question. Acoustic properties of speech intonation produced by these individuals were discernible among utterances of different intonation contour types according to NH listeners' perceptual judgments. Conclusions These findings delineated the perceptual and acoustic characteristics of speech intonation imitated by prelingually deafened children and young adults with a CI. Future studies should address whether the degraded signals these individuals perceive via a CI contribute to their difficulties with speech intonation production. PMID:17905907

Automated segmentation and dose-volume analysis with DICOMautomaton

NASA Astrophysics Data System (ADS)

Clark, H.; Thomas, S.; Moiseenko, V.; Lee, R.; Gill, B.; Duzenli, C.; Wu, J.

2014-03-01

Purpose: Exploration of historical data for regional organ dose sensitivity is limited by the effort needed to (sub-)segment large numbers of contours. A system has been developed which can rapidly perform autonomous contour sub-segmentation and generic dose-volume computations, substantially reducing the effort required for exploratory analyses. Methods: A contour-centric approach is taken which enables lossless, reversible segmentation and dramatically reduces computation time compared with voxel-centric approaches. Segmentation can be specified on a per-contour, per-organ, or per-patient basis, and can be performed along either an embedded plane or in terms of the contour's bounds (e.g., split organ into fractional-volume/dose pieces along any 3D unit vector). More complex segmentation techniques are available. Anonymized data from 60 head-and-neck cancer patients were used to compare dose-volume computations with Varian's EclipseTM (Varian Medical Systems, Inc.). Results: Mean doses and Dose-volume-histograms computed agree strongly with Varian's EclipseTM. Contours which have been segmented can be injected back into patient data permanently and in a Digital Imaging and Communication in Medicine (DICOM)-conforming manner. Lossless segmentation persists across such injection, and remains fully reversible. Conclusions: DICOMautomaton allows researchers to rapidly, accurately, and autonomously segment large amounts of data into intricate structures suitable for analyses of regional organ dose sensitivity.

Efficient use of mobile devices for quantification of pressure injury images.

PubMed

Garcia-Zapirain, Begonya; Sierra-Sosa, Daniel; Ortiz, David; Isaza-Monsalve, Mariano; Elmaghraby, Adel

2018-01-01

Pressure Injuries are chronic wounds that are formed due to the constriction of the soft tissues against bone prominences. In order to assess these injuries, the medical personnel carry out the evaluation and diagnosis using visual methods and manual measurements, which can be inaccurate and may generate discomfort in the patients. By using segmentation techniques, the Pressure Injuries can be extracted from an image and accurately parameterized, leading to a correct diagnosis. In general, these techniques are based on the solution of differential equations and the involved numerical methods are demanding in terms of computational resources. In previous work, we proposed a technique developed using toroidal parametric equations for image decomposition and segmentation without solving differential equations. In this paper, we present the development of a mobile application useful for the non-contact assessment of Pressure Injuries based on the toroidal decomposition from images. The usage of this technique allows us to achieve an accurate segmentation almost 8 times faster than Active Contours without Edges (ACWE) and Dynamic Contours methods. We describe the techniques and the implementation for Android devices using Python and Kivy. This application allows for the segmentation and parameterization of injuries, obtain relevant information for the diagnosis and tracking the evolution of patient's injuries.

Fast Solvers for Moving Material Interfaces

DTIC Science & Technology

2008-01-01

interface method—with the semi-Lagrangian contouring method developed in References [16–20]. We are now finalizing portable C / C ++ codes for fast adaptive ...stepping scheme couples a CIR predictor with a trapezoidal corrector using the velocity evaluated from the CIR approximation. It combines the...formula with efficient geometric algorithms and fast accurate contouring techniques. A modular adaptive implementation with fast new geometry modules

Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

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

Eckert-Gallup, Aubrey C.; Sallaberry, Cédric J.; Dallman, Ann R.

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s) and either energy period (T e) or peak period (T p) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmentalmore » contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.« less

Application of principal component analysis (PCA) and improved joint probability distributions to the inverse first-order reliability method (I-FORM) for predicting extreme sea states

DOE PAGES

Eckert-Gallup, Aubrey C.; Sallaberry, Cédric J.; Dallman, Ann R.; ...

2016-01-06

Environmental contours describing extreme sea states are generated as the input for numerical or physical model simulations as a part of the standard current practice for designing marine structures to survive extreme sea states. These environmental contours are characterized by combinations of significant wave height (H s) and either energy period (T e) or peak period (T p) values calculated for a given recurrence interval using a set of data based on hindcast simulations or buoy observations over a sufficient period of record. The use of the inverse first-order reliability method (I-FORM) is a standard design practice for generating environmentalmore » contours. This paper develops enhanced methodologies for data analysis prior to the application of the I-FORM, including the use of principal component analysis (PCA) to create an uncorrelated representation of the variables under consideration as well as new distribution and parameter fitting techniques. As a result, these modifications better represent the measured data and, therefore, should contribute to the development of more realistic representations of environmental contours of extreme sea states for determining design loads for marine structures.« less

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

NASA Astrophysics Data System (ADS)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

Method and apparatus for manufacturing high-accuracy radio telescope reflector panels

NASA Astrophysics Data System (ADS)

Bosma, Marinus B.

1998-07-01

This article covers the manufacturing of aluminum reflector panels for submillimeter radio astronomy. The first part involves the general construction and application of a machine custom designed and built to do this. The second is a discussion of the software and execution of method to actually produce the reflectors for the Smithsonian Astrophysical Observatories Submillimeter Array (SMA). The reflective surface of each panel is contoured both radially and circularly by oscillating a platen supporting the panel about a fixed axis relative to a tool which is fixed during platen oscillation. The tool is repositionable between oscillations along an x axis to achieve the radial contour and along a z axis to achieve the desired parabolic or spherical contour. Contrary to the normal contouring of such a surface with a 5- axis CNC machine, tool positioning along either axis is independent of tool location along the other axis, simplifying the machine structure as well as its computerized operation. A unique hinge is provided to restrain the platen in a radial direction while allowing floating action of the platen on an air cushion during its oscillation. These techniques and the equipment are documented in U.S. Patent No. 5477602.

Method of fabricating a flow device

DOEpatents

Hale, Robert L.

1978-01-01

This invention is a novel method for fabricating leak-tight tubular articles which have an interior flow channel whose contour must conform very closely with design specifications but which are composed of metal which tends to warp if welded. The method comprises designing two longitudinal half-sections of the article, the half-sections being contoured internally to cooperatively form the desired flow passageway. Each half-section is designed with a pair of opposed side flanges extending between the end flanges and integral therewith. The half-sections are positioned with their various flanges in confronting relation and with elongated metal gaskets extending between the confronting flanges for the length of the array. The gaskets are a deformable metal which is fusion-weldable to the end flanges. The mating side flanges are joined mechanically to deform the gaskets and provide a longitudinally sealed assembly. The portions of the end flanges contiguous with the ends of the gaskets then are welded to provide localized end welds which incorporate ends of the gaskets, thus transversely sealing the assembly. This method of fabrication provides leak-tight articles having the desired precisely contoured flow channels, whereas various conventional methods have been found unsatisfactory.

Advanced two-layer level set with a soft distance constraint for dual surfaces segmentation in medical images

NASA Astrophysics Data System (ADS)

Ji, Yuanbo; van der Geest, Rob J.; Nazarian, Saman; Lelieveldt, Boudewijn P. F.; Tao, Qian

2018-03-01

Anatomical objects in medical images very often have dual contours or surfaces that are highly correlated. Manually segmenting both of them by following local image details is tedious and subjective. In this study, we proposed a two-layer region-based level set method with a soft distance constraint, which not only regularizes the level set evolution at two levels, but also imposes prior information on wall thickness in an effective manner. By updating the level set function and distance constraint functions alternatingly, the method simultaneously optimizes both contours while regularizing their distance. The method was applied to segment the inner and outer wall of both left atrium (LA) and left ventricle (LV) from MR images, using a rough initialization from inside the blood pool. Compared to manual annotation from experience observers, the proposed method achieved an average perpendicular distance (APD) of less than 1mm for the LA segmentation, and less than 1.5mm for the LV segmentation, at both inner and outer contours. The method can be used as a practical tool for fast and accurate dual wall annotations given proper initialization.

Human body contour data based activity recognition.

PubMed

Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

2013-01-01

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

Impact of region contouring variability on image-based focal therapy evaluation

NASA Astrophysics Data System (ADS)

Gibson, Eli; Donaldson, Ian A.; Shah, Taimur T.; Hu, Yipeng; Ahmed, Hashim U.; Barratt, Dean C.

2016-03-01

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

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

Baumann, Brian C.; Bosch, Walter R.; Bahl, Amit

Purpose: To develop multi-institutional consensus clinical target volumes (CTVs) and organs at risk (OARs) for male and female bladder cancer patients undergoing adjuvant radiation therapy (RT) in clinical trials. Methods and Materials: We convened a multidisciplinary group of bladder cancer specialists from 15 centers and 5 countries. Six radiation oncologists and 7 urologists participated in the development of the initial contours. The group proposed initial language for the CTVs and OARs, and each radiation oncologist contoured them on computed tomography scans of a male and female cystectomy patient with input from ≥1 urologist. On the basis of the initial contouring, themore » group updated its CTV and OAR descriptions. The cystectomy bed, the area of greatest controversy, was contoured by another 6 radiation oncologists, and the cystectomy bed contouring language was again updated. To determine whether the revised language produced consistent contours, CTVs and OARs were redrawn by 6 additional radiation oncologists. We evaluated their contours for level of agreement using the Landis-Koch interpretation of the κ statistic. Results: The group proposed that patients at elevated risk for local-regional failure with negative margins should be treated to the pelvic nodes alone (internal/external iliac, distal common iliac, obturator, and presacral), whereas patients with positive margins should be treated to the pelvic nodes and cystectomy bed. Proposed OARs included the rectum, bowel space, bone marrow, and urinary diversion. Consensus language describing the CTVs and OARs was developed and externally validated. The revised instructions were found to produce consistent contours. Conclusions: Consensus descriptions of CTVs and OARs were successfully developed and can be used in clinical trials of adjuvant radiation therapy for bladder cancer.« less

Consistency in seroma contouring for partial breast radiotherapy: Impact of guidelines

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

Wong, Elaine K.; Truong, Pauline T.; Kader, Hosam A.

2006-10-01

Purpose: Inconsistencies in contouring target structures can undermine the precision of conformal radiation therapy (RT) planning and compromise the validity of clinical trial results. This study evaluated the impact of guidelines on consistency in target volume contouring for partial breast RT planning. Methods and Materials: Guidelines for target volume definition for partial breast radiation therapy (PBRT) planning were developed by members of the steering committee for a pilot trial of PBRT using conformal external beam planning. In phase 1, delineation of the breast seroma in 5 early-stage breast cancer patients was independently performed by a 'trained' cohort of four radiationmore » oncologists who were provided with these guidelines and an 'untrained' cohort of four radiation oncologists who contoured without guidelines. Using automated planning software, the seroma target volume (STV) was expanded into a clinical target volume (CTV) and planning target volume (PTV) for each oncologist. Means and standard deviations were calculated, and two-tailed t tests were used to assess differences between the 'trained' and 'untrained' cohorts. In phase 2, all eight radiation oncologists were provided with the same contouring guidelines, and were asked to delineate the seroma in five new cases. Data were again analyzed to evaluate consistency between the two cohorts. Results: The 'untrained' cohort contoured larger seroma volumes and had larger CTVs and PTVs compared with the 'trained' cohort in three of five cases. When seroma contouring was performed after review of contouring guidelines, the differences in the STVs, CTVs, and PTVs were no longer statistically significant. Conclusion: Guidelines can improve consistency among radiation oncologists performing target volume delineation for PBRT planning.« less

Evaluating the impact of an integrated multidisciplinary head & neck competency-based anatomy & radiology teaching approach in radiation oncology: a prospective cohort study

PubMed Central

2014-01-01

Background Modern radiation oncology demands a thorough understanding of gross and cross-sectional anatomy for diagnostic and therapeutic applications. Complex anatomic sites present challenges for learners and are not well-addressed in traditional postgraduate curricula. A multidisciplinary team (MDT) based head-and-neck gross and radiologic anatomy program for radiation oncology trainees was developed, piloted, and empirically assessed for efficacy and learning outcomes. Methods Four site-specific MDT head-and-neck seminars were implemented, each involving a MDT delivering didactic and case-based instruction, supplemented by cadaveric presentations. There was no dedicated contouring instruction. Pre- and post-testing were performed to assess knowledge, and ability to apply knowledge to the clinical setting as defined by accuracy of contouring. Paired analyses of knowledge pretests and posttests were performed by Wilcoxon matched-pair signed-rank test. Results Fifteen post-graduate trainees participated. A statistically significant (p < 0.001) mean absolute improvement of 4.6 points (17.03%) was observed between knowledge pretest and posttest scores. Contouring accuracy was analyzed quantitatively by comparing spatial overlap of participants’ pretest and posttest contours with a gold standard through the dice similarity coefficient. A statistically significant improvement in contouring accuracy was observed for 3 out of 20 anatomical structures. Qualitative and quantitative feedback revealed that participants were more confident at contouring and were enthusiastic towards the seminars. Conclusions MDT seminars were associated with improved knowledge scores and resident satisfaction; however, increased gross and cross-sectional anatomic knowledge did not translate into improvements in contouring accuracy. Further research should evaluate the impact of hands-on contouring sessions in addition to dedicated instructional sessions to develop competencies. PMID:24969509

Feature selection and definition for contours classification of thermograms in breast cancer detection

NASA Astrophysics Data System (ADS)

Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold; Cichosz, Paweł

2016-09-01

This contribution introduces the method of cancer pathologies detection on breast skin temperature distribution images. The use of thermosensitive foils applied to the breasts skin allows to create thermograms, which displays the amount of infrared energy emitted by all breast cells. The significant foci of hyperthermia or inflammation are typical for cancer cells. That foci can be recognized on thermograms as a contours, which are the areas of higher temperature. Every contour can be converted to a feature set that describe it, using the raw, central, Hu, outline, Fourier and colour moments of image pixels processing. This paper defines also the new way of describing a set of contours through theirs neighbourhood relations. Contribution introduces moreover the way of ranking and selecting most relevant features. Authors used Neural Network with Gevrey`s concept and recursive feature elimination, to estimate feature importance.

Optimization of supersonic axisymmetric nozzles with a center body for aerospace propulsion

NASA Astrophysics Data System (ADS)

Davidenko, D. M.; Eude, Y.; Falempin, F.

2011-10-01

This study is aimed at optimization of axisymmetric nozzles with a center body, which are suitable for thrust engines having an annular duct. To determine the flow conditions and nozzle dimensions, the Vinci rocket engine is chosen as a prototype. The nozzle contours are described by 2nd and 3rd order analytical functions and specified by a set of geometrical parameters. A direct optimization method is used to design maximum thrust nozzle contours. During optimization, the flow of multispecies reactive gas is simulated by an Euler code. Several optimized contours have been obtained for the center body diameter ranging from 0.2 to 0.4 m. For these contours, Navier-Stokes (NS) simulations have been performed to take into account viscous effects assuming adiabatic and cooled wall conditions. The paper presents an analysis of factors influencing the nozzle thrust.

TU-H-CAMPUS-JeP2-03: Machine-Learning-Based Delineation Framework of GTV Regions of Solid and Ground Glass Opacity Lung Tumors at Datasets of Planning CT and PET/CT Images

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

Ikushima, K; Arimura, H; Jin, Z

Purpose: In radiation treatment planning, delineation of gross tumor volume (GTV) is very important, because the GTVs affect the accuracies of radiation therapy procedure. To assist radiation oncologists in the delineation of GTV regions while treatment planning for lung cancer, we have proposed a machine-learning-based delineation framework of GTV regions of solid and ground glass opacity (GGO) lung tumors following by optimum contour selection (OCS) method. Methods: Our basic idea was to feed voxel-based image features around GTV contours determined by radiation oncologists into a machine learning classifier in the training step, after which the classifier produced the degree ofmore » GTV for each voxel in the testing step. Ten data sets of planning CT and PET/CT images were selected for this study. The support vector machine (SVM), which learned voxel-based features which include voxel value and magnitudes of image gradient vector that obtained from each voxel in the planning CT and PET/CT images, extracted initial GTV regions. The final GTV regions were determined using the OCS method that was able to select a global optimum object contour based on multiple active delineations with a level set method around the GTV. To evaluate the results of proposed framework for ten cases (solid:6, GGO:4), we used the three-dimensional Dice similarity coefficient (DSC), which denoted the degree of region similarity between the GTVs delineated by radiation oncologists and the proposed framework. Results: The proposed method achieved an average three-dimensional DSC of 0.81 for ten lung cancer patients, while a standardized uptake value-based method segmented GTV regions with the DSC of 0.43. The average DSCs for solid and GGO were 0.84 and 0.76, respectively, obtained by the proposed framework. Conclusion: The proposed framework with the support vector machine may be useful for assisting radiation oncologists in delineating solid and GGO lung tumors.« less

End-to-end distance and contour length distribution functions of DNA helices

NASA Astrophysics Data System (ADS)

Zoli, Marco

2018-06-01

I present a computational method to evaluate the end-to-end and the contour length distribution functions of short DNA molecules described by a mesoscopic Hamiltonian. The method generates a large statistical ensemble of possible configurations for each dimer in the sequence, selects the global equilibrium twist conformation for the molecule, and determines the average base pair distances along the molecule backbone. Integrating over the base pair radial and angular fluctuations, I derive the room temperature distribution functions as a function of the sequence length. The obtained values for the most probable end-to-end distance and contour length distance, providing a measure of the global molecule size, are used to examine the DNA flexibility at short length scales. It is found that, also in molecules with less than ˜60 base pairs, coiled configurations maintain a large statistical weight and, consistently, the persistence lengths may be much smaller than in kilo-base DNA.

Generation algorithm of craniofacial structure contour in cephalometric images

NASA Astrophysics Data System (ADS)

Mondal, Tanmoy; Jain, Ashish; Sardana, H. K.

2010-02-01

Anatomical structure tracing on cephalograms is a significant way to obtain cephalometric analysis. Computerized cephalometric analysis involves both manual and automatic approaches. The manual approach is limited in accuracy and repeatability. In this paper we have attempted to develop and test a novel method for automatic localization of craniofacial structure based on the detected edges on the region of interest. According to the grey scale feature at the different region of the cephalometric images, an algorithm for obtaining tissue contour is put forward. Using edge detection with specific threshold an improved bidirectional contour tracing approach is proposed by an interactive selection of the starting edge pixels, the tracking process searches repetitively for an edge pixel at the neighborhood of previously searched edge pixel to segment images, and then craniofacial structures are obtained. The effectiveness of the algorithm is demonstrated by the preliminary experimental results obtained with the proposed method.

A hybrid skull-stripping algorithm based on adaptive balloon snake models

NASA Astrophysics Data System (ADS)

Liu, Hung-Ting; Sheu, Tony W. H.; Chang, Herng-Hua

2013-02-01

Skull-stripping is one of the most important preprocessing steps in neuroimage analysis. We proposed a hybrid algorithm based on an adaptive balloon snake model to handle this challenging task. The proposed framework consists of two stages: first, the fuzzy possibilistic c-means (FPCM) is used for voxel clustering, which provides a labeled image for the snake contour initialization. In the second stage, the contour is initialized outside the brain surface based on the FPCM result and evolves under the guidance of the balloon snake model, which drives the contour with an adaptive inward normal force to capture the boundary of the brain. The similarity indices indicate that our method outperformed the BSE and BET methods in skull-stripping the MR image volumes in the IBSR data set. Experimental results show the effectiveness of this new scheme and potential applications in a wide variety of skull-stripping applications.

3D reconstruction of microminiature objects based on contour line

NASA Astrophysics Data System (ADS)

Li, Cailin; Wang, Qiang; Guo, Baoyun

2009-10-01

A new 3D automatic reconstruction method of micro solid of revolution is presented in this paper. In the implementation procedure of this method, image sequence of the solid of revolution of 360° is obtained, which rotation speed is controlled by motor precisely, in the rotate photographic mode of back light. Firstly, we need calibrate the height of turntable, the size of pixel and rotation axis of turntable. Then according to the calibration result of rotation axis, the height of turntable, rotation angle and the pixel size, the contour points of each image can be transformed into 3D points in the reference coordinate system to generate the point cloud model. Finally, the surface geometrical model of solid of revolution is obtained by using the relationship of two adjacent contours. Experimental results on real images are presented, which demonstrate the effectiveness of the Approach.

3D contour fluorescence spectroscopy with Brus model: Determination of size and band gap of double stranded DNA templated silver nanoclusters

NASA Astrophysics Data System (ADS)

Kamalraj, Devaraj; Yuvaraj, Selvaraj; Yoganand, Coimbatore Paramasivam; Jaffer, Syed S.

2018-01-01

Here, we propose a new synthetic methodology for silver nanocluster preparation by using a double stranded-DNA (ds-DNA) template which no one has reported yet. A new calculative method was formulated to determine the size of the nanocluster and their band gaps by using steady state 3D contour fluorescence technique with Brus model. Generally, the structure and size of the nanoclusters determine by using High Resolution Transmission Electron Microscopy (HR-TEM). Before imaging the samples by using HR-TEM, they are introduced to drying process which causes aggregation and forms bigger polycrystalline particles. It takes long time duration and expensive methodology. In this current methodology, we found out the size and band gap of the nanocluster in the liquid form without any polycrystalline aggregation for which 3D contour fluorescence technique was used as an alternative approach to the HR-TEM method.

Automated contouring error detection based on supervised geometric attribute distribution models for radiation therapy: A general strategy

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

Chen, Hsin-Chen; Tan, Jun; Dolly, Steven

2015-02-15

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy basedmore » on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets were separately employed to test the effectiveness of the proposed contouring error detection strategy. Results: An evaluation tool was implemented to illustrate how the proposed strategy automatically detects the radiation therapy contouring errors for a given patient and provides 3D graphical visualization of error detection results as well. The contouring error detection results were achieved with an average sensitivity of 0.954/0.906 and an average specificity of 0.901/0.909 on the centroid/volume related contouring errors of all the tested samples. As for the detection results on structural shape related contouring errors, an average sensitivity of 0.816 and an average specificity of 0.94 on all the tested samples were obtained. The promising results indicated the feasibility of the proposed strategy for the detection of contouring errors with low false detection rate. Conclusions: The proposed strategy can reliably identify contouring errors based upon inter- and intrastructural constraints derived from clinically approved contours. It holds great potential for improving the radiation therapy workflow. ROC and box plot analyses allow for analytically tuning of the system parameters to satisfy clinical requirements. Future work will focus on the improvement of strategy reliability by utilizing more training sets and additional geometric attribute constraints.« less

Analytical solutions for determining residual stresses in two-dimensional domains using the contour method

PubMed Central

Kartal, Mehmet E.

2013-01-01

The contour method is one of the most prevalent destructive techniques for residual stress measurement. Up to now, the method has involved the use of the finite-element (FE) method to determine the residual stresses from the experimental measurements. This paper presents analytical solutions, obtained for a semi-infinite strip and a finite rectangle, which can be used to calculate the residual stresses directly from the measured data; thereby, eliminating the need for an FE approach. The technique is then used to determine the residual stresses in a variable-polarity plasma-arc welded plate and the results show good agreement with independent neutron diffraction measurements. PMID:24204187

Consensus Contouring Guidelines for Postoperative Stereotactic Body Radiation Therapy for Metastatic Solid Tumor Malignancies to the Spine

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

Redmond, Kristin J., E-mail: kjanson3@jhmi.edu; Robertson, Scott; Lo, Simon S.

Purpose: To develop consensus contouring guidelines for postoperative stereotactic body radiation therapy (SBRT) for spinal metastases. Methods and Materials: Ten spine SBRT specialists representing 10 international centers independently contoured the clinical target volume (CTV), planning target volume (PTV), spinal cord, and spinal cord planning organ at risk volume (PRV) for 10 representative clinical scenarios in postoperative spine SBRT for metastatic solid tumor malignancies. Contours were imported into the Computational Environment for Radiotherapy Research. Agreement between physicians was calculated with an expectation minimization algorithm using simultaneous truth and performance level estimation with κ statistics. Target volume definition guidelines were established by finding optimizedmore » confidence level consensus contours using histogram agreement analyses. Results: Nine expert radiation oncologists and 1 neurosurgeon completed contours for all 10 cases. The mean sensitivity and specificity were 0.79 (range, 0.71-0.89) and 0.94 (range, 0.90-0.99) for the CTV and 0.79 (range, 0.70-0.95) and 0.92 (range, 0.87-0.99) for the PTV), respectively. Mean κ agreement, which demonstrates the probability that contours agree by chance alone, was 0.58 (range, 0.43-0.70) for CTV and 0.58 (range, 0.37-0.76) for PTV (P<.001 for all cases). Optimized consensus contours were established for all patients with 80% confidence interval. Recommendations for CTV include treatment of the entire preoperative extent of bony and epidural disease, plus immediately adjacent bony anatomic compartments at risk of microscopic disease extension. In particular, a “donut-shaped” CTV was consistently applied in cases of preoperative circumferential epidural extension, regardless of extent of residual epidural extension. Otherwise more conformal anatomic-based CTVs were determined and described. Spinal instrumentation was consistently excluded from the CTV. Conclusions: We provide consensus contouring guidelines for common scenarios in postoperative SBRT for spinal metastases. These consensus guidelines are subject to clinical validation.« less

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

D’Souza, W; Zhang, B; Feigenberg, S

Purpose: To evaluate the compliance with evidence-based treatment planning organ-at-risk (OAR) guidelines in a single institution with four practice sites. Methods: Two hundred thirteen head and neck cancer patients treated between September 2009 and September 2013 were retrospectively selected. Consensus treatment planning guidelines, including OAR dose constraints, were established based on institutional experience and published data. Data spanned a time period of 2 years prior to (n=112) and 2 years post-enactment (n=101) of the guidelines. We investigated the differences in the frequency with which (1) OARs were contoured and (2) OAR DVH goals were met. Trends in the proportion withmore » OAR contours over time was tested using linear regression. Trends in the proportion of contoured OARs achieving clinical DVH goals were similarly tested. The proportion of patients contoured and meeting DVH goals before and after guidelines was compared using a test of proportions. Results: When the proportion of cases with OAR contours before and after guidelines were compared, we observed an increase from 75% to 87% (p=0.02) for the brainstem, decrease from 97% to 88% (p=0.01) for the cord and increase from 47% to 77% (p<0.001) for the mandible. For the proportion of cases with OAR contours in which clinical goals were met, a significant decrease from 99% to 90% was observed for the cord V48<0.3% (p=0.001). A significant decrease in the proportion of cases with left parotid contours (from 92% to 73% (p=0.03)) was observed over 2 years after guideline enactment and the proportion meeting the clinical DVH goal of V30<50% increased significantly from 36% to 50% (p=0.007) over the 2 years after guidelines. Conclusion: The enactment of OAR planning guidelines resulted in an increase in OAR contour compliance, overall. In cases with OAR contours, there was little to no change in the proportion that met clinical goals.« less

SU-F-T-455: Is Contouring the Whole Breast Necessary for Two-Field 3D Breast Planning?

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

Desai, A; Ku, Eric; Fang, D

Purpose: To investigate the effect of contouring the whole breast on reducing the radiation dose to the heart and affected lung in tangential field-in-field 3D breast planning. We hypothesize that contouring the whole breast will simplify the plan normalization process, reduce dose to critical structures, while maintaining treatment plan quality and consistency. Methods: Twenty previously treated breast cancer patients using tangential field-in-field 3D planning technique were randomly selected. The affected breast was contoured following the RTOG breast atlas guideline. Breast PTV was created by shrinking 5 mm from the breast contour. The same plan has been pasted to the newmore » contour and normalized to 95% of the Breast PTV receiving the prescribed isodose line. Lung V20 Gy% and Heart V25 Gy% were the primary study endpoints. Homogeneity Index (HI) and Conformity Index (CI) were calculated based on the following equations. HI= Dmax/ D95 and Nakamura’s Conformity Index= PIV/TVPIV × TV/TVPIV. Results: The average CI for previous plans was 1.68 vs. 1.66 for the new hybrid plan: both plans were conformal to the breast with similar quality. The HI for both the previous and the new hybrid plan was 1.24. Lung V 20% slightly increased from 4.27% to 4.82%. Heart V 25% for LT breast patients slightly decreased from 0.38% to 0.29%. Heart V 25% for RT breast patients was close to zero in both cases. Conclusion: With similar conformal and homogeneity indices for the plan quality, by contouring the whole breast following RTOG breast atlas guideline will simplify the planning process. The study showed that contouring the whole breast for patients with left-sided breast cancer reduced the heart V 25%, although not significantly, while maintaining the CI and HI. There was no measurable gain seen with whole breast contour for right-sided breast cancer patients.« less

Automated segmentation of blood-flow regions in large thoracic arteries using 3D-cine PC-MRI measurements.

PubMed

van Pelt, Roy; Nguyen, Huy; ter Haar Romeny, Bart; Vilanova, Anna

2012-03-01

Quantitative analysis of vascular blood flow, acquired by phase-contrast MRI, requires accurate segmentation of the vessel lumen. In clinical practice, 2D-cine velocity-encoded slices are inspected, and the lumen is segmented manually. However, segmentation of time-resolved volumetric blood-flow measurements is a tedious and time-consuming task requiring automation. Automated segmentation of large thoracic arteries, based solely on the 3D-cine phase-contrast MRI (PC-MRI) blood-flow data, was done. An active surface model, which is fast and topologically stable, was used. The active surface model requires an initial surface, approximating the desired segmentation. A method to generate this surface was developed based on a voxel-wise temporal maximum of blood-flow velocities. The active surface model balances forces, based on the surface structure and image features derived from the blood-flow data. The segmentation results were validated using volunteer studies, including time-resolved 3D and 2D blood-flow data. The segmented surface was intersected with a velocity-encoded PC-MRI slice, resulting in a cross-sectional contour of the lumen. These cross-sections were compared to reference contours that were manually delineated on high-resolution 2D-cine slices. The automated approach closely approximates the manual blood-flow segmentations, with error distances on the order of the voxel size. The initial surface provides a close approximation of the desired luminal geometry. This improves the convergence time of the active surface and facilitates parametrization. An active surface approach for vessel lumen segmentation was developed, suitable for quantitative analysis of 3D-cine PC-MRI blood-flow data. As opposed to prior thresholding and level-set approaches, the active surface model is topologically stable. A method to generate an initial approximate surface was developed, and various features that influence the segmentation model were evaluated. The active surface segmentation results were shown to closely approximate manual segmentations.

Common Visual Preference for Curved Contours in Humans and Great Apes.

PubMed

Munar, Enric; Gómez-Puerto, Gerardo; Call, Josep; Nadal, Marcos

2015-01-01

Among the visual preferences that guide many everyday activities and decisions, from consumer choices to social judgment, preference for curved over sharp-angled contours is commonly thought to have played an adaptive role throughout human evolution, favoring the avoidance of potentially harmful objects. However, because nonhuman primates also exhibit preferences for certain visual qualities, it is conceivable that humans' preference for curved contours is grounded on perceptual and cognitive mechanisms shared with extant nonhuman primate species. Here we aimed to determine whether nonhuman great apes and humans share a visual preference for curved over sharp-angled contours using a 2-alternative forced choice experimental paradigm under comparable conditions. Our results revealed that the human group and the great ape group indeed share a common preference for curved over sharp-angled contours, but that they differ in the manner and magnitude with which this preference is expressed behaviorally. These results suggest that humans' visual preference for curved objects evolved from earlier primate species' visual preferences, and that during this process it became stronger, but also more susceptible to the influence of higher cognitive processes and preference for other visual features.

Anatomy structure creation and editing using 3D implicit surfaces

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

Hibbard, Lyndon S.

2012-05-15

Purpose: To accurately reconstruct, and interactively reshape 3D anatomy structures' surfaces using small numbers of 2D contours drawn in the most visually informative views of 3D imagery. The innovation of this program is that the number of 2D contours can be very much smaller than the number of transverse sections, even for anatomy structures spanning many sections. This program can edit 3D structures from prior segmentations, including those from autosegmentation programs. The reconstruction and surface editing works with any image modality. Methods: Structures are represented by variational implicit surfaces defined by weighted sums of radial basis functions (RBFs). Such surfacesmore » are smooth, continuous, and closed and can be reconstructed with RBFs optimally located to efficiently capture shape in any combination of transverse (T), sagittal (S), and coronal (C) views. The accuracy of implicit surface reconstructions was measured by comparisons with the corresponding expert-contoured surfaces in 103 prostate cancer radiotherapy plans. Editing a pre-existing surface is done by overdrawing its profiles in image views spanning the affected part of the structure, deleting an appropriate set of prior RBFs, and merging the remainder with the new edit contour RBFs. Two methods were devised to identify RBFs to be deleted based only on the geometry of the initial surface and the locations of the new RBFs. Results: Expert-contoured surfaces were compared with implicit surfaces reconstructed from them over varying numbers and combinations of T/S/C planes. Studies revealed that surface-surface agreement increases monotonically with increasing RBF-sample density, and that the rate of increase declines over the same range. These trends were observed for all surface agreement metrics and for all the organs studied--prostate, bladder, and rectum. In addition, S and C contours may convey more shape information than T views for CT studies in which the axial slice thickness is greater than the pixel size. Surface editing accuracy likewise improves with larger sampling densities, and the rate of improvement similarly declines over the same conditions. Conclusions: Implicit surfaces based on RBFs are accurate representations of anatomic structures and can be interactively generated or modified to correct segmentation errors. The number of input contours is typically smaller than the number of T contours spanned by the structure.« less

WE-G-BRD-07: Automated MR Image Standardization and Auto-Contouring Strategy for MRI-Based Adaptive Brachytherapy for Cervix Cancer

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

Saleh, H Al; Erickson, B; Paulson, E

Purpose: MRI-based adaptive brachytherapy (ABT) is an emerging treatment modality for patients with gynecological tumors. However, MR image intensity non-uniformities (IINU) can vary from fraction to fraction, complicating image interpretation and auto-contouring accuracy. We demonstrate here an automated MR image standardization and auto-contouring strategy for MRI-based ABT of cervix cancer. Methods: MR image standardization consisted of: 1) IINU correction using the MNI N3 algorithm, 2) noise filtering using anisotropic diffusion, and 3) signal intensity normalization using the volumetric median. This post-processing chain was implemented as a series of custom Matlab and Java extensions in MIM (v6.4.5, MIM Software) and wasmore » applied to 3D T2 SPACE images of six patients undergoing MRI-based ABT at 3T. Coefficients of variation (CV=σ/µ) were calculated for both original and standardized images and compared using Mann-Whitney tests. Patient-specific cumulative MR atlases of bladder, rectum, and sigmoid contours were constructed throughout ABT, using original and standardized MR images from all previous ABT fractions. Auto-contouring was performed in MIM two ways: 1) best-match of one atlas image to the daily MR image, 2) multi-match of all previous fraction atlas images to the daily MR image. Dice’s Similarity Coefficients (DSCs) were calculated for auto-generated contours relative to reference contours for both original and standardized MR images and compared using Mann-Whitney tests. Results: Significant improvements in CV were detected following MR image standardization (p=0.0043), demonstrating an improvement in MR image uniformity. DSCs consistently increased for auto-contoured bladder, rectum, and sigmoid following MR image standardization, with the highest DSCs detected when the combination of MR image standardization and multi-match cumulative atlas-based auto-contouring was utilized. Conclusion: MR image standardization significantly improves MR image uniformity. The combination of MR image standardization and multi-match cumulative atlas-based auto-contouring produced the highest DSCs and is a promising strategy for MRI-based ABT for cervix cancer.« less

Molar axis estimation from computed tomography images.

PubMed

Dongxia Zhang; Yangzhou Gan; Zeyang Xia; Xinwen Zhou; Shoubin Liu; Jing Xiong; Guanglin Li

2016-08-01

Estimation of tooth axis is needed for some clinical dental treatment. Existing methods require to segment the tooth volume from Computed Tomography (CT) images, and then estimate the axis from the tooth volume. However, they may fail during estimating molar axis due to that the tooth segmentation from CT images is challenging and current segmentation methods may get poor segmentation results especially for these molars with angle which will result in the failure of axis estimation. To resolve this problem, this paper proposes a new method for molar axis estimation from CT images. The key innovation point is that: instead of estimating the 3D axis of each molar from the segmented volume, the method estimates the 3D axis from two projection images. The method includes three steps. (1) The 3D images of each molar are projected to two 2D image planes. (2) The molar contour are segmented and the contour's 2D axis are extracted in each 2D projection image. Principal Component Analysis (PCA) and a modified symmetry axis detection algorithm are employed to extract the 2D axis from the segmented molar contour. (3) A 3D molar axis is obtained by combining the two 2D axes. Experimental results verified that the proposed method was effective to estimate the axis of molar from CT images.

An adipose segmentation and quantification scheme for the intra abdominal region on minipigs

NASA Astrophysics Data System (ADS)

Engholm, Rasmus; Dubinskiy, Aleksandr; Larsen, Rasmus; Hanson, Lars G.; Christoffersen, Berit Østergaard

2006-03-01

This article describes a method for automatic segmentation of the abdomen into three anatomical regions: subcutaneous, retroperitoneal and visceral. For the last two regions the amount of adipose tissue (fat) is quantified. According to recent medical research, the distinction between retroperitoneal and visceral fat is important for studying metabolic syndrome, which is closely related to diabetes. However previous work has neglected to address this point, treating the two types of fat together. We use T1-weighted three-dimensional magnetic resonance data of the abdomen of obese minipigs. The pigs were manually dissected right after the scan, to produce the "ground truth" segmentation. We perform automatic segmentation on a representative slice, which on humans has been shown to correlate with the amount of adipose tissue in the abdomen. The process of automatic fat estimation consists of three steps. First, the subcutaneous fat is removed with a modified active contour approach. The energy formulation of the active contour exploits the homogeneous nature of the subcutaneous fat and the smoothness of the boundary. Subsequently the retroperitoneal fat located around the abdominal cavity is separated from the visceral fat. For this, we formulate a cost function on a contour, based on intensities, edges, distance to center and smoothness, so as to exploit the properties of the retroperitoneal fat. We then globally optimize this function using dynamic programming. Finally, the fat content of the retroperitoneal and visceral regions is quantified based on a fuzzy c-means clustering of the intensities within the segmented regions. The segmentation proved satisfactory by visual inspection, and closely correlated with the manual dissection data. The correlation was 0.89 for the retroperitoneal fat, and 0.74 for the visceral fat.

Localized Statistics for DW-MRI Fiber Bundle Segmentation

PubMed Central

Lankton, Shawn; Melonakos, John; Malcolm, James; Dambreville, Samuel; Tannenbaum, Allen

2013-01-01

We describe a method for segmenting neural fiber bundles in diffusion-weighted magnetic resonance images (DWMRI). As these bundles traverse the brain to connect regions, their local orientation of diffusion changes drastically, hence a constant global model is inaccurate. We propose a method to compute localized statistics on orientation information and use it to drive a variational active contour segmentation that accurately models the non-homogeneous orientation information present along the bundle. Initialized from a single fiber path, the proposed method proceeds to capture the entire bundle. We demonstrate results using the technique to segment the cingulum bundle and describe several extensions making the technique applicable to a wide range of tissues. PMID:23652079

Innovative design method of automobile profile based on Fourier descriptor

NASA Astrophysics Data System (ADS)

Gao, Shuyong; Fu, Chaoxing; Xia, Fan; Shen, Wei

2017-10-01

Aiming at the innovation of the contours of automobile side, this paper presents an innovative design method of vehicle side profile based on Fourier descriptor. The design flow of this design method is: pre-processing, coordinate extraction, standardization, discrete Fourier transform, simplified Fourier descriptor, exchange descriptor innovation, inverse Fourier transform to get the outline of innovative design. Innovative concepts of the innovative methods of gene exchange among species and the innovative methods of gene exchange among different species are presented, and the contours of the innovative design are obtained separately. A three-dimensional model of a car is obtained by referring to the profile curve which is obtained by exchanging xenogeneic genes. The feasibility of the method proposed in this paper is verified by various aspects.

SU-E-J-208: Fast and Accurate Auto-Segmentation of Abdominal Organs at Risk for Online Adaptive Radiotherapy

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

Gupta, V; Wang, Y; Romero, A

2014-06-01

Purpose: Various studies have demonstrated that online adaptive radiotherapy by real-time re-optimization of the treatment plan can improve organs-at-risk (OARs) sparing in the abdominal region. Its clinical implementation, however, requires fast and accurate auto-segmentation of OARs in CT scans acquired just before each treatment fraction. Autosegmentation is particularly challenging in the abdominal region due to the frequently observed large deformations. We present a clinical validation of a new auto-segmentation method that uses fully automated non-rigid registration for propagating abdominal OAR contours from planning to daily treatment CT scans. Methods: OARs were manually contoured by an expert panel to obtain groundmore » truth contours for repeat CT scans (3 per patient) of 10 patients. For the non-rigid alignment, we used a new non-rigid registration method that estimates the deformation field by optimizing local normalized correlation coefficient with smoothness regularization. This field was used to propagate planning contours to repeat CTs. To quantify the performance of the auto-segmentation, we compared the propagated and ground truth contours using two widely used metrics- Dice coefficient (Dc) and Hausdorff distance (Hd). The proposed method was benchmarked against translation and rigid alignment based auto-segmentation. Results: For all organs, the auto-segmentation performed better than the baseline (translation) with an average processing time of 15 s per fraction CT. The overall improvements ranged from 2% (heart) to 32% (pancreas) in Dc, and 27% (heart) to 62% (spinal cord) in Hd. For liver, kidneys, gall bladder, stomach, spinal cord and heart, Dc above 0.85 was achieved. Duodenum and pancreas were the most challenging organs with both showing relatively larger spreads and medians of 0.79 and 2.1 mm for Dc and Hd, respectively. Conclusion: Based on the achieved accuracy and computational time we conclude that the investigated auto-segmentation method overcomes an important hurdle to the clinical implementation of online adaptive radiotherapy. Partial funding for this work was provided by Accuray Incorporated as part of a research collaboration with Erasmus MC Cancer Institute.« less

Conventional 3D staging PET/CT in CT simulation for lung cancer: impact of rigid and deformable target volume alignments for radiotherapy treatment planning.

PubMed

Hanna, G G; Van Sörnsen De Koste, J R; Carson, K J; O'Sullivan, J M; Hounsell, A R; Senan, S

2011-10-01

Positron emission tomography (PET)/CT scans can improve target definition in radiotherapy for non-small cell lung cancer (NSCLC). As staging PET/CT scans are increasingly available, we evaluated different methods for co-registration of staging PET/CT data to radiotherapy simulation (RTP) scans. 10 patients underwent staging PET/CT followed by RTP PET/CT. On both scans, gross tumour volumes (GTVs) were delineated using CT (GTV(CT)) and PET display settings. Four PET-based contours (manual delineation, two threshold methods and a source-to-background ratio method) were delineated. The CT component of the staging scan was co-registered using both rigid and deformable techniques to the CT component of RTP PET/CT. Subsequently rigid registration and deformation warps were used to transfer PET and CT contours from the staging scan to the RTP scan. Dice's similarity coefficient (DSC) was used to assess the registration accuracy of staging-based GTVs following both registration methods with the GTVs delineated on the RTP PET/CT scan. When the GTV(CT) delineated on the staging scan after both rigid registration and deformation was compared with the GTV(CT)on the RTP scan, a significant improvement in overlap (registration) using deformation was observed (mean DSC 0.66 for rigid registration and 0.82 for deformable registration, p = 0.008). A similar comparison for PET contours revealed no significant improvement in overlap with the use of deformable registration. No consistent improvements in similarity measures were observed when deformable registration was used for transferring PET-based contours from a staging PET/CT. This suggests that currently the use of rigid registration remains the most appropriate method for RTP in NSCLC.

SU-F-J-97: A Joint Registration and Segmentation Approach for Large Bladder Deformations in Adaptive Radiotherapy

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

Derksen, A; Koenig, L; Heldmann, S

Purpose: To improve results of deformable image registration (DIR) in adaptive radiotherapy for large bladder deformations in CT/CBCT pelvis imaging. Methods: A variational multi-modal DIR algorithm is incorporated in a joint iterative scheme, alternating between segmentation based bladder matching and registration. Using an initial DIR to propagate the bladder contour to the CBCT, in a segmentation step the contour is improved by discrete image gradient sampling along all surface normals and adapting the delineation to match the location of each maximum (with a search range of +−5/2mm at the superior/inferior bladder side and step size of 0.5mm). An additional graph-cutmore » based constraint limits the maximum difference between neighboring points. This improved contour is utilized in a subsequent DIR with a surface matching constraint. By calculating an euclidean distance map of the improved contour surface, the new constraint enforces the DIR to map each point of the original contour onto the improved contour. The resulting deformation is then used as a starting guess to compute a deformation update, which can again be used for the next segmentation step. The result is a dense deformation, able to capture much larger bladder deformations. The new method is evaluated on ten CT/CBCT male pelvis datasets, calculating Dice similarity coefficients (DSC) between the final propagated bladder contour and a manually delineated gold standard on the CBCT image. Results: Over all ten cases, an average DSC of 0.93±0.03 is achieved on the bladder. Compared with the initial DIR (0.88±0.05), the DSC is equal (2 cases) or improved (8 cases). Additionally, DSC accuracy of femoral bones (0.94±0.02) was not affected. Conclusion: The new approach shows that using the presented alternating segmentation/registration approach, the results of bladder DIR in the pelvis region can be greatly improved, especially for cases with large variations in bladder volume. Fraunhofer MEVIS received funding from a research grant by Varian Medical Systems.« less

ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery.

PubMed

Partl, Christian; Lex, Alexander; Streit, Marc; Strobelt, Hendrik; Wassermann, Anne-Mai; Pfister, Hanspeter; Schmalstieg, Dieter

2014-12-01

Large scale data analysis is nowadays a crucial part of drug discovery. Biologists and chemists need to quickly explore and evaluate potentially effective yet safe compounds based on many datasets that are in relationship with each other. However, there is a lack of tools that support them in these processes. To remedy this, we developed ConTour, an interactive visual analytics technique that enables the exploration of these complex, multi-relational datasets. At its core ConTour lists all items of each dataset in a column. Relationships between the columns are revealed through interaction: selecting one or multiple items in one column highlights and re-sorts the items in other columns. Filters based on relationships enable drilling down into the large data space. To identify interesting items in the first place, ConTour employs advanced sorting strategies, including strategies based on connectivity strength and uniqueness, as well as sorting based on item attributes. ConTour also introduces interactive nesting of columns, a powerful method to show the related items of a child column for each item in the parent column. Within the columns, ConTour shows rich attribute data about the items as well as information about the connection strengths to other datasets. Finally, ConTour provides a number of detail views, which can show items from multiple datasets and their associated data at the same time. We demonstrate the utility of our system in case studies conducted with a team of chemical biologists, who investigate the effects of chemical compounds on cells and need to understand the underlying mechanisms.

Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25

NASA Technical Reports Server (NTRS)

Burke, Christopher J.; Catanzarite, Joseph

2017-01-01

A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

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

Gong, G; Liu, C; Liu, C

Purpose: To analyze the error in contouring the brainstem for patients with head and neck cancer who underwent radiotherapy based on computed tomography (CT) and magnetic resonance (MR) images. Methods: 20 brain tumor and 17 nasopharyngeal cancer patients were randomly selected. Each patient underwent MR and CT scanning. For each patient, one observer contoured the brainstem on CT and MR images for 10 times, and 10 observers from five centers delineated the brainstem on CT and MR images only one time. The inter- and intra-observers volume and outline variations were compared. Results: The volumes of brainstem contoured by inter- andmore » intra-observers on CT and MR images were similar (p>0.05). The reproducibility of contouring brainstem on MR images was better than that on CT images (p<0.05) for both inter- and intra-observer variability. The inter- and intra-observer for contouring on CT images reached mean values of 0.81±0.05 (p>0.05) and of 0.85±0.05 (p>0.05), respectively, while on MR images these respective values were 0.90±0.05 (p>0.05) and 0.92±0.04 (p>0.05). Conclusion: Contouring the brainstem on MR images was more accurate and reproducible than that on CT images. Precise information might be more helpful for protecting the brainstem radiation injury the patients whose lesion were closed to brainstem.« less

Accuracy of Cardiac Output by Nine Different Pulse Contour Algorithms in Cardiac Surgery Patients: A Comparison with Transpulmonary Thermodilution.

PubMed

Broch, Ole; Bein, Berthold; Gruenewald, Matthias; Masing, Sarah; Huenges, Katharina; Haneya, Assad; Steinfath, Markus; Renner, Jochen

2016-01-01

Objective. Today, there exist several different pulse contour algorithms for calculation of cardiac output (CO). The aim of the present study was to compare the accuracy of nine different pulse contour algorithms with transpulmonary thermodilution before and after cardiopulmonary bypass (CPB). Methods. Thirty patients scheduled for elective coronary surgery were studied before and after CPB. A passive leg raising maneuver was also performed. Measurements included CO obtained by transpulmonary thermodilution (CO TPTD ) and by nine pulse contour algorithms (CO X1-9 ). Calibration of pulse contour algorithms was performed by esophageal Doppler ultrasound after induction of anesthesia and 15 min after CPB. Correlations, Bland-Altman analysis, four-quadrant, and polar analysis were also calculated. Results. There was only a poor correlation between CO TPTD and CO X1-9 during passive leg raising and in the period before and after CPB. Percentage error exceeded the required 30% limit. Four-quadrant and polar analysis revealed poor trending ability for most algorithms before and after CPB. The Liljestrand-Zander algorithm revealed the best reliability. Conclusions. Estimation of CO by nine different pulse contour algorithms revealed poor accuracy compared with transpulmonary thermodilution. Furthermore, the less-invasive algorithms showed an insufficient capability for trending hemodynamic changes before and after CPB. The Liljestrand-Zander algorithm demonstrated the highest reliability. This trial is registered with NCT02438228 (ClinicalTrials.gov).

The Noisiness of Low Frequency Bands of Noise

NASA Technical Reports Server (NTRS)

Lawton, B. W.

1975-01-01

The relative noisiness of low frequency 1/3-octave bands of noise was examined. The frequency range investigated was bounded by the bands centered at 25 and 200 Hz, with intensities ranging from 50 to 95 db (SPL). Thirty-two subjects used a method of adjustment technique, producing comparison band intensities as noisy as 100 and 200 Hz standard bands at 60 and 72 db. The work resulted in contours of equal noisiness for 1/3-octave bands, ranging in intensity from approximately 58 to 86 db (SPL). These contours were compared with the standard equal noisiness contours; in the region of overlap, between 50 and 200 Hz, the agreement was good.

Design equations for the assessment and FRP-strengthening of reinforced rectangular concrete columns under combined biaxial bending and axial loads

NASA Astrophysics Data System (ADS)

Alessandri, S.; Monti, G.

2008-05-01

A simple procedure is proposed for the assessment of reinforced rectangular concrete columns under combined biaxial bending and axial loads and for the design of a correct amount of FRP-strengthening for underdesigned concrete sections. Approximate closed-form equations are developed based on the load contour method originally proposed by Bresler for reinforced concrete sections. The 3D failure surface is approximated along its contours, at a constant axial load, by means of equations given as the sum of the acting/resisting moment ratio in the directions of principal axes of the sections, raised to a power depending on the axial load, the steel reinforcement ratio, and the section shape. The method is extended to FRP-strengthened sections. Moreover, to make it possible to apply the load contour method in a more practical way, simple closed-form equations are developed for rectangular reinforced concrete sections with a two-way steel reinforcement and FRP strengthenings on each side. A comparison between the approach proposed and the fiber method (which is considered exact) shows that the simplified equations correctly represent the section interaction diagram.

Eyelid contour detection and tracking for startle research related eye-blink measurements from high-speed video records.

PubMed

Bernard, Florian; Deuter, Christian Eric; Gemmar, Peter; Schachinger, Hartmut

2013-10-01

Using the positions of the eyelids is an effective and contact-free way for the measurement of startle induced eye-blinks, which plays an important role in human psychophysiological research. To the best of our knowledge, no methods for an efficient detection and tracking of the exact eyelid contours in image sequences captured at high-speed exist that are conveniently usable by psychophysiological researchers. In this publication a semi-automatic model-based eyelid contour detection and tracking algorithm for the analysis of high-speed video recordings from an eye tracker is presented. As a large number of images have been acquired prior to method development it was important that our technique is able to deal with images that are recorded without any special parametrisation of the eye tracker. The method entails pupil detection, specular reflection removal and makes use of dynamic model adaption. In a proof-of-concept study we could achieve a correct detection rate of 90.6%. With this approach, we provide a feasible method to accurately assess eye-blinks from high-speed video recordings. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Staged marginal contoured and central excision technique in the surgical management of perianal Paget's disease.

PubMed

Möller, Mecker G; Lugo-Baruqui, Jose Alejandro; Milikowski, Clara; Salgado, Christopher J

2014-04-01

Extramammary Paget's disease (EMPD) is an adenocarcinoma of the apocrine glands with unknown exact prevalence and obscure etiology. It has been divided into primary EMPD and secondary EMPD, in which an internal malignancy is usually associated. Treatment for primary EMPD usually consists of wide lesion excision with negative margins. Multiple methods have been proposed to obtain free-margin status of the disease. These include visible border lesion excision, punch biopsies, and micrographic and frozen-section surgery, with different results but still high recurrence rates. The investigators propose a method consisting of a staged contoured marginal excision using "en face" permanent pathologic analysis preceding the steps of central excision of the lesion and the final reconstruction of the surgical defect. Advantages of this method include adequate margin control allowing final reconstruction and tissue preservation, while minimizing patient discomfort. The staged contoured marginal and central excision technique offers a new alternative to the armamentarium for surgical oncologists for the management of EMPD in which margin control is imperative for control of recurrence rates. Copyright © 2014 Elsevier Inc. All rights reserved.

Object-oriented approach to the automatic segmentation of bones from pediatric hand radiographs

NASA Astrophysics Data System (ADS)

Shim, Hyeonjoon; Liu, Brent J.; Taira, Ricky K.; Hall, Theodore R.

1997-04-01

The purpose of this paper is to develop a robust and accurate method that automatically segments phalangeal and epiphyseal bones from digital pediatric hand radiographs exhibiting various stages of growth. The development of this system draws principles from object-oriented design, model- guided analysis, and feedback control. A system architecture called 'the object segmentation machine' was implemented incorporating these design philosophies. The system is aided by a knowledge base where all model contours and other information such as age, race, and sex, are stored. These models include object structure models, shape models, 1-D wrist profiles, and gray level histogram models. Shape analysis is performed first by using an arc-length orientation transform to break down a given contour into elementary segments and curves. Then an interpretation tree is used as an inference engine to map known model contour segments to data contour segments obtained from the transform. Spatial and anatomical relationships among contour segments work as constraints from shape model. These constraints aid in generating a list of candidate matches. The candidate match with the highest confidence is chosen to be the current intermediate result. Verification of intermediate results are perform by a feedback control loop.

SU-E-J-192: Verification of 4D-MRI Internal Target Volume Using Cine MRI

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

Lafata, K; Czito, B; Palta, M

Purpose: To investigate the accuracy of 4D-MRI in determining the Internal Target Volume (ITV) used in radiation oncology treatment planning of liver cancers. Cine MRI is used as the standard baseline in establishing the feasibility and accuracy of 4D-MRI tumor motion within the liver. Methods: IRB approval was obtained for this retrospective study. Analysis was performed on MR images from four patients receiving external beam radiation therapy for liver cancer at our institution. Eligible patients received both Cine and 4D-MRI scans before treatment. Cine images were acquired sagittally in real time at a slice bisecting the tumor, while 4D imagesmore » were acquired volumetrically. Cine MR DICOM headers were manipulated such that each respiratory frame was assigned a unique slice location. This approach permitted the treatment planning system (Eclipse, Varian Medical Systems) to recognize a complete respiratory cycle as a “volume”, where the gross tumor was contoured temporally. Software was developed to calculate the union of all frame contours in the structure set, resulting in the corresponding plane of the ITV projecting through the middle of the tumor, defined as the Internal Target Area (ITA). This was repeated for 4D-MRI, at the corresponding slice location, allowing a direct comparison of ITAs obtained from each modality. Results: Four patients have been analyzed. ITAs contoured from 4D-MRI correlate with contours from Cine MRI. The mean error of 4D values relative to Cine values is 7.67 +/− 2.55 %. No single ITA contoured from 4D-MRI demonstrated more than 10.5 % error compared to its Cine MRI counterpart. Conclusion: Motion management is a significant aspect of treatment planning within dynamic environments such as the liver, where diaphragmatic and cardiac activity influence plan accuracy. This small pilot study suggests that 4D-MRI based ITA measurements agree with Cine MRI based measurements, an important step towards clinical implementation. NIH 1R21CA165384-01A1.« less

Performance Evaluation of Three Blood Glucose Monitoring Systems Using ISO 15197

PubMed Central

Bedini, José Luis; Wallace, Jane F.; Pardo, Scott; Petruschke, Thorsten

2015-01-01

Background: Blood glucose monitoring is an essential component of diabetes management. Inaccurate blood glucose measurements can severely impact patients’ health. This study evaluated the performance of 3 blood glucose monitoring systems (BGMS), Contour® Next USB, FreeStyle InsuLinx®, and OneTouch® Verio™ IQ, under routine hospital conditions. Methods: Venous blood samples (N = 236) obtained for routine laboratory procedures were collected at a Spanish hospital, and blood glucose (BG) concentrations were measured with each BGMS and with the available reference (hexokinase) method. Accuracy of the 3 BGMS was compared according to ISO 15197:2013 accuracy limit criteria, by mean absolute relative difference (MARD), consensus error grid (CEG) and surveillance error grid (SEG) analyses, and an insulin dosing error model. Results: All BGMS met the accuracy limit criteria defined by ISO 15197:2013. While all measurements of the 3 BGMS were within low-risk zones in both error grid analyses, the Contour Next USB showed significantly smaller MARDs between reference values compared to the other 2 BGMS. Insulin dosing errors were lowest for the Contour Next USB than compared to the other systems. Conclusions: All BGMS fulfilled ISO 15197:2013 accuracy limit criteria and CEG criterion. However, taking together all analyses, differences in performance of potential clinical relevance may be observed. Results showed that Contour Next USB had lowest MARD values across the tested glucose range, as compared with the 2 other BGMS. CEG and SEG analyses as well as calculation of the hypothetical bolus insulin dosing error suggest a high accuracy of the Contour Next USB. PMID:26445813

Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology.

PubMed

Li, Qingli; Zhou, Mei; Liu, Hongying; Wang, Yiting; Guo, Fangmin

2015-12-01

Red blood cell counts have been proven to be one of the most frequently performed blood tests and are valuable for early diagnosis of some diseases. This paper describes an automated red blood cell counting method based on microscopic hyperspectral imaging technology. Unlike the light microscopy-based red blood count methods, a combined spatial and spectral algorithm is proposed to identify red blood cells by integrating active contour models and automated two-dimensional k-means with spectral angle mapper algorithm. Experimental results show that the proposed algorithm has better performance than spatial based algorithm because the new algorithm can jointly use the spatial and spectral information of blood cells.

Yet another method for triangulation and contouring for automated cartography

NASA Technical Reports Server (NTRS)

De Floriani, L.; Falcidieno, B.; Nasy, G.; Pienovi, C.

1982-01-01

An algorithm is presented for hierarchical subdivision of a set of three-dimensional surface observations. The data structure used for obtaining the desired triangulation is also singularly appropriate for extracting contours. Some examples are presented, and the results obtained are compared with those given by Delaunay triangulation. The data points selected by the algorithm provide a better approximation to the desired surface than do randomly selected points.

Equal vibrotactile sense thresholds of the fingers and its diagnostic significance for hand-arm vibration syndrome.

PubMed

Cheng, H; Zhang, X C; Duan, L; Ma, Y; Wang, J X

1995-01-01

The vibrotactile sense thresholds (VSTs) of the middle fingers of 60 healthy persons and 97 patients with Hand-Arm Vibration Syndrome (HAVS) or subclinical HAVS were measured quantitatively. Intermittent vibratory irritations were adopted, with vibration stimulus frequencies at 8, 16, 31.5, 63, 125, 250, and 500 Hz. The equal VST contours of the fingers were mapped. Results showed that the VSTs of the normal group were not correlated with sex or handedness. From 8 Hz to 250 Hz the equal VST contours of the normal group were relatively flat; at more than 250 Hz the contours began an abrupt ascent. The VST values had a logarithmic rising tendency with the increasing age of subjects. In the equal VST contours the frequency of the most sensitive threshold value was 125 Hz in the normal group and 8 Hz in the HAVS group. The patients' VST values were higher than that of the healthy persons. The vibrotactilegram showed that the VST values of the patient groups first shifted at high frequencies and VST loss displayed a "V"-type hollow at 125 Hz and 250 Hz. The quantitative test method of VST was a valuable auxiliary detection method for HAVS. The "V"-type hollow of VST was an early clinical manifestation of HAVS.

Mass diffusion coefficient measurement for vitreous humor using FEM and MRI

NASA Astrophysics Data System (ADS)

Rattanakijsuntorn, Komsan; Penkova, Anita; Sadha, Satwindar S.

2018-01-01

In early studies, the ‘contour method’ for determining the diffusion coefficient of the vitreous humor was developed. This technique relied on careful injection of an MRI contrast agent (surrogate drug) into the vitreous humor of fresh bovine eyes, and tracking the contours of the contrast agent in time. In addition, an analytical solution was developed for the theoretical contours built on point source model for the injected surrogate drug. The match between theoretical and experimental contours as a least square fit, while floating the diffusion coefficient, led to the value of the diffusion coefficient. This method had its limitation that the initial injection of the surrogate had to be spherical or ellipsoidal because of the analytical result based on the point-source model. With a new finite element model for the analysis in this study, the technique is much less restrictive and handles irregular shapes of the initial bolus. The fresh bovine eyes were used for drug diffusion study in the vitreous and three contrast agents of different molecular masses: gadolinium-diethylenetriaminepentaacetic acid (Gd-DTPA, 938 Da), non-ionic gadoteridol (Prohance, 559 Da), and bovine albumin conjugated with gadolinium (Galbumin, 74 kDa) were used as drug surrogates to visualize the diffusion process by MRI. The 3D finite element model was developed to determine the diffusion coefficients of these surrogates with the images from MRI. This method can be used for other types of bioporous media provided the concentration profile can be visualized (by methods such as MRI or fluorescence).

Method of surface error visualization using laser 3D projection technology

NASA Astrophysics Data System (ADS)

Guo, Lili; Li, Lijuan; Lin, Xuezhu

2017-10-01

In the process of manufacturing large components, such as aerospace, automobile and shipping industry, some important mold or stamped metal plate requires precise forming on the surface, which usually needs to be verified, if necessary, the surface needs to be corrected and reprocessed. In order to make the correction of the machined surface more convenient, this paper proposes a method based on Laser 3D projection system, this method uses the contour form of terrain contour, directly showing the deviation between the actually measured data and the theoretical mathematical model (CAD) on the measured surface. First, measure the machined surface to get the point cloud data and the formation of triangular mesh; secondly, through coordinate transformation, unify the point cloud data to the theoretical model and calculate the three-dimensional deviation, according to the sign (positive or negative) and size of the deviation, use the color deviation band to denote the deviation of three-dimensional; then, use three-dimensional contour lines to draw and represent every coordinates deviation band, creating the projection files; finally, import the projection files into the laser projector, and make the contour line projected to the processed file with 1:1 in the form of a laser beam, compare the Full-color 3D deviation map with the projection graph, then, locate and make quantitative correction to meet the processing precision requirements. It can display the trend of the machined surface deviation clearly.

System Accuracy Evaluation of Four Systems for Self-Monitoring of Blood Glucose Following ISO 15197 Using a Glucose Oxidase and a Hexokinase-Based Comparison Method.

PubMed

Link, Manuela; Schmid, Christina; Pleus, Stefan; Baumstark, Annette; Rittmeyer, Delia; Haug, Cornelia; Freckmann, Guido

2015-04-14

The standard ISO (International Organization for Standardization) 15197 is widely accepted for the accuracy evaluation of systems for self-monitoring of blood glucose (SMBG). Accuracy evaluation was performed for 4 SMBG systems (Accu-Chek Aviva, ContourXT, GlucoCheck XL, GlucoMen LX PLUS) with 3 test strip lots each. To investigate a possible impact of the comparison method on system accuracy data, 2 different established methods were used. The evaluation was performed in a standardized manner following test procedures described in ISO 15197:2003 (section 7.3). System accuracy was assessed by applying ISO 15197:2003 and in addition ISO 15197:2013 criteria (section 6.3.3). For each system, comparison measurements were performed with a glucose oxidase (YSI 2300 STAT Plus glucose analyzer) and a hexokinase (cobas c111) method. All 4 systems fulfilled the accuracy requirements of ISO 15197:2003 with the tested lots. More stringent accuracy criteria of ISO 15197:2013 were fulfilled by 3 systems (Accu-Chek Aviva, ContourXT, GlucoMen LX PLUS) when compared to the manufacturer's comparison method and by 2 systems (Accu-Chek Aviva, ContourXT) when compared to the alternative comparison method. All systems showed lot-to-lot variability to a certain degree; 2 systems (Accu-Chek Aviva, ContourXT), however, showed only minimal differences in relative bias between the 3 evaluated lots. In this study, all 4 systems complied with the evaluated test strip lots with accuracy criteria of ISO 15197:2003. Applying ISO 15197:2013 accuracy limits, differences in the accuracy of the tested systems were observed, also demonstrating that the applied comparison method/system and the lot-to-lot variability can have a decisive influence on accuracy data obtained for a SMBG system. © 2015 Diabetes Technology Society.

Real-time biscuit tile image segmentation method based on edge detection.

PubMed

Matić, Tomislav; Aleksi, Ivan; Hocenski, Željko; Kraus, Dieter

2018-05-01

In this paper we propose a novel real-time Biscuit Tile Segmentation (BTS) method for images from ceramic tile production line. BTS method is based on signal change detection and contour tracing with a main goal of separating tile pixels from background in images captured on the production line. Usually, human operators are visually inspecting and classifying produced ceramic tiles. Computer vision and image processing techniques can automate visual inspection process if they fulfill real-time requirements. Important step in this process is a real-time tile pixels segmentation. BTS method is implemented for parallel execution on a GPU device to satisfy the real-time constraints of tile production line. BTS method outperforms 2D threshold-based methods, 1D edge detection methods and contour-based methods. Proposed BTS method is in use in the biscuit tile production line. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

After massive weight loss: patients' expectations of body contouring surgery.

PubMed

Kitzinger, Hugo B; Abayev, Sara; Pittermann, Anna; Karle, Birgit; Bohdjalian, Arthur; Langer, Felix B; Prager, Gerhard; Frey, Manfred

2012-04-01

Massive weight loss following bariatric surgery leads to excess skin with functional and aesthetic impairments. Surplus skin can then contribute to problems with additional weight loss or gain. The aims of the current study were to evaluate the frequency of massive soft tissue development in gastric bypass patients, to determine whether males and females experience similar post-bypass body changes, and to learn about the expectations and impairments related to body contouring surgery. A questionnaire addressing information on the satisfaction of body image, quality of life, and expectation of body contouring surgery following massive weight loss was mailed to 425 patients who had undergone gastric bypass surgery between 2003 and 2009. Of these 425 individuals, 252 (59%) patients completed the survey. Ninety percent of women and 88% of men surveyed rated their appearance following massive weight loss as satisfactory, good, or very good. However, 96% of all patients developed surplus skin, which caused intertriginous dermatitis and itching. In addition, patients reported problems with physical activity (playing sports) and finding clothing that fit appropriately. Moreover, 75% of female and 68% of male patients reported desiring body contouring surgery. The most important expectation of body contouring surgery was improved appearance, followed by improved self-confidence and quality of life. Surplus skin resulting from gastric bypass surgery is a common issue that causes functional and aesthetic impairments in patients. Consequently, this increases the desire for body contouring surgery with high expectations for the aesthetic outcome as well as improved life satisfaction.

Gallbladder Boundary Segmentation from Ultrasound Images Using Active Contour Model

NASA Astrophysics Data System (ADS)

Ciecholewski, Marcin

Extracting the shape of the gallbladder from an ultrasonography (US) image allows superfluous information which is immaterial in the diagnostic process to be eliminated. In this project an active contour model was used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps and changes in the shape of the organ, such as folds or turns of the gallbladder. The approximate shape of the gallbladder was found by applying the motion equation model. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 18.15%.

Auto-steering apparatus and method

DOEpatents

McKay, Mark D.; Anderson, Matthew O.

2007-03-13

A vehicular guidance method involves providing a user interface using which data can be input to establish a contour for a vehicle to follow, the user interface further configured to receive information from a differential global positioning system (DGPS), determining cross track and offset data using information received from the DGPS, generating control values, using at least vehicular kinematics, the cross track, and the offset data, and providing an output to control steering of the vehicle, using the control values, in a direction to follow the established contour while attempting to minimize the cross track and the offset data.

Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences

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

Dowling, Jason A., E-mail: jason.dowling@csiro.au; University of Newcastle, Callaghan, New South Wales; Sun, Jidi

Purpose: To validate automatic substitute computed tomography CT (sCT) scans generated from standard T2-weighted (T2w) magnetic resonance (MR) pelvic scans for MR-Sim prostate treatment planning. Patients and Methods: A Siemens Skyra 3T MR imaging (MRI) scanner with laser bridge, flat couch, and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole-pelvis MRI scan (1.6 mm 3-dimensional isotropic T2w SPACE [Sampling Perfection with Application optimized Contrasts using different flip angle Evolution] sequence) was acquired. Three additional small field of view scans were acquired: T2w, T2*w, and T1wmore » flip angle 80° for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder, and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI, allowing interobserver quantification. To generate a training database, each patient CT scan was coregistered to their whole-pelvis T2w using symmetric rigid registration and structure-guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. Results: The mean error in Hounsfield units between the sCT and corresponding patient CT (within the body contour) was 0.6 ± 14.7 (mean ± 1 SD), with a mean absolute error of 40.5 ± 8.2 Hounsfield units. Automatic contouring results were very close to the expert interobserver level (Dice similarity coefficient): prostate 0.80 ± 0.08, bladder 0.86 ± 0.12, rectum 0.84 ± 0.06, bones 0.91 ± 0.03, and body 1.00 ± 0.003. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same dose prescription was found to be 0.3% ± 0.8%. The 3-dimensional γ pass rate was 1.00 ± 0.00 (2 mm/2%). Conclusions: The MR-Sim setup and automatic sCT generation methods using standard MR sequences generates realistic contours and electron densities for prostate cancer radiation therapy dose planning and digitally reconstructed radiograph generation.« less

Using satellite radiotelemetry data to delineate and manage wildlife populations

USGS Publications Warehouse

Amstrup, Steven C.; McDonald, T.L.; Durner, George M.

2004-01-01

The greatest promise of radiotelemetry always has been a better understanding of animal movements. Telemetry has helped us know when animals are active, how active they are, how far and how fast they move, the geographic areas they occupy, and whether individuals vary in these traits. Unfortunately, the inability to estimate the error in animals utilization distributions (UDs), has prevented probabilistic linkage of movements data, which are always retrospective, with future management actions. We used the example of the harvested population of polar bears (Ursus maritimus) in the Southern Beaufort Sea to illustrate a method that provides that linkage. We employed a 2-dimensional Gaussian kernel density estimator to smooth and scale frequencies of polar bear radio locations within cells of a grid overlying our study area. True 2-dimensional smoothing allowed us to create accurate descriptions of the UDs of individuals and groups of bears. We used a new method of clustering, based upon the relative use collared bears made of each cell in our grid, to assign individual animals to populations. We applied the fast Fourier transform to make bootstrapped estimates of the error in UDs computationally feasible. Clustering and kernel smoothing identified 3 populations of polar bears in the region between Wrangel Island, Russia, and Banks Island, Canada. The relative probability of occurrence of animals from each population varied significantly among grid cells distributed across the study area. We displayed occurrence probabilities as contour maps wherein each contour line corresponded with a change in relative probability. Only at the edges of our study area and in some offshore regions were bootstrapped estimates of error in occurrence probabilities too high to allow prediction. Error estimates, which also were displayed as contours, allowed us to show that occurrence probabilities did not vary by season. Near Barrow, Alaska, 50% of bears observed are predicted to be from the Chukchi Sea population and 50% from the Southern Beaufort Sea population. At Tuktoyaktuk, Northwest Territories, Canada, 50% are from the Southern Beaufort Sea and 50% from the Northern Beaufort Sea population. The methods described here will aid managers of all wildlife that can be studied by telemetry to allocate harvests and other human perturbations to the appropriate populations, make risk assessments, and predict impacts of human activities. They will aid researchers by providing the refined descriptions of study populations that are necessary for population estimation and other investigative tasks. Arctic, Beaufort Sea, boundaries, clustering, Fourier transform, kernel, management, polar bears, population delineation, radiotelemetry, satellite, smoothing, Ursus maritimus

What is in a contour map? A region-based logical formalization of contour semantics

USGS Publications Warehouse

Usery, E. Lynn; Hahmann, Torsten

2015-01-01

This paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. The elicited contour semantics comprises four key concepts – contour regions, contour lines, contour values, and contour sets – and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology. All concepts and relations are illustrated and motivated by physical-geographic features identifiable on topographic contour maps. The encoding of the semantics of contour concepts in first-order logic and a derived conceptual model as basis for an OWL ontology lay the foundation for fully automated, semantically-aware qualitative and quantitative reasoning about contours.

Contour-Driven Atlas-Based Segmentation

PubMed Central

Wachinger, Christian; Fritscher, Karl; Sharp, Greg; Golland, Polina

2016-01-01

We propose new methods for automatic segmentation of images based on an atlas of manually labeled scans and contours in the image. First, we introduce a Bayesian framework for creating initial label maps from manually annotated training images. Within this framework, we model various registration- and patch-based segmentation techniques by changing the deformation field prior. Second, we perform contour-driven regression on the created label maps to refine the segmentation. Image contours and image parcellations give rise to non-stationary kernel functions that model the relationship between image locations. Setting the kernel to the covariance function in a Gaussian process establishes a distribution over label maps supported by image structures. Maximum a posteriori estimation of the distribution over label maps conditioned on the outcome of the atlas-based segmentation yields the refined segmentation. We evaluate the segmentation in two clinical applications: the segmentation of parotid glands in head and neck CT scans and the segmentation of the left atrium in cardiac MR angiography images. PMID:26068202

SU-F-J-115: Target Volume and Artifact Evaluation of a New Device-Less 4D CT Algorithm

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

Martin, R; Pan, T

2016-06-15

Purpose: 4DCT is often used in radiation therapy treatment planning to define the extent of motion of the visible tumor (IGTV). Recent available software allows 4DCT images to be created without the use of an external motion surrogate. This study aims to compare this device-less algorithm to a standard device-driven technique (RPM) in regards to artifacts and the creation of treatment volumes. Methods: 34 lung cancer patients who had previously received a cine 4DCT scan on a GE scanner with an RPM determined respiratory signal were selected. Cine images were sorted into 10 phases based on both the RPM signalmore » and the device-less algorithm. Contours were created on standard and device-less maximum intensity projection (MIP) images using a region growing algorithm and manual adjustment to remove other structures. Variations in measurements due to intra-observer differences in contouring were assessed by repeating a subset of 6 patients 2 additional times. Artifacts in each phase image were assessed using normalized cross correlation at each bed position transition. A score between +1 (artifacts “better” in all phases for device-less) and −1 (RPM similarly better) was assigned for each patient based on these results. Results: Device-less IGTV contours were 2.1 ± 1.0% smaller than standard IGTV contours (not significant, p = 0.15). The Dice similarity coefficient (DSC) was 0.950 ± 0.006 indicating good similarity between the contours. Intra-observer variation resulted in standard deviations of 1.2 percentage points in percent volume difference and 0.005 in DSC measurements. Only two patients had improved artifacts with RPM, and the average artifact score (0.40) was significantly greater than zero. Conclusion: Device-less 4DCT can be used in place of the standard method for target definition due to no observed difference between standard and device-less IGTVs. Phase image artifacts were significantly reduced with the device-less method.« less

Review of the Mechanisms and Effects of Noninvasive Body Contouring Devices on Cellulite and Subcutaneous Fat.

PubMed

Alizadeh, Zahra; Halabchi, Farzin; Mazaheri, Reza; Abolhasani, Maryam; Tabesh, Mastaneh

2016-10-01

Today, different kinds of non-invasive body contouring modalities, including cryolipolysis, radiofrequency (RF), low-level laser therapy (LLLT), and high-intensity focused ultrasound (HIFU) are available for reducing the volume of subcutaneous adipose tissue or cellulite. Each procedure has distinct mechanisms for stimulating apoptosis or necrosis adipose tissue. In addition to the mentioned techniques, some investigations are underway for analyzing the efficacy of other techniques such as whole body vibration (WBV) and extracorporeal shockwave therapy (ESWT). In the present review the mechanisms, effects and side effects of the mentioned methods have been discussed. The effect of these devices on cellulite or subcutaneous fat reduction has been assessed. We searched pubmed, google scholar and the cochrane databases for systemic reviews, review articles, meta-analysis and randomized clinical trials up to February 2015. The keywords were subcutaneous fat, cellulite, obesity, noninvasive body contouring, cryolipolysis, RF, LLLT, HIFU, ESWT and WBV with full names and abbreviations. We included seven reviews and 66 original articles in the present narrative review. Most of them were applied on normal weight or overweight participants (body mass index < 30 kg/m 2 ) in both genders with broad range of ages (18 to 50 years on average). In the original articles, the numbers of included methods were: 10 HIFU, 13 RF, 22 cryolipolysis, 11 LLLT, 5 ESWT and 4 WBV therapies. Six of the articles evaluated combination therapies and seven compared the effects of different devices. Some of the noninvasive body contouring devices in animal and human studies such as cryolipolysis, RF, LLLT and HIFU showed statistical significant effects on body contouring, removing unwanted fat and cellulite in some body areas. However, the clinical effects are mild to moderate, for example 2 - 4 cm circumference reduction as a sign of subcutaneous fat reduction during total treatment sessions. Overall, there is no definitive noninvasive treatment method for cellulite. Additionally, due to the methodological differences in the existing evidence, comparing the techniques is difficult.

SU-F-T-405: Development of a Rapid Cardiac Contouring Tool Using Landmark-Driven Modeling

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

Pelletier, C; Jung, J; Mosher, E

2016-06-15

Purpose: This study aims to develop a tool to rapidly delineate cardiac substructures for use in dosimetry for large-scale clinical trial or epidemiological investigations. The goal is to produce a system that can semi-automatically delineate nine cardiac structures to a reasonable accuracy within a couple of minutes. Methods: The cardiac contouring tool employs a Most Similar Atlas method, where a selection criterion is used to pre-select the most similar model to the patient from a library of pre-defined atlases. Sixty contrast-enhanced cardiac computed tomography angiography (CTA) scans (30 male and 30 female) were manually contoured to serve as the atlasmore » library. For each CTA 12 structures were delineated. Kabsch algorithm was used to compute the optimum rotation and translation matrices between the patient and atlas. Minimum root mean squared distance between the patient and atlas after transformation was used to select the most-similar atlas. An initial study using 10 CTA sets was performed to assess system feasibility. Leave-one patient out method was performed, and fit criteria were calculated to evaluate the fit accuracy compared to manual contours. Results: For the pilot study, mean dice indices of .895 were achieved for the whole heart, .867 for the ventricles, and .802 for the atria. In addition, mean distance was measured via the chord length distribution (CLD) between ground truth and the atlas structures for the four coronary arteries. The mean CLD for all coronary arteries was below 14mm, with the left circumflex artery showing the best agreement (7.08mm). Conclusion: The cardiac contouring tool is able to delineate cardiac structures with reasonable accuracy in less than 90 seconds. Pilot data indicates that the system is able to delineate the whole heart and ventricles within a reasonable accuracy using even a limited library. We are extending the atlas sets to 60 adult males and females in total.« less

SU-F-J-72: A Clinical Usable Integrated Contouring Quality Evaluation Software for Radiotherapy

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

Jiang, S; Dolly, S; Cai, B

Purpose: To introduce the Auto Contour Evaluation (ACE) software, which is the clinical usable, user friendly, efficient and all-in-one toolbox for automatically identify common contouring errors in radiotherapy treatment planning using supervised machine learning techniques. Methods: ACE is developed with C# using Microsoft .Net framework and Windows Presentation Foundation (WPF) for elegant GUI design and smooth GUI transition animations through the integration of graphics engines and high dots per inch (DPI) settings on modern high resolution monitors. The industrial standard software design pattern, Model-View-ViewModel (MVVM) pattern, is chosen to be the major architecture of ACE for neat coding structure, deepmore » modularization, easy maintainability and seamless communication with other clinical software. ACE consists of 1) a patient data importing module integrated with clinical patient database server, 2) a 2D DICOM image and RT structure simultaneously displaying module, 3) a 3D RT structure visualization module using Visualization Toolkit or VTK library and 4) a contour evaluation module using supervised pattern recognition algorithms to detect contouring errors and display detection results. ACE relies on supervised learning algorithms to handle all image processing and data processing jobs. Implementations of related algorithms are powered by Accord.Net scientific computing library for better efficiency and effectiveness. Results: ACE can take patient’s CT images and RT structures from commercial treatment planning software via direct user input or from patients’ database. All functionalities including 2D and 3D image visualization and RT contours error detection have been demonstrated with real clinical patient cases. Conclusion: ACE implements supervised learning algorithms and combines image processing and graphical visualization modules for RT contours verification. ACE has great potential for automated radiotherapy contouring quality verification. Structured with MVVM pattern, it is highly maintainable and extensible, and support smooth connections with other clinical software tools.« less

Evaluating the Impact of a Canadian National Anatomy and Radiology Contouring Boot Camp for Radiation Oncology Residents

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

Jaswal, Jasbir; D'Souza, Leah; Johnson, Marjorie

Background: Radiation therapy treatment planning has advanced over the past 2 decades, with increased emphasis on 3-dimensional imaging for target and organ-at-risk (OAR) delineation. Recent studies suggest a need for improved resident instruction in this area. We developed and evaluated an intensive national educational course (“boot camp”) designed to provide dedicated instruction in site-specific anatomy, radiology, and contouring using a multidisciplinary (MDT) approach. Methods: The anatomy and radiology contouring (ARC) boot camp was modeled after prior single-institution pilot studies and a needs-assessment survey. The boot camp incorporated joint lectures from radiation oncologists, anatomists, radiologists, and surgeons, with hands-on contouring instructionmore » and small group interactive seminars using cadaveric prosections and correlative axial radiographs. Outcomes were evaluated using pretesting and posttesting, including anatomy/radiology multiple-choice questions (MCQ), timed contouring sessions (evaluated relative to a gold standard using Dice similarity metrics), and qualitative questions on satisfaction and perceived effectiveness. Analyses of pretest versus posttest scores were performed using nonparametric paired testing. Results: Twenty-nine radiation oncology residents from 10 Canadian universities participated. As part of their current training, 29%, 75%, and 21% receive anatomy, radiology, and contouring instruction, respectively. On posttest scores, the MCQ knowledge scores improved significantly (pretest mean 60% vs posttest mean 80%, P<.001). Across all contoured structures, there was a 0.20 median improvement in students' average Dice score (P<.001). For individual structures, significant Dice improvements occurred in 10 structures. Residents self-reported an improved ability to contour OARs and interpret radiographs in all anatomic sites, 92% of students found the MDT format effective for their learning, and 93% found the boot camp more effective than educational sessions at their own institutions. All of the residents (100%) would recommend this course to others. Conclusions: The ARC boot camp is an effective intervention for improving radiation oncology residents' knowledge and understanding of anatomy and radiology in addition to enhancing their confidence and accuracy in contouring.« less

TU-H-CAMPUS-JeP2-05: Can Automatic Delineation of Cardiac Substructures On Noncontrast CT Be Used for Cardiac Toxicity Analysis?

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

Luo, Y; Liao, Z; Jiang, W

Purpose: To evaluate the feasibility of using an automatic segmentation tool to delineate cardiac substructures from computed tomography (CT) images for cardiac toxicity analysis for non-small cell lung cancer (NSCLC) patients after radiotherapy. Methods: A multi-atlas segmentation tool developed in-house was used to delineate eleven cardiac substructures including the whole heart, four heart chambers, and six greater vessels automatically from the averaged 4DCT planning images for 49 NSCLC patients. The automatic segmented contours were edited appropriately by two experienced radiation oncologists. The modified contours were compared with the auto-segmented contours using Dice similarity coefficient (DSC) and mean surface distance (MSD)more » to evaluate how much modification was needed. In addition, the dose volume histogram (DVH) of the modified contours were compared with that of the auto-segmented contours to evaluate the dosimetric difference between modified and auto-segmented contours. Results: Of the eleven structures, the averaged DSC values ranged from 0.73 ± 0.08 to 0.95 ± 0.04 and the averaged MSD values ranged from 1.3 ± 0.6 mm to 2.9 ± 5.1mm for the 49 patients. Overall, the modification is small. The pulmonary vein (PV) and the inferior vena cava required the most modifications. The V30 (volume receiving 30 Gy or above) for the whole heart and the mean dose to the whole heart and four heart chambers did not show statistically significant difference between modified and auto-segmented contours. The maximum dose to the greater vessels did not show statistically significant difference except for the PV. Conclusion: The automatic segmentation of the cardiac substructures did not require substantial modification. The dosimetric evaluation showed no statistically significant difference between auto-segmented and modified contours except for the PV, which suggests that auto-segmented contours for the cardiac dose response study are feasible in the clinical practice with a minor modification to the PV vessel.« less

Effectiveness of Educational Intervention on the Congruence of Prostate and Rectal Contouring as Compared With a Gold Standard in Three-Dimensional Radiotherapy for Prostate

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

Szumacher, Ewa, E-mail: Ewa.Szumacher@sunnybrook.c; Harnett, Nicole; Warner, Saar

Purpose: To examine effects of a teaching intervention on precise delineation of the prostate and rectum during planning of three-dimensional conformal radiotherapy (3D-CRT) for prostate cancer. Methods and Materials: A pretest, posttest, randomized controlled group design was used. During pretest all participants contoured prostate and rectum on planning CT. Afterward, they participated in two types of workshops. The experimental group engaged in an interactive teaching session focused on prostate and rectum MR anatomy compared with CT anatomy. The control group focused on 3D-CRT planning without mention of prostate or rectal contouring. The experimental group practiced on fused MR-CT images, whereasmore » the control group practiced on CT images. All participants completed the posttest. Results: Thirty-one trainees (12 male, 19 female) were randomly assigned to two groups, 17 in the experimental arm, and 14 in the control group. Seventeen felt familiar or very familiar with pelvic organ contouring, 12 somewhat, and 2 had never done it. Thirteen felt confident with organ contouring, 13 somewhat, and 5 not confident. The demographics and composition of groups were analyzed with chi{sup 2} and repeated-measures analysis of variance with the two groups (experimental or control) and two tests (pre- or posttest) as factors. Satisfaction with the course and long-term effects of the course on practice were assessed with immediate and delayed surveys. All performance variables showed a similar pattern of results. Conclusions: The training sessions improved the technical performance similarly in both groups. Participants were satisfied with the course content, and the delayed survey reflected that cognitively participants felt more confident with prostate and rectum contouring and would investigate opportunities to learn more about organ contouring.« less

Automatic contouring of geologic fabric and finite strain data on the unit hyperboloid

NASA Astrophysics Data System (ADS)

Vollmer, Frederick W.

2018-06-01

Fabric and finite strain analysis, an integral part of studies of geologic structures and orogenic belts, is commonly done by the analysis of particles whose shapes can be approximated as ellipses. Given a sample of such particles, the mean and confidence intervals of particular parameters can be calculated, however, taking the extra step of plotting and contouring the density distribution can identify asymmetries or modes related to sedimentary fabrics or other factors. A common graphical strain analysis technique is to plot final ellipse ratios, Rf , versus orientations, ϕf on polar Elliott or Rf / ϕ plots to examine the density distribution. The plot may be contoured, however, it is desirable to have a contouring method that is rapid, reproducible, and based on the underlying geometry of the data. The unit hyperboloid, H2 , gives a natural parameter space for two-dimensional strain, and various projections, including equal-area and stereographic, have useful properties for examining density distributions for anisotropy. An index, Ia , is given to quantify the magnitude and direction of anisotropy. Elliott and Rf / ϕ plots can be understood by applying hyperbolic geometry and recognizing them as projections of H2 . These both distort area, however, so the equal-area projection is preferred for examining density distributions. The algorithm presented here gives fast, accurate, and reproducible contours of density distributions calculated directly on H2 . The algorithm back-projects the data onto H2 , where the density calculation is done at regular nodes using a weighting value based on the hyperboloid distribution, which is then contoured. It is implemented as an Octave compatible MATLAB function that plots ellipse data using a variety of projections, and calculates and displays contours of their density distribution on H2 .

Poster – 41: External marker block placement on the breast or chest wall for left-sided deep inspiration breath-hold radiotherapy

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

Conroy, Leigh; Guebert, Alexandra; Smith, Wendy

Purpose: We investigate DIBH breast radiotherapy using the Real-time Position Management (RPM) system with the marker-block placed on the target breast or chest wall. Methods: We measured surface dose for three different RPM marker-blocks using EBT3 Gafchromic film at 0° and 30° incidence. A registration study was performed to determine the breast surface position that best correlates with overall internal chest wall position. Surface and chest wall contours from MV images of the medial tangent field were extracted for 15 patients. Surface contours were divided into three potential marker-block positions on the breast: Superior, Middle, and Inferior. Translational registration wasmore » used to align the partial contours to the first-fraction contour. Each resultant transformation matrix was applied to the chest wall contour, and the minimum distance between the reference chest wall contour and the transformed chest wall contour was evaluated for each pixel. Results: The measured surface dose for the 2-dot, 6-dot, and 4-dot marker-blocks at 0° incidence were 74%, 71%, and 77% of dose to dmax respectively. At 30° beam incidence this increased to 76%, 72%, and 81%. The best external surface position was patient and fraction dependent, with no consistent best choice. Conclusions: The increase in surface dose directly under the RPM block is approximately equivalent to 3 mm of bolus. No marker-block position on the breast surface was found to be more representative of overall chest wall motion; therefore block positional stability and reproducibility can be used to determine optimal placement on the breast or chest wall.« less

Integration of intracardiac echocardiography and computed tomography during atrial fibrillation ablation: Combining ultrasound contours obtained from the right atrium and ventricular outflow tract.

PubMed

Nakamura, Kohki; Naito, Shigeto; Kaseno, Kenichi; Nakatani, Yosuke; Sasaki, Takehito; Anjo, Naofumi; Yamashita, Eiji; Kumagai, Koji; Funabashi, Nobusada; Kobayashi, Yoshio; Oshima, Shigeru

2017-02-01

We aimed to optimize the acquisition of the left atrial (LA) and pulmonary vein (PV) ultrasound contours for more accurate integration of intracardiac echocardiography (ICE) and computed tomography (CT) using the CARTO ® 3 system during atrial fibrillation (AF) ablation. Eighty-five AF patients underwent integration of ICE and CT using (1) the LA roof and posterior wall contours acquired from the right atrium (RA), (2) all LA/PV contours from the RA (Whole-RA-integration), (3) the LA roof/posterior wall contours from the RA and right ventricular outflow tract (RVOT) (Posterior-RA/RV-integration), and (4) all LA/PV contours from the RA and RVOT (Whole-RA/RV-integration). The integration accuracy was compared using the (1) surface registration error, (2) distances between the three-dimensional CT and eight specific sites on the anterior, posterior, superior, and inferior aspects of the right and left circumferential PV isolation lines, and (3) registration score: a score of 0 or 1 was assigned for whether or not each specific site was visually aligned with the CT, and summed for each method (0 best, 8 worst). Posterior-RA/RV-integration revealed a significantly lower surface registration error (1.30±0.15mm) than Whole-RA- and Whole-RA/RV-integration (p<0.001). The mean distances of the eight specific sites and the registration score for Posterior-RA/RV-integration (median 1.26mm and 2, respectively) were significantly smaller than those for the other integration approaches (p<0.001). Image integration with the LA roof and posterior wall contours acquired from the RA and RVOT may provide greater accuracy for catheter navigation with three-dimensional CT during AF ablation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Target volume definition for 18F-FDG PET-positive lymph nodes in radiotherapy of patients with non-small cell lung cancer.

PubMed

Nestle, Ursula; Schaefer-Schuler, Andrea; Kremp, Stephanie; Groeschel, Andreas; Hellwig, Dirk; Rübe, Christian; Kirsch, Carl-Martin

2007-04-01

FDG PET is increasingly used in radiotherapy planning. Recently, we demonstrated substantial differences in target volumes when applying different methods of FDG-based contouring in primary lung tumours (Nestle et al., J Nucl Med 2005;46:1342-8). This paper focusses on FDG-positive mediastinal lymph nodes (LN(PET)). In our institution, 51 NSCLC patients who were candidates for radiotherapy prospectively underwent staging FDG PET followed by a thoracic PET scan in the treatment position and a planning CT. Eleven of them had 32 distinguishable non-confluent mediastinal or hilar nodal FDG accumulations (LN(PET)). For these, sets of gross tumour volumes (GTVs) were generated at both acquisition times by four different PET-based contouring methods (visual: GTV(vis); 40% SUVmax: GTV40; SUV=2.5: GTV2.5; target/background (T/B) algorithm: GTV(bg)). All differences concerning GTV sizes were within the range of the resolution of the PET system. The detectability and technical delineability of the GTVs were significantly better in the late scans (e.g. p = 0.02 for diagnostic application of SUVmax = 2.5; p = 0.0001 for technical delineability by GTV2.5; p = 0.003 by GTV40), favouring the GTV(bg) method owing to satisfactory overall applicability and independence of GTVs from acquisition time. Compared with CT, the majority of PET-based GTVs were larger, probably owing to resolution effects, with a possible influence of lesion movements. For nodal GTVs, different methods of contouring did not lead to clinically relevant differences in volumes. However, there were significant differences in technical delineability, especially after early acquisition. Overall, our data favour a late acquisition of FDG PET scans for radiotherapy planning, and the use of a T/B algorithm for GTV contouring.

The Effect of Local Orientation Change on the Detection of Contours Defined by Constant Curvature: Psychophysics and Image Statistics.

PubMed

Khuu, Sieu K; Cham, Joey; Hayes, Anthony

2016-01-01

In the present study, we investigated the detection of contours defined by constant curvature and the statistics of curved contours in natural scenes. In Experiment 1, we examined the degree to which human sensitivity to contours is affected by changing the curvature angle and disrupting contour curvature continuity by varying the orientation of end elements. We find that (1) changing the angle of contour curvature decreased detection performance, while (2) end elements oriented in the direction (i.e., clockwise) of curvature facilitated contour detection regardless of the curvature angle of the contour. In Experiment 2 we further established that the relative effect of end-element orientation on contour detection was not only dependent on their orientation (collinear or cocircular), but also their spatial separation from the contour, and whether the contour shape was curved or not (i.e., C-shaped or S-shaped). Increasing the spatial separation of end-elements reduced contour detection performance regardless of their orientation or the contour shape. However, at small separations, cocircular end-elements facilitated the detection of C-shaped contours, but not S-shaped contours. The opposite result was observed for collinear end-elements, which improved the detection of S- shaped, but not C-shaped contours. These dissociative results confirmed that the visual system specifically codes contour curvature, but the association of contour elements occurs locally. Finally, we undertook an analysis of natural images that mapped contours with a constant angular change and determined the frequency of occurrence of end elements with different orientations. Analogous to our behavioral data, this image analysis revealed that the mapped end elements of constantly curved contours are likely to be oriented clockwise to the angle of curvature. Our findings indicate that the visual system is selectively sensitive to contours defined by constant curvature and that this might reflect the properties of curved contours in natural images.

Efficient hyperspectral image segmentation using geometric active contour formulation

NASA Astrophysics Data System (ADS)

Albalooshi, Fatema A.; Sidike, Paheding; Asari, Vijayan K.

2014-10-01

In this paper, we present a new formulation of geometric active contours that embeds the local hyperspectral image information for an accurate object region and boundary extraction. We exploit self-organizing map (SOM) unsupervised neural network to train our model. The segmentation process is achieved by the construction of a level set cost functional, in which, the dynamic variable is the best matching unit (BMU) coming from SOM map. In addition, we use Gaussian filtering to discipline the deviation of the level set functional from a signed distance function and this actually helps to get rid of the re-initialization step that is computationally expensive. By using the properties of the collective computational ability and energy convergence capability of the active control models (ACM) energy functional, our method optimizes the geometric ACM energy functional with lower computational time and smoother level set function. The proposed algorithm starts with feature extraction from raw hyperspectral images. In this step, the principal component analysis (PCA) transformation is employed, and this actually helps in reducing dimensionality and selecting best sets of the significant spectral bands. Then the modified geometric level set functional based ACM is applied on the optimal number of spectral bands determined by the PCA. By introducing local significant spectral band information, our proposed method is capable to force the level set functional to be close to a signed distance function, and therefore considerably remove the need of the expensive re-initialization procedure. To verify the effectiveness of the proposed technique, we use real-life hyperspectral images and test our algorithm in varying textural regions. This framework can be easily adapted to different applications for object segmentation in aerial hyperspectral imagery.

Evaluating performance of a user-trained MR lung tumor autocontouring algorithm in the context of intra- and interobserver variations.

PubMed

Yip, Eugene; Yun, Jihyun; Gabos, Zsolt; Baker, Sarah; Yee, Don; Wachowicz, Keith; Rathee, Satyapal; Fallone, B Gino

2018-01-01

Real-time tracking of lung tumors using magnetic resonance imaging (MRI) has been proposed as a potential strategy to mitigate the ill-effects of breathing motion in radiation therapy. Several autocontouring methods have been evaluated against a "gold standard" of a single human expert user. However, contours drawn by experts have inherent intra- and interobserver variations. In this study, we aim to evaluate our user-trained autocontouring algorithm with manually drawn contours from multiple expert users, and to contextualize the accuracy of these autocontours within intra- and interobserver variations. Six nonsmall cell lung cancer patients were recruited, with institutional ethics approval. Patients were imaged with a clinical 3 T Philips MR scanner using a dynamic 2D balanced SSFP sequence under free breathing. Three radiation oncology experts, each in two separate sessions, contoured 130 dynamic images for each patient. For autocontouring, the first 30 images were used for algorithm training, and the remaining 100 images were autocontoured and evaluated. Autocontours were compared against manual contours in terms of Dice's coefficient (DC) and Hausdorff distances (d H ). Intra- and interobserver variations of the manual contours were also evaluated. When compared with the manual contours of the expert user who trained it, the algorithm generates autocontours whose evaluation metrics (same session: DC = 0.90(0.03), d H  = 3.8(1.6) mm; different session DC = 0.88(0.04), d H  = 4.3(1.5) mm) are similar to or better than intraobserver variations (DC = 0.88(0.04), and d H  = 4.3(1.7) mm) between two sessions. The algorithm's autocontours are also compared to the manual contours from different expert users with evaluation metrics (DC = 0.87(0.04), d H  = 4.8(1.7) mm) similar to interobserver variations (DC = 0.87(0.04), d H  = 4.7(1.6) mm). Our autocontouring algorithm delineates tumor contours (<20 ms per contour), in dynamic MRI of lung, that are comparable to multiple human experts (several seconds per contour), but at a much faster speed. At the same time, the agreement between autocontours and manual contours is comparable to the intra- and interobserver variations. This algorithm may be a key component of the real time tumor tracking workflow for our hybrid Linac-MR device in the future. © 2017 American Association of Physicists in Medicine.

Contour integral method for obtaining the self-energy matrices of electrodes in electron transport calculations

NASA Astrophysics Data System (ADS)

Iwase, Shigeru; Futamura, Yasunori; Imakura, Akira; Sakurai, Tetsuya; Tsukamoto, Shigeru; Ono, Tomoya

2018-05-01

We propose an efficient computational method for evaluating the self-energy matrices of electrodes to study ballistic electron transport properties in nanoscale systems. To reduce the high computational cost incurred in large systems, a contour integral eigensolver based on the Sakurai-Sugiura method combined with the shifted biconjugate gradient method is developed to solve an exponential-type eigenvalue problem for complex wave vectors. A remarkable feature of the proposed algorithm is that the numerical procedure is very similar to that of conventional band structure calculations. We implement the developed method in the framework of the real-space higher-order finite-difference scheme with nonlocal pseudopotentials. Numerical tests for a wide variety of materials validate the robustness, accuracy, and efficiency of the proposed method. As an illustration of the method, we present the electron transport property of the freestanding silicene with the line defect originating from the reversed buckled phases.

Target volume and artifact evaluation of a new data-driven 4D CT.

PubMed

Martin, Rachael; Pan, Tinsu

Four-dimensional computed tomography (4D CT) is often used to define the internal gross target volume (IGTV) for radiation therapy of lung cancer. Traditionally, this technique requires the use of an external motion surrogate; however, a new image, data-driven 4D CT, has become available. This study aims to describe this data-driven 4D CT and compare target contours created with it to those created using standard 4D CT. Cine CT data of 35 patients undergoing stereotactic body radiation therapy were collected and sorted into phases using standard and data-driven 4D CT. IGTV contours were drawn using a semiautomated method on maximum intensity projection images of both 4D CT methods. Errors resulting from reproducibility of the method were characterized. A comparison of phase image artifacts was made using a normalized cross-correlation method that assigned a score from +1 (data-driven "better") to -1 (standard "better"). The volume difference between the data-driven and standard IGTVs was not significant (data driven was 2.1 ± 1.0% smaller, P = .08). The Dice similarity coefficient showed good similarity between the contours (0.949 ± 0.006). The mean surface separation was 0.4 ± 0.1 mm and the Hausdorff distance was 3.1 ± 0.4 mm. An average artifact score of +0.37 indicated that the data-driven method had significantly fewer and/or less severe artifacts than the standard method (P = 1.5 × 10 -5 for difference from 0). On average, the difference between IGTVs derived from data-driven and standard 4D CT was not clinically relevant or statistically significant, suggesting data-driven 4D CT can be used in place of standard 4D CT without adjustments to IGTVs. The relatively large differences in some patients were usually attributed to limitations in automatic contouring or differences in artifacts. Artifact reduction and setup simplicity suggest a clinical advantage to data-driven 4D CT. Published by Elsevier Inc.

Segmentation of solid subregion of high grade gliomas in MRI images based on active contour model (ACM)

NASA Astrophysics Data System (ADS)

Seow, P.; Win, M. T.; Wong, J. H. D.; Abdullah, N. A.; Ramli, N.

2016-03-01

Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, active contour model (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging.

Segmentation and Quantitative Analysis of Apoptosis of Chinese Hamster Ovary Cells from Fluorescence Microscopy Images.

PubMed

Du, Yuncheng; Budman, Hector M; Duever, Thomas A

2017-06-01

Accurate and fast quantitative analysis of living cells from fluorescence microscopy images is useful for evaluating experimental outcomes and cell culture protocols. An algorithm is developed in this work to automatically segment and distinguish apoptotic cells from normal cells. The algorithm involves three steps consisting of two segmentation steps and a classification step. The segmentation steps are: (i) a coarse segmentation, combining a range filter with a marching square method, is used as a prefiltering step to provide the approximate positions of cells within a two-dimensional matrix used to store cells' images and the count of the number of cells for a given image; and (ii) a fine segmentation step using the Active Contours Without Edges method is applied to the boundaries of cells identified in the coarse segmentation step. Although this basic two-step approach provides accurate edges when the cells in a given image are sparsely distributed, the occurrence of clusters of cells in high cell density samples requires further processing. Hence, a novel algorithm for clusters is developed to identify the edges of cells within clusters and to approximate their morphological features. Based on the segmentation results, a support vector machine classifier that uses three morphological features: the mean value of pixel intensities in the cellular regions, the variance of pixel intensities in the vicinity of cell boundaries, and the lengths of the boundaries, is developed for distinguishing apoptotic cells from normal cells. The algorithm is shown to be efficient in terms of computational time, quantitative analysis, and differentiation accuracy, as compared with the use of the active contours method without the proposed preliminary coarse segmentation step.

Fully automated adipose tissue measurement on abdominal CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Sussman, Daniel L.; Summers, Ronald M.

2011-03-01

Obesity has become widespread in America and has been associated as a risk factor for many illnesses. Adipose tissue (AT) content, especially visceral AT (VAT), is an important indicator for risks of many disorders, including heart disease and diabetes. Measuring adipose tissue (AT) with traditional means is often unreliable and inaccurate. CT provides a means to measure AT accurately and consistently. We present a fully automated method to segment and measure abdominal AT in CT. Our method integrates image preprocessing which attempts to correct for image artifacts and inhomogeneities. We use fuzzy cmeans to cluster AT regions and active contour models to separate subcutaneous and visceral AT. We tested our method on 50 abdominal CT scans and evaluated the correlations between several measurements.

Identifying a maximum tolerated contour in two-dimensional dose-finding

PubMed Central

Wages, Nolan A.

2016-01-01

The majority of Phase I methods for multi-agent trials have focused on identifying a single maximum tolerated dose combination (MTDC) among those being investigated. Some published methods in the area have been based on the notion that there is no unique MTDC, and that the set of dose combinations with acceptable toxicity forms an equivalence contour in two dimensions. Therefore, it may be of interest to find multiple MTDC's for further testing for efficacy in a Phase II setting. In this paper, we present a new dose-finding method that extends the continual reassessment method to account for the location of multiple MTDC's. Operating characteristics are demonstrated through simulation studies, and are compared to existing methodology. Some brief discussion of implementation and available software is also provided. PMID:26910586

Combined 3D-QSAR modeling and molecular docking study on azacycles CCR5 antagonists

NASA Astrophysics Data System (ADS)

Ji, Yongjun; Shu, Mao; Lin, Yong; Wang, Yuanqiang; Wang, Rui; Hu, Yong; Lin, Zhihua

2013-08-01

The beta chemokine receptor 5 (CCR5) is an attractive target for pharmaceutical industry in the HIV-1, inflammation and cancer therapeutic areas. In this study, we have developed quantitative structure activity relationship (QSAR) models for a series of 41 azacycles CCR5 antagonists using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and Topomer CoMFA methods. The cross-validated coefficient q2 values of 3D-QASR (CoMFA, CoMSIA, and Topomer CoMFA) methods were 0.630, 0.758, and 0.852, respectively, the non-cross-validated R2 values were 0.979, 0.978, and 0.990, respectively. Docking studies were also employed to determine the most probable binding mode. 3D contour maps and docking results suggested that bulky groups and electron-withdrawing groups on the core part would decrease antiviral activity. Furthermore, docking results indicated that H-bonds and π bonds were favorable for antiviral activities. Finally, a set of novel derivatives with predicted activities were designed.

New methods in iris recognition.

PubMed

Daugman, John

2007-10-01

This paper presents the following four advances in iris recognition: 1) more disciplined methods for detecting and faithfully modeling the iris inner and outer boundaries with active contours, leading to more flexible embedded coordinate systems; 2) Fourier-based methods for solving problems in iris trigonometry and projective geometry, allowing off-axis gaze to be handled by detecting it and "rotating" the eye into orthographic perspective; 3) statistical inference methods for detecting and excluding eyelashes; and 4) exploration of score normalizations, depending on the amount of iris data that is available in images and the required scale of database search. Statistical results are presented based on 200 billion iris cross-comparisons that were generated from 632500 irises in the United Arab Emirates database to analyze the normalization issues raised in different regions of receiver operating characteristic curves.

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

NASA Astrophysics Data System (ADS)

Yu, Tianli; Luo, Jiebo; Singhal, Amit; Ahuja, Narendra

2005-04-01

We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP"s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Fully-automated identification of fish species based on otolith contour: using short-time Fourier transform and discriminant analysis (STFT-DA).

PubMed

Salimi, Nima; Loh, Kar Hoe; Kaur Dhillon, Sarinder; Chong, Ving Ching

2016-01-01

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

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

Guo, Yiting; Dong, Bin; Wang, Bing

Purpose: Effective and accurate segmentation of the aortic valve (AV) from sequenced ultrasound (US) images remains a technical challenge because of intrinsic factors of ultrasound images that impact the quality and the continuous changes of shape and position of segmented objects. In this paper, a novel shape-constraint gradient Chan-Vese (GCV) model is proposed for segmenting the AV from time serial echocardiography. Methods: The GCV model is derived by incorporating the energy of the gradient vector flow into a CV model framework, where the gradient vector energy term is introduced by calculating the deviation angle between the inward normal force ofmore » the evolution contour and the gradient vector force. The flow force enlarges the capture range and enhances the blurred boundaries of objects. This is achieved by adding a circle-like contour (constructed using the AV structure region as a constraint shape) as an energy item to the GCV model through the shape comparison function. This shape-constrained energy can enhance the image constraint force by effectively connecting separate gaps of the object edge as well as driving the evolution contour to quickly approach the ideal object. Because of the slight movement of the AV in adjacent frames, the initial constraint shape is defined by users, with the other constraint shapes being derived from the segmentation results of adjacent sequence frames after morphological filtering. The AV is segmented from the US images by minimizing the proposed energy function. Results: To evaluate the performance of the proposed method, five assessment parameters were used to compare it with manual delineations performed by radiologists (gold standards). Three hundred and fifteen images acquired from nine groups were analyzed in the experiment. The area-metric overlap error rate was 6.89% ± 2.88%, the relative area difference rate 3.94% ± 2.63%, the average symmetric contour distance 1.08 ± 0.43 mm, the root mean square symmetric contour distance 1.37 ± 0.52 mm, and the maximum symmetric contour distance was 3.57 ± 1.72 mm. Conclusions: Compared with the CV model, as a result of the combination of the gradient vector and neighborhood shape information, this semiautomatic segmentation method significantly improves the accuracy and robustness of AV segmentation, making it feasible for improved segmentation of aortic valves from US images that have fuzzy boundaries.« less

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

Khoo, Eric L.H., E-mail: eric.khoo@roq.net.au; Schick, Karlissa; Plank, Ashley W.

Purpose: To assess whether an education program on CT and MRI prostate anatomy would reduce inter- and intraobserver prostate contouring variation among experienced radiation oncologists. Methods and Materials: Three patient CT and MRI datasets were selected. Five radiation oncologists contoured the prostate for each patient on CT first, then MRI, and again between 2 and 4 weeks later. Three education sessions were then conducted. The same contouring process was then repeated with the same datasets and oncologists. The observer variation was assessed according to changes in the ratio of the encompassing volume to intersecting volume (volume ratio [VR]), across setsmore » of target volumes. Results: For interobserver variation, there was a 15% reduction in mean VR with CT, from 2.74 to 2.33, and a 40% reduction in mean VR with MRI, from 2.38 to 1.41 after education. A similar trend was found for intraobserver variation, with a mean VR reduction for CT and MRI of 9% (from 1.51 to 1.38) and 16% (from 1.37 to 1.15), respectively. Conclusion: A well-structured education program has reduced both inter- and intraobserver prostate contouring variations. The impact was greater on MRI than on CT. With the ongoing incorporation of new technologies into routine practice, education programs for target contouring should be incorporated as part of the continuing medical education of radiation oncologists.« less

Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

PubMed Central

Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

Synthesis of Polysyllabic Sequences of Thai Tones Using a Generative Model of Fundamental Frequency Contours

NASA Astrophysics Data System (ADS)

Seresangtakul, Pusadee; Takara, Tomio

In this paper, the distinctive tones of Thai in running speech are studied. We present rules to synthesize F0 contours of Thai tones in running speech by using the generative model of F0 contours. Along with our method, the pitch contours of Thai polysyllabic words, both disyllabic and trisyllabic words, were analyzed. The coarticulation effect of Thai tones in running speech were found. Based on the analysis of the polysyllabic words using this model, rules are derived and applied to synthesize Thai polysyllabic tone sequences. We performed listening tests to evaluate intelligibility of the rules for Thai tones generation. The average intelligibility scores became 98.8%, and 96.6% for disyllabic and trisyllabic words, respectively. From these result, the rule of the tones' generation was shown to be effective. Furthermore, we constructed the connecting rules to synthesize suprasegmental F0 contours using the trisyllable training rules' parameters. The parameters of the first, the third, and the second syllables were selected and assigned to the initial, the ending, and the remaining syllables in a sentence, respectively. Even such a simple rule, the synthesized phrases/senetences were completely identified in listening tests. The MOSs (Mean Opinion Score) was 3.50 while the original and analysis/synthesis samples were 4.82 and 3.59, respectively.

Least-squares/parabolized Navier-Stokes procedure for optimizing hypersonic wind tunnel nozzles

NASA Technical Reports Server (NTRS)

Korte, John J.; Kumar, Ajay; Singh, D. J.; Grossman, B.

1991-01-01

A new procedure is demonstrated for optimizing hypersonic wind-tunnel-nozzle contours. The procedure couples a CFD computer code to an optimization algorithm, and is applied to both conical and contoured hypersonic nozzles for the purpose of determining an optimal set of parameters to describe the surface geometry. A design-objective function is specified based on the deviation from the desired test-section flow-field conditions. The objective function is minimized by optimizing the parameters used to describe the nozzle contour based on the solution to a nonlinear least-squares problem. The effect of the changes in the nozzle wall parameters are evaluated by computing the nozzle flow using the parabolized Navier-Stokes equations. The advantage of the new procedure is that it directly takes into account the displacement effect of the boundary layer on the wall contour. The new procedure provides a method for optimizing hypersonic nozzles of high Mach numbers which have been designed by classical procedures, but are shown to produce poor flow quality due to the large boundary layers present in the test section. The procedure is demonstrated by finding the optimum design parameters for a Mach 10 conical nozzle and a Mach 6 and a Mach 15 contoured nozzle.

Toward a standard for the evaluation of PET-Auto-Segmentation methods following the recommendations of AAPM task group No. 211: Requirements and implementation.

PubMed

Berthon, Beatrice; Spezi, Emiliano; Galavis, Paulina; Shepherd, Tony; Apte, Aditya; Hatt, Mathieu; Fayad, Hadi; De Bernardi, Elisabetta; Soffientini, Chiara D; Ross Schmidtlein, C; El Naqa, Issam; Jeraj, Robert; Lu, Wei; Das, Shiva; Zaidi, Habib; Mawlawi, Osama R; Visvikis, Dimitris; Lee, John A; Kirov, Assen S

2017-08-01

The aim of this paper is to define the requirements and describe the design and implementation of a standard benchmark tool for evaluation and validation of PET-auto-segmentation (PET-AS) algorithms. This work follows the recommendations of Task Group 211 (TG211) appointed by the American Association of Physicists in Medicine (AAPM). The recommendations published in the AAPM TG211 report were used to derive a set of required features and to guide the design and structure of a benchmarking software tool. These items included the selection of appropriate representative data and reference contours obtained from established approaches and the description of available metrics. The benchmark was designed in a way that it could be extendable by inclusion of bespoke segmentation methods, while maintaining its main purpose of being a standard testing platform for newly developed PET-AS methods. An example of implementation of the proposed framework, named PETASset, was built. In this work, a selection of PET-AS methods representing common approaches to PET image segmentation was evaluated within PETASset for the purpose of testing and demonstrating the capabilities of the software as a benchmark platform. A selection of clinical, physical, and simulated phantom data, including "best estimates" reference contours from macroscopic specimens, simulation template, and CT scans was built into the PETASset application database. Specific metrics such as Dice Similarity Coefficient (DSC), Positive Predictive Value (PPV), and Sensitivity (S), were included to allow the user to compare the results of any given PET-AS algorithm to the reference contours. In addition, a tool to generate structured reports on the evaluation of the performance of PET-AS algorithms against the reference contours was built. The variation of the metric agreement values with the reference contours across the PET-AS methods evaluated for demonstration were between 0.51 and 0.83, 0.44 and 0.86, and 0.61 and 1.00 for DSC, PPV, and the S metric, respectively. Examples of agreement limits were provided to show how the software could be used to evaluate a new algorithm against the existing state-of-the art. PETASset provides a platform that allows standardizing the evaluation and comparison of different PET-AS methods on a wide range of PET datasets. The developed platform will be available to users willing to evaluate their PET-AS methods and contribute with more evaluation datasets. © 2017 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Calculation of continuum damping of Alfvén eigenmodes in tokamak and stellarator equilibria

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

Bowden, G. W.; Hole, M. J.; Könies, A.

2015-09-15

In an ideal magnetohydrodynamic (MHD) plasma, shear Alfvén eigenmodes may experience dissipationless damping due to resonant interaction with the shear Alfvén continuum. This continuum damping can make a significant contribution to the overall growth/decay rate of shear Alfvén eigenmodes, with consequent implications for fast ion transport. One method for calculating continuum damping is to solve the MHD eigenvalue problem over a suitable contour in the complex plane, thereby satisfying the causality condition. Such an approach can be implemented in three-dimensional ideal MHD codes which use the Galerkin method. Analytic functions can be fitted to numerical data for equilibrium quantities inmore » order to determine the value of these quantities along the complex contour. This approach requires less resolution than the established technique of calculating damping as resistivity vanishes and is thus more computationally efficient. The complex contour method has been applied to the three-dimensional finite element ideal MHD Code for Kinetic Alfvén waves. In this paper, we discuss the application of the complex contour technique to calculate the continuum damping of global modes in tokamak as well as torsatron, W7-X and H-1NF stellarator cases. To the authors' knowledge, these stellarator calculations represent the first calculation of continuum damping for eigenmodes in fully three-dimensional equilibria. The continuum damping of global modes in W7-X and H-1NF stellarator configurations investigated is found to depend sensitively on coupling to numerous poloidal and toroidal harmonics.« less

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Systems and methods for measuring component matching

NASA Technical Reports Server (NTRS)

Courter, Kelly J. (Inventor); Slenk, Joel E. (Inventor)

2006-01-01

Systems and methods for measuring a contour match between adjacent components are disclosed. In one embodiment, at least two pressure sensors are located between adjacent components. Each pressure sensor is adapted to obtain a pressure measurement at a location a predetermined distance away from the other pressure sensors, and to output a pressure measurement for each sensor location. An output device is adapted to receive the pressure measurements from at least two pressure sensors and display the pressure measurements. In one aspect, the pressure sensors include flexible thin film pressure sensors. In accordance with other aspects of the invention, a method is provided for measuring a contour match between two interfacing components including measuring at least one pressure applied to at least one sensor between the interfacing components.

Application of the gingival contour plaque index: six-month plaque and gingivitis study.

PubMed

Scherl, Dale S; Bork, Kim; Coffman, Lori; Lowry, Stephen R; VanCleave, Misty

2009-01-01

The Gingival Contour Plaque Index (GCPI) is a recently introduced and validated method of measuring plaque accumulation in dogs. It focuses on plaque accumulated along the gingival margin. Plaque accumulation in this area leads to gingival inflammation and, potentially, periodontitis. A 6-month plaque and gingivitis study was conducted to demonstrate the clinical research application of the GCPI, and to ensure that documented quantification of plaque-reducing efficacy could be related to a reduction in gingivitis. Advantages of the GCPI method are the ability to quantify plaque accumulation in an awake dog with fewer research personnel and more efficient time usage.

Contour-Based Corner Detection and Classification by Using Mean Projection Transform

PubMed Central

Kahaki, Seyed Mostafa Mousavi; Nordin, Md Jan; Ashtari, Amir Hossein

2014-01-01

Image corner detection is a fundamental task in computer vision. Many applications require reliable detectors to accurately detect corner points, commonly achieved by using image contour information. The curvature definition is sensitive to local variation and edge aliasing, and available smoothing methods are not sufficient to address these problems properly. Hence, we propose Mean Projection Transform (MPT) as a corner classifier and parabolic fit approximation to form a robust detector. The first step is to extract corner candidates using MPT based on the integral properties of the local contours in both the horizontal and vertical directions. Then, an approximation of the parabolic fit is calculated to localize the candidate corner points. The proposed method presents fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques, especially in comparison with curvature scale space (CSS) methods. Moreover, a new evaluation metric, called accuracy of repeatability (AR), is introduced. AR combines repeatability and the localization error (Le) for finding the probability of correct detection in the target image. The output results exhibit better repeatability, localization, and AR for the detected points compared with the criteria in original and transformed images. PMID:24590354

Contour-based corner detection and classification by using mean projection transform.

PubMed

Kahaki, Seyed Mostafa Mousavi; Nordin, Md Jan; Ashtari, Amir Hossein

2014-02-28

Image corner detection is a fundamental task in computer vision. Many applications require reliable detectors to accurately detect corner points, commonly achieved by using image contour information. The curvature definition is sensitive to local variation and edge aliasing, and available smoothing methods are not sufficient to address these problems properly. Hence, we propose Mean Projection Transform (MPT) as a corner classifier and parabolic fit approximation to form a robust detector. The first step is to extract corner candidates using MPT based on the integral properties of the local contours in both the horizontal and vertical directions. Then, an approximation of the parabolic fit is calculated to localize the candidate corner points. The proposed method presents fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques, especially in comparison with curvature scale space (CSS) methods. Moreover, a new evaluation metric, called accuracy of repeatability (AR), is introduced. AR combines repeatability and the localization error (Le) for finding the probability of correct detection in the target image. The output results exhibit better repeatability, localization, and AR for the detected points compared with the criteria in original and transformed images.

Clinical evaluation of atlas and deep learning based automatic contouring for lung cancer.

PubMed

Lustberg, Tim; van Soest, Johan; Gooding, Mark; Peressutti, Devis; Aljabar, Paul; van der Stoep, Judith; van Elmpt, Wouter; Dekker, Andre

2018-02-01

Contouring of organs at risk (OARs) is an important but time consuming part of radiotherapy treatment planning. The aim of this study was to investigate whether using institutional created software-generated contouring will save time if used as a starting point for manual OAR contouring for lung cancer patients. Twenty CT scans of stage I-III NSCLC patients were used to compare user adjusted contours after an atlas-based and deep learning contour, against manual delineation. The lungs, esophagus, spinal cord, heart and mediastinum were contoured for this study. The time to perform the manual tasks was recorded. With a median time of 20 min for manual contouring, the total median time saved was 7.8 min when using atlas-based contouring and 10 min for deep learning contouring. Both atlas based and deep learning adjustment times were significantly lower than manual contouring time for all OARs except for the left lung and esophagus of the atlas based contouring. User adjustment of software generated contours is a viable strategy to reduce contouring time of OARs for lung radiotherapy while conforming to local clinical standards. In addition, deep learning contouring shows promising results compared to existing solutions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Attention to emotion modulates fMRI activity in human right superior temporal sulcus.

PubMed

Narumoto, J; Okada, T; Sadato, N; Fukui, K; Yonekura, Y

2001-10-01

A parallel neural network has been proposed for processing various types of information conveyed by faces including emotion. Using functional magnetic resonance imaging (fMRI), we tested the effect of the explicit attention to the emotional expression of the faces on the neuronal activity of the face-responsive regions. Delayed match to sample procedure was adopted. Subjects were required to match the visually presented pictures with regard to the contour of the face pictures, facial identity, and emotional expressions by valence (happy and fearful expressions) and arousal (fearful and sad expressions). Contour matching of the non-face scrambled pictures was used as a control condition. The face-responsive regions that responded more to faces than to non-face stimuli were the bilateral lateral fusiform gyrus (LFG), the right superior temporal sulcus (STS), and the bilateral intraparietal sulcus (IPS). In these regions, general attention to the face enhanced the activities of the bilateral LFG, the right STS, and the left IPS compared with attention to the contour of the facial image. Selective attention to facial emotion specifically enhanced the activity of the right STS compared with attention to the face per se. The results suggest that the right STS region plays a special role in facial emotion recognition within distributed face-processing systems. This finding may support the notion that the STS is involved in social perception.

Clustering Of Left Ventricular Wall Motion Patterns

NASA Astrophysics Data System (ADS)

Bjelogrlic, Z.; Jakopin, J.; Gyergyek, L.

1982-11-01

A method for detection of wall regions with similar motion was presented. A model based on local direction information was used to measure the left ventricular wall motion from cineangiographic sequence. Three time functions were used to define segmental motion patterns: distance of a ventricular contour segment from the mean contour, the velocity of a segment and its acceleration. Motion patterns were clustered by the UPGMA algorithm and by an algorithm based on K-nearest neighboor classification rule.

Pre-loading of components during laser peenforming

DOEpatents

Hackel, Lloyd A [Livermore, CA; Halpin, John M [Tracy, CA; Harris, Fritz B [Rocklin, CA

2003-12-30

A method and apparatus are provided for forming shapes and contours in metal sections by prestressing a workpiece and generating laser induced compressive stress on the surface of the metal workpiece. The step of prestressing the workpiece is carried out with a jig. The laser process can generate deep compressive stresses to shape even thick components without inducing unwanted tensile stress at the metal surface. The precision of the laser-induced stress enables exact prediction and subsequent contouring of parts.

Interface proliferation and the growth of labyrinths in a reaction-diffusion system

NASA Astrophysics Data System (ADS)

Goldstein, Raymond E.; Muraki, David J.; Petrich, Dean M.

1996-04-01

In the bistable regime of the FitzHugh-Nagumo model of reaction-diffusion systems, spatially homogeneous patterns may be nonlinearly unstable to the formation of compact "localized states." The formation of space-filling patterns from instabilities of such structures is studied in the context of a nonlocal contour dynamics model for the evolution of boundaries between high and low concentrations of the activator. An earlier heuristic derivation [D. M. Petrich and R. E. Goldstein,

A segmentation editing framework based on shape change statistics

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Vicory, Jared; Styner, Martin; Pizer, Stephen

2017-02-01

Segmentation is a key task in medical image analysis because its accuracy significantly affects successive steps. Automatic segmentation methods often produce inadequate segmentations, which require the user to manually edit the produced segmentation slice by slice. Because editing is time-consuming, an editing tool that enables the user to produce accurate segmentations by only drawing a sparse set of contours would be needed. This paper describes such a framework as applied to a single object. Constrained by the additional information enabled by the manually segmented contours, the proposed framework utilizes object shape statistics to transform the failed automatic segmentation to a more accurate version. Instead of modeling the object shape, the proposed framework utilizes shape change statistics that were generated to capture the object deformation from the failed automatic segmentation to its corresponding correct segmentation. An optimization procedure was used to minimize an energy function that consists of two terms, an external contour match term and an internal shape change regularity term. The high accuracy of the proposed segmentation editing approach was confirmed by testing it on a simulated data set based on 10 in-vivo infant magnetic resonance brain data sets using four similarity metrics. Segmentation results indicated that our method can provide efficient and adequately accurate segmentations (Dice segmentation accuracy increase of 10%), with very sparse contours (only 10%), which is promising in greatly decreasing the work expected from the user.

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

Peressutti, D; Schipaanboord, B; Kadir, T

Purpose: To investigate the effectiveness of atlas selection methods for improving atlas-based auto-contouring in radiotherapy planning. Methods: 275 H&N clinically delineated cases were employed as an atlas database from which atlases would be selected. A further 40 previously contoured cases were used as test patients against which atlas selection could be performed and evaluated. 26 variations of selection methods proposed in the literature and used in commercial systems were investigated. Atlas selection methods comprised either global or local image similarity measures, computed after rigid or deformable registration, combined with direct atlas search or with an intermediate template image. Workflow Boxmore » (Mirada-Medical, Oxford, UK) was used for all auto-contouring. Results on brain, brainstem, parotids and spinal cord were compared to random selection, a fixed set of 10 “good” atlases, and optimal selection by an “oracle” with knowledge of the ground truth. The Dice score and the average ranking with respect to the “oracle” were employed to assess the performance of the top 10 atlases selected by each method. Results: The fixed set of “good” atlases outperformed all of the atlas-patient image similarity-based selection methods (mean Dice 0.715 c.f. 0.603 to 0.677). In general, methods based on exhaustive comparison of local similarity measures showed better average Dice scores (0.658 to 0.677) compared to the use of either template image (0.655 to 0.672) or global similarity measures (0.603 to 0.666). The performance of image-based selection methods was found to be only slightly better than a random (0.645). Dice scores given relate to the left parotid, but similar results patterns were observed for all organs. Conclusion: Intuitively, atlas selection based on the patient CT is expected to improve auto-contouring performance. However, it was found that published approaches performed marginally better than random and use of a fixed set of representative atlases showed favourable performance. This research was funded via InnovateUK Grant 600277 as part of Eurostars Grant E!9297. DP,BS,MG,TK are employees of Mirada Medical Ltd.« less

Shaping the Landscape.

ERIC Educational Resources Information Center

Naturescope, 1987

1987-01-01

Provides background information on various agents that change the landscape. Includes teaching activities on weathering, water, wind and ice erosion, plate tectonics, sedimentation, deposition, mountain building, and determining contour lines. Contains reproducible handouts and worksheets for two of the activities. (TW)

Active contour configuration model for estimating the posterior ablative margin in image fusion of real-time ultrasound and 3D ultrasound or magnetic resonance images for radiofrequency ablation: an experimental study.

PubMed

Lee, Junkyo; Lee, Min Woo; Choi, Dongil; Cha, Dong Ik; Lee, Sunyoung; Kang, Tae Wook; Yang, Jehoon; Jo, Jaemoon; Bang, Won-Chul; Kim, Jongsik; Shin, Dongkuk

2017-12-21

The purpose of this study was to evaluate the accuracy of an active contour model for estimating the posterior ablative margin in images obtained by the fusion of real-time ultrasonography (US) and 3-dimensional (3D) US or magnetic resonance (MR) images of an experimental tumor model for radiofrequency ablation. Chickpeas (n=12) and bovine rump meat (n=12) were used as an experimental tumor model. Grayscale 3D US and T1-weighted MR images were pre-acquired for use as reference datasets. US and MR/3D US fusion was performed for one group (n=4), and US and 3D US fusion only (n=8) was performed for the other group. Half of the models in each group were completely ablated, while the other half were incompletely ablated. Hyperechoic ablation areas were extracted using an active contour model from real-time US images, and the posterior margin of the ablation zone was estimated from the anterior margin. After the experiments, the ablated pieces of bovine rump meat were cut along the electrode path and the cut planes were photographed. The US images with the estimated posterior margin were compared with the photographs and post-ablation MR images. The extracted contours of the ablation zones from 12 US fusion videos and post-ablation MR images were also matched. In the four models fused under real-time US with MR/3D US, compression from the transducer and the insertion of an electrode resulted in misregistration between the real-time US and MR images, making the estimation of the ablation zones less accurate than was achieved through fusion between real-time US and 3D US. Eight of the 12 post-ablation 3D US images were graded as good when compared with the sectioned specimens, and 10 of the 12 were graded as good in a comparison with nicotinamide adenine dinucleotide staining and histopathologic results. Estimating the posterior ablative margin using an active contour model is a feasible way of predicting the ablation area, and US/3D US fusion was more accurate than US/MR fusion.

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.

Redefining face contour with a novel anti-aging cosmetic product: an open-label, prospective clinical study

PubMed Central

Garre, Aurora; Martinez-Masana, Gemma; Piquero-Casals, Jaime; Granger, Corinne

2017-01-01

Background Skin aging is accelerated by multiple extrinsic factors: ultraviolet radiation, smoking and pollution increase oxidative activity, damaging cellular and extracellular components such as DNA, proteins, and lipids. With age, collagen and hyaluronic acid levels decline, resulting in loss of elasticity and moisture of the skin. Over time this damage leads to characteristic signs that make the skin look older: altered facial contour, sagging skin, wrinkles, and an uneven complexion. This study evaluated the anti-aging effects of a new facial cream formulated with carnosine, Alteromonas ferment extract, crosspolymer hyaluronic acid, and a tripeptide. Methods An open-label intra-individual study to assess the anti-aging efficacy of the investigational product in 33 women aged 45 to 65 years. The product was applied twice daily for 56 days. Facial contour and skin deformation, elasticity, hydration, and complexion were measured with specialized equipment at baseline and days 28 and 56. Additionally, subjects completed questionnaires at days 28 and 56 on the perceived efficacy and cosmetic characteristics of the product. Results After 56 days of use of the investigational product, a redefining effect was observed, with a significant decrease in sagging jawline (7%). Skin was significantly more hydrated (12%), firmer (29%), and more elastic (20%) (P<0.001 for all). On complexion assessment, skin texture (a measure of skin smoothness) and spots (brown and red skin lesions) also improved significantly (12% and 6% decrease, respectively). In the subjective self-evaluation, the majority of subjects reported that the skin was visibly tightened and more elastic, flexible, and moisturized (91%, 88%, 91%, and 90%, respectively). The product was well tolerated with no adverse events reported during the study. Conclusion This new cosmetic product demonstrated anti-aging effects after 56 days of use, most notably a redefined facial contour and improved complexion. It is a safe and effective anti-aging product. PMID:29180884

Gray matter segmentation of the spinal cord with active contours in MR images.

PubMed

Datta, Esha; Papinutto, Nico; Schlaeger, Regina; Zhu, Alyssa; Carballido-Gamio, Julio; Henry, Roland G

2017-02-15

Fully or partially automated spinal cord gray matter segmentation techniques for spinal cord gray matter segmentation will allow for pivotal spinal cord gray matter measurements in the study of various neurological disorders. The objective of this work was multi-fold: (1) to develop a gray matter segmentation technique that uses registration methods with an existing delineation of the cord edge along with Morphological Geodesic Active Contour (MGAC) models; (2) to assess the accuracy and reproducibility of the newly developed technique on 2D PSIR T1 weighted images; (3) to test how the algorithm performs on different resolutions and other contrasts; (4) to demonstrate how the algorithm can be extended to 3D scans; and (5) to show the clinical potential for multiple sclerosis patients. The MGAC algorithm was developed using a publicly available implementation of a morphological geodesic active contour model and the spinal cord segmentation tool of the software Jim (Xinapse Systems) for initial estimate of the cord boundary. The MGAC algorithm was demonstrated on 2D PSIR images of the C2/C3 level with two different resolutions, 2D T2* weighted images of the C2/C3 level, and a 3D PSIR image. These images were acquired from 45 healthy controls and 58 multiple sclerosis patients selected for the absence of evident lesions at the C2/C3 level. Accuracy was assessed though visual assessment, Hausdorff distances, and Dice similarity coefficients. Reproducibility was assessed through interclass correlation coefficients. Validity was assessed through comparison of segmented gray matter areas in images with different resolution for both manual and MGAC segmentations. Between MGAC and manual segmentations in healthy controls, the mean Dice similarity coefficient was 0.88 (0.82-0.93) and the mean Hausdorff distance was 0.61 (0.46-0.76) mm. The interclass correlation coefficient from test and retest scans of healthy controls was 0.88. The percent change between the manual segmentations from high and low-resolution images was 25%, while the percent change between the MGAC segmentations from high and low resolution images was 13%. Between MGAC and manual segmentations in MS patients, the average Dice similarity coefficient was 0.86 (0.8-0.92) and the average Hausdorff distance was 0.83 (0.29-1.37) mm. We demonstrate that an automatic segmentation technique, based on a morphometric geodesic active contours algorithm, can provide accurate and precise spinal cord gray matter segmentations on 2D PSIR images. We have also shown how this automated technique can potentially be extended to other imaging protocols. Copyright © 2016 Elsevier Inc. All rights reserved.

A novel magnetic resonance imaging segmentation technique for determining diffuse intrinsic pontine glioma tumor volume.

PubMed

Singh, Ranjodh; Zhou, Zhiping; Tisnado, Jamie; Haque, Sofia; Peck, Kyung K; Young, Robert J; Tsiouris, Apostolos John; Thakur, Sunitha B; Souweidane, Mark M

2016-11-01

OBJECTIVE Accurately determining diffuse intrinsic pontine glioma (DIPG) tumor volume is clinically important. The aims of the current study were to 1) measure DIPG volumes using methods that require different degrees of subjective judgment; and 2) evaluate interobserver agreement of measurements made using these methods. METHODS Eight patients from a Phase I clinical trial testing convection-enhanced delivery (CED) of a therapeutic antibody were included in the study. Pre-CED, post-radiation therapy axial T2-weighted images were analyzed using 2 methods requiring high degrees of subjective judgment (picture archiving and communication system [PACS] polygon and Volume Viewer auto-contour methods) and 1 method requiring a low degree of subjective judgment (k-means clustering segmentation) to determine tumor volumes. Lin's concordance correlation coefficients (CCCs) were calculated to assess interobserver agreement. RESULTS The CCCs of measurements made by 2 observers with the PACS polygon and the Volume Viewer auto-contour methods were 0.9465 (lower 1-sided 95% confidence limit 0.8472) and 0.7514 (lower 1-sided 95% confidence limit 0.3143), respectively. Both were considered poor agreement. The CCC of measurements made using k-means clustering segmentation was 0.9938 (lower 1-sided 95% confidence limit 0.9772), which was considered substantial strength of agreement. CONCLUSIONS The poor interobserver agreement of PACS polygon and Volume Viewer auto-contour methods highlighted the difficulty in consistently measuring DIPG tumor volumes using methods requiring high degrees of subjective judgment. k-means clustering segmentation, which requires a low degree of subjective judgment, showed better interobserver agreement and produced tumor volumes with delineated borders.

A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.

PubMed

Timp, Sheila; Karssemeijer, Nico

2004-05-01

Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area Az under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in Az values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant.

Model-based segmentation of hand radiographs

NASA Astrophysics Data System (ADS)

Weiler, Frank; Vogelsang, Frank

1998-06-01

An important procedure in pediatrics is to determine the skeletal maturity of a patient from radiographs of the hand. There is great interest in the automation of this tedious and time-consuming task. We present a new method for the segmentation of the bones of the hand, which allows the assessment of the skeletal maturity with an appropriate database of reference bones, similar to the atlas based methods. The proposed algorithm uses an extended active contour model for the segmentation of the hand bones, which incorporates a-priori knowledge of shape and topology of the bones in an additional energy term. This `scene knowledge' is integrated in a complex hierarchical image model, that is used for the image analysis task.

Fast retinal layer segmentation of spectral domain optical coherence tomography images

NASA Astrophysics Data System (ADS)

Zhang, Tianqiao; Song, Zhangjun; Wang, Xiaogang; Zheng, Huimin; Jia, Fucang; Wu, Jianhuang; Li, Guanglin; Hu, Qingmao

2015-09-01

An approach to segment macular layer thicknesses from spectral domain optical coherence tomography has been proposed. The main contribution is to decrease computational costs while maintaining high accuracy via exploring Kalman filtering, customized active contour, and curve smoothing. Validation on 21 normal volumes shows that 8 layer boundaries could be segmented within 5.8 s with an average layer boundary error <2.35 μm. It has been compared with state-of-the-art methods for both normal and age-related macular degeneration cases to yield similar or significantly better accuracy and is 37 times faster. The proposed method could be a potential tool to clinically quantify the retinal layer boundaries.

An automated skin segmentation of Breasts in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

PubMed

Lee, Chia-Yen; Chang, Tzu-Fang; Chang, Nai-Yun; Chang, Yeun-Chung

2018-04-18

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is used to diagnose breast disease. Obtaining anatomical information from DCE-MRI requires the skin be manually removed so that blood vessels and tumors can be clearly observed by physicians and radiologists; this requires considerable manpower and time. We develop an automated skin segmentation algorithm where the surface skin is removed rapidly and correctly. The rough skin area is segmented by the active contour model, and analyzed in segments according to the continuity of the skin thickness for accuracy. Blood vessels and mammary glands are retained, which remedies the defect of removing some blood vessels in active contours. After three-dimensional imaging, the DCE-MRIs without the skin can be used to see internal anatomical information for clinical applications. The research showed the Dice's coefficients of the 3D reconstructed images using the proposed algorithm and the active contour model for removing skins are 93.2% and 61.4%, respectively. The time performance of segmenting skins automatically is about 165 times faster than manually. The texture information of the tumors position with/without the skin is compared by the paired t-test yielded all p < 0.05, which suggested the proposed algorithm may enhance observability of tumors at the significance level of 0.05.

SU-E-J-110: A Novel Level Set Active Contour Algorithm for Multimodality Joint Segmentation/Registration Using the Jensen-Rényi Divergence.

PubMed

Markel, D; Naqa, I El; Freeman, C; Vallières, M

2012-06-01

To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. To present a novel joint segmentation/registration for multimodality image-guided and adaptive radiotherapy. A major challenge to this framework is the sensitivity of many segmentation or registration algorithms to noise. Presented is a level set active contour based on the Jensen-Renyi (JR) divergence to achieve improved noise robustness in a multi-modality imaging space. It was found that JR divergence when used for segmentation has an improved robustness to noise compared to using mutual information, or other entropy-based metrics. The MI metric failed at around 2/3 the noise power than the JR divergence. The JR divergence metric is useful for the task of joint segmentation/registration of multimodality images and shows improved results compared entropy based metric. The algorithm can be easily modified to incorporate non-intensity based images, which would allow applications into multi-modality and texture analysis. © 2012 American Association of Physicists in Medicine.

A new fractional order derivative based active contour model for colon wall segmentation

NASA Astrophysics Data System (ADS)

Chen, Bo; Li, Lihong C.; Wang, Huafeng; Wei, Xinzhou; Huang, Shan; Chen, Wensheng; Liang, Zhengrong

2018-02-01

Segmentation of colon wall plays an important role in advancing computed tomographic colonography (CTC) toward a screening modality. Due to the low contrast of CT attenuation around colon wall, accurate segmentation of the boundary of both inner and outer wall is very challenging. In this paper, based on the geodesic active contour model, we develop a new model for colon wall segmentation. First, tagged materials in CTC images were automatically removed via a partial volume (PV) based electronic colon cleansing (ECC) strategy. We then present a new fractional order derivative based active contour model to segment the volumetric colon wall from the cleansed CTC images. In this model, the regionbased Chan-Vese model is incorporated as an energy term to the whole model so that not only edge/gradient information but also region/volume information is taken into account in the segmentation process. Furthermore, a fractional order differentiation derivative energy term is also developed in the new model to preserve the low frequency information and improve the noise immunity of the new segmentation model. The proposed colon wall segmentation approach was validated on 16 patient CTC scans. Experimental results indicate that the present scheme is very promising towards automatically segmenting colon wall, thus facilitating computer aided detection of initial colonic polyp candidates via CTC.

Near-threshold equal-loudness contours for harbor seals (Phoca vitulina) derived from reaction times during underwater audiometry: a preliminary study.

PubMed

Kastelein, Ronald A; Wensveen, Paul J; Terhune, John M; de Jong, Christ A F

2011-01-01

Equal-loudness functions describe relationships between the frequencies of sounds and their perceived loudness. This pilot study investigated the possibility of deriving equal-loudness contours based on the assumption that sounds of equal perceived loudness elicit equal reaction times (RTs). During a psychoacoustic underwater hearing study, the responses of two young female harbor seals to tonal signals between 0.125 and 100 kHz were filmed. Frame-by-frame analysis was used to quantify RT (the time between the onset of the sound stimulus and the onset of movement of the seal away from the listening station). Near-threshold equal-latency contours, as surrogates for equal-loudness contours, were estimated from RT-level functions fitted to mean RT data. The closer the received sound pressure level was to the 50% detection hearing threshold, the more slowly the animals reacted to the signal (RT range: 188-982 ms). Equal-latency contours were calculated relative to the RTs shown by each seal at sound levels of 0, 10, and 20 dB above the detection threshold at 1 kHz. Fifty percent detection thresholds are obtained with well-trained subjects actively listening for faint familiar sounds. When calculating audibility ranges of sounds for harbor seals in nature, it may be appropriate to consider levels 20 dB above this threshold.

Counting Magnetic Bipoles on the Sun by Polarity Inversion

NASA Technical Reports Server (NTRS)

Jones, Harrison P.

2004-01-01

This paper presents a simple and efficient algorithm for deriving images of polarity inversion from NSO/Kitt Peak magnetograms without use of contouring routines and shows by example how these maps depend upon the spatial scale for filtering the raw data. Smaller filtering scales produce many localized closed contours in mixed polarity regions while supergranular and larger filtering scales produce more global patterns. The apparent continuity of an inversion line depends on how the spatial filtering is accomplished, but its shape depends only on scale. The total length of the magnetic polarity inversion contours varies as a power law of the filter scale with fractal dimension of order 1.9. The amplitude but nut the exponent of this power-law relation varies with solar activity. The results are compared to similar analyses of areal distributions of bipolar magnetic regions.

Revision of empirical electric field modeling in the inner magnetosphere using Cluster data

NASA Astrophysics Data System (ADS)

Matsui, H.; Torbert, R. B.; Spence, H. E.; Khotyaintsev, Yu. V.; Lindqvist, P.-A.

2013-07-01

Using Cluster data from the Electron Drift (EDI) and the Electric Field and Wave (EFW) instruments, we revise our empirically-based, inner-magnetospheric electric field (UNH-IMEF) model at 22.662 mV/m; Kp<1, 1≤Kp<2, 2≤Kp<3, 3≤Kp<4, 4≤Kp<5, and Kp≥4+. Patterns consist of one set of data and processing for smaller activities, and another for higher activities. As activity increases, the skewed potential contour related to the partial ring current appears on the nightside. With the revised analysis, we find that the skewed potential contours get clearer and potential contours get denser on the nightside and morningside. Since the fluctuating components are not negligible, standard deviations from the modeled values are included in the model. In this study, we perform validation of the derived model more extensively. We find experimentally that the skewed contours are located close to the last closed equipotential, consistent with previous theories. This gives physical context to our model and serves as one validation effort. As another validation effort, the derived results are compared with other models/measurements. From these comparisons, we conclude that our model has some clear advantages over the others.

An evaluation of the contouring abilities of medical dosimetry students for the anatomy of a prostate cancer patient

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

Collins, Kevin S., E-mail: kscollin@siu.edu

2012-10-01

Prostate cancer is one of the most common diseases treated in a radiation oncology department. One of the major predictors of the treatment outcome and patient side effects is the accuracy of the anatomical contours for the treatment plan. Therefore, the purpose of this study was to determine which anatomical structures are most often contoured correctly and incorrectly by medical dosimetry students. The author also wanted to discover whether a review of the contouring rules would increase contouring accuracy. To achieve this, a male computed tomography dataset consisting of 72 transverse slices was sent to students for contouring. The studentsmore » were instructed to import this dataset into their treatment planning system and contour the following structures: skin, bladder, rectum, prostate, penile bulb, seminal vesicles, left femoral head, and right femoral head. Upon completion of the contours, the contour file was evaluated against a 'gold standard' contour set using StructSure software (Standard Imaging, Inc). A review of the initial contour results was conducted and then students were instructed to contour the dataset a second time. The results of this study showed significant differences between contouring sessions. These results and the standardization of contouring rules should benefit all individuals who participate in the treatment planning of cancer patients.« less

SU-F-J-88: Comparison of Two Deformable Image Registration Algorithms for CT-To-CT Contour Propagation

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

Gopal, A; Xu, H; Chen, S

Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagationmore » was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS < 0.35, RQS > 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in contour propagation.« less

Perceptual representation and effectiveness of local figure–ground cues in natural contours

PubMed Central

Sakai, Ko; Matsuoka, Shouhei; Kurematsu, Ken; Hatori, Yasuhiro

2015-01-01

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure–ground segregation. Although previous studies have reported local contour features that evoke figure–ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure–ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure–ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure–ground perception with natural contours when the other cues coexist with equal probability including contradictory cases. PMID:26579057

Perceptual representation and effectiveness of local figure-ground cues in natural contours.

PubMed

Sakai, Ko; Matsuoka, Shouhei; Kurematsu, Ken; Hatori, Yasuhiro

2015-01-01

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure-ground segregation. Although previous studies have reported local contour features that evoke figure-ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure-ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure-ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure-ground perception with natural contours when the other cues coexist with equal probability including contradictory cases.

A new technique for correcting cryptotia: bolster external fixation method.

PubMed

Qing, Yong; Cen, Ying; Yu, Rong; Xu, Xuewen

2010-11-01

Cryptotia is a congenital auricular deformity in which the upper third of the auricle is buried under the temporal skin. There is no standard surgical method to correct cryptotia. This study is aimed at devising a new surgical method to correct cryptotia with good auricular contour and inconspicuous scar. We retrospectively reviewed 8 patients diagnosed with cryptotia in West China Hospital between 2006 and 2009. All of them received this new surgical method to correct cryptotia. The follow-up period ranged from 6 months to 1 year. All patients possessed good auricular contour and sufficient skin for release of the upper part of the auricle without the need for a skin graft or local skin flap transferred. All patients possessed deep auriculotemporal sulci and inconspicuous scars. There were no complications, and cryptotia did not recur in any patient.

An automated and robust image processing algorithm for glaucoma diagnosis from fundus images using novel blood vessel tracking and bend point detection.

PubMed

M, Soorya; Issac, Ashish; Dutta, Malay Kishore

2018-02-01

Glaucoma is an ocular disease which can cause irreversible blindness. The disease is currently identified using specialized equipment operated by optometrists manually. The proposed work aims to provide an efficient imaging solution which can help in automating the process of Glaucoma diagnosis using computer vision techniques from digital fundus images. The proposed method segments the optic disc using a geometrical feature based strategic framework which improves the detection accuracy and makes the algorithm invariant to illumination and noise. Corner thresholding and point contour joining based novel methods are proposed to construct smooth contours of Optic Disc. Based on a clinical approach as used by ophthalmologist, the proposed algorithm tracks blood vessels inside the disc region and identifies the points at which first vessel bend from the optic disc boundary and connects them to obtain the contours of Optic Cup. The proposed method has been compared with the ground truth marked by the medical experts and the similarity parameters, used to determine the performance of the proposed method, have yield a high similarity of segmentation. The proposed method has achieved a macro-averaged f-score of 0.9485 and accuracy of 97.01% in correctly classifying fundus images. The proposed method is clinically significant and can be used for Glaucoma screening over a large population which will work in a real time. Copyright © 2017 Elsevier B.V. All rights reserved.

A non-conventional watershed partitioning method for semi-distributed hydrological modelling: the package ALADHYN

NASA Astrophysics Data System (ADS)

Menduni, Giovanni; Pagani, Alessandro; Rulli, Maria Cristina; Rosso, Renzo

2002-02-01

The extraction of the river network from a digital elevation model (DEM) plays a fundamental role in modelling spatially distributed hydrological processes. The present paper deals with a new two-step procedure based on the preliminary identification of an ideal drainage network (IDN) from contour lines through a variable mesh size, and the further extraction of the actual drainage network (AND) from the IDN using land morphology. The steepest downslope direction search is used to identify individual channels, which are further merged into a network path draining to a given node of the IDN. The contributing area, peaks and saddles are determined by means of a steepest upslope direction search. The basin area is thus partitioned into physically based finite elements enclosed by irregular polygons. Different methods, i.e. the constant and variable threshold area methods, the contour line curvature method, and a topologic method descending from the Hortonian ordering scheme, are used to extract the ADN from the IDN. The contour line curvature method is shown to provide the most appropriate method from a comparison with field surveys. Using the ADN one can model the hydrological response of any sub-basin using a semi-distributed approach. The model presented here combines storm abstraction by the SCS-CN method with surface runoff routing as a geomorphological dispersion process. This is modelled using the gamma instantaneous unit hydrograph as parameterized by river geomorphology. The results are implemented using a project-oriented software facility for the Analysis of LAnd Digital HYdrological Networks (ALADHYN).

Impacts of Sigma Coordinates on the Euler and Navier-Stokes Equations using Continuous Galerkin Methods

DTIC Science & Technology

2009-03-01

the 1- D local basis functions. The 1-D Lagrange polynomial local basis function, using Legendre -Gauss-Lobatto interpolation points, was defined by...cases were run using 10th order polynomials , with contours from -0.05 to 0.525 K with an interval of 0.025 K...after 700 s for reso- lutions: (a) 20, (b) 10, and (c) 5 m. All cases were run using 10th order polynomials , with contours from -0.05 to 0.525 K

Aeromechanics and Vehicle Configuration Demonstrations. Volume 2: Understanding Vehicle Sizing, Aeromechanics and Configuration Trades, Risks, and Issues for Next-Generations Access to Space Vehicles

DTIC Science & Technology

2014-01-01

and proportional correctors. The weighting function evaluates nearby data samples to determine the utility of each correction style , eliminating the...sparse methods may be of use. As for other multi-fidelity techniques, true cokriging in the style described by geo-statisticians[93] is beyond the...sampling style between sampling points predicted to fall near the contour and sampling points predicted to be farther from the contour but with

Application Of Holographic Interferometry For Investigation Of Microroughness Of Engineering Surfaces

NASA Astrophysics Data System (ADS)

Lech, Marek; Mruk, Irena; Stupnicki, Jacek

1985-01-01

The paper describes an improved immersion method of holographic interferometry /IMHI/ adjusted for studies of roughness of engineering surfaces. Special optical arrangement, with two types of immersion cells and adequate technique of preparing transparent replicas reproducting with high fidelity details of differently machined surfaces was elaborated. It permits to obtain the contour maps of the surface asperities with intervals between the planes of succesive contour lines within a range of 1 μm. The results obtained for some engineering surfaces are given.

TU-CD-BRA-04: Evaluation of An Atlas-Based Segmentation Method for Prostate and Peripheral Zone Regions On MRI

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

Nelson, AS; Piper, J; Curry, K

2015-06-15

Purpose: Prostate MRI plays an important role in diagnosis, biopsy guidance, and therapy planning for prostate cancer. Prostate MRI contours can be used to aid in image fusion for ultrasound biopsy guidance and delivery of radiation. Our goal in this study is to evaluate an automatic atlas-based segmentation method for generating prostate and peripheral zone (PZ) contours on MRI. Methods: T2-weighted MRIs were acquired on 3T-Discovery MR750 System (GE, Milwaukee). The Volumes of Interest (VOIs): prostate and PZ were outlined by an expert radiation oncologist and used to create an atlas library for atlas-based segmentation. The atlas-segmentation accuracy was evaluatedmore » using a leave-one-out analysis. The method involved automatically finding the atlas subject that best matched the test subject followed by a normalized intensity-based free-form deformable registration of the atlas subject to the test subject. The prostate and PZ contours were transformed to the test subject using the same deformation. For each test subject the three best matches were used and the final contour was combined using Majority Vote. The atlas-segmentation process was fully automatic. Dice similarity coefficients (DSC) and mean Hausdorff values were used for comparison. Results: VOIs contours were available for 28 subjects. For the prostate, the atlas-based segmentation method resulted in an average DSC of 0.88+/−0.08 and a mean Hausdorff distance of 1.1+/−0.9mm. The number of patients (#) in DSC ranges are as follows: 0.60–0.69(1), 0.70–0.79(2), 0.80–0.89(13), >0.89(11). For the PZ, the average DSC was 0.72+/−0.17 and average Hausdorff of 0.9+/−0.9mm. The number of patients (#) in DSC ranges are as follows: <0.60(4), 0.60–0.69(6), 0.70–0.79(7), 0.80–0.89(9), >0.89(1). Conclusion: The MRI atlas-based segmentation method achieved good results for both the whole prostate and PZ compared to expert defined VOIs. The technique is fast, fully automatic, and has the potential to provide significant time savings for prostate VOI definition. AS Nelson and J Piper are partial owners of MIM Software, Inc. AS Nelson, J Piper, K Curry, and A Swallen are current employees at MIM Software, Inc.« less

TH-AB-BRA-04: Dosimetric Evaluation of MR-Guided HDR Brachytherapy Planning for Cervical Cancer

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

Kamio, Y; Barkati, M; Beliveau-Nadeau, D

2016-06-15

Purpose: To perform a retrospective study on 16 patients that had both CT and T2-weighted MR scans done at first fraction using the Utrecht CT/MR applicator (Elekta Brachytherapy) in order to evaluate uncertainties associated with an MR-only planning workflow. Methods: MR-workflow uncertainties were classified in three categories: reconstruction, registration and contouring. A systematic comparison of the CT and MR contouring, manual reconstruction and optimization process was performed to evaluate the impact of these uncertainties on the recommended GEC ESTRO DVH parameters: D90% and V100% for HR-CTV as well as D2cc for bladder, rectum, sigmoid colon and small bowel. This comparisonmore » was done using the following four steps: 1. Catheter reconstruction done on MR images with original CT-plan contours and dwell times. 2. OAR contours adjusted on MR images with original CT-plan reconstruction and dwell times. 3. Both reconstruction and contours done on MR images with original CT-plan dwell times. 4. Entire MR-based workflow optimized dwell times reimported to the original CT-plan. Results: The MR-based reconstruction process showed average D2cc deviations of 4.5 ± 3.0%, 1.5 ± 2.0%, 2.5 ± 2.0% and 2.0 ± 1.0% for the bladder, rectum, sigmoid colon and small bowels respectively with a maximum of 10%, 6%, 6% and 4%. The HR-CTV’s D90% and V100% average deviations was found to be 4.0 ± 3.0%, and 2.0 ± 2.0% respectively with a maximum of 10% and 6%. Adjusting contours on MR-images was found to have a similar impact. Finally, the optimized MR-based workflow dwell times were found to still give acceptable plans when re-imported to the original CT-plan which validated the entire workflow. Conclusion: This work illustrates a systematic validation method for centers wanting to move towards an MR-only workflow. This work will be expanded to model based reconstruction, PD-weighted images and other types of applicators.« less

Automated consensus contour building for prostate MRI.

PubMed

Khalvati, Farzad

2014-01-01

Inter-observer variability is the lack of agreement among clinicians in contouring a given organ or tumour in a medical image. The variability in medical image contouring is a source of uncertainty in radiation treatment planning. Consensus contour of a given case, which was proposed to reduce the variability, is generated by combining the manually generated contours of several clinicians. However, having access to several clinicians (e.g., radiation oncologists) to generate a consensus contour for one patient is costly. This paper presents an algorithm that automatically generates a consensus contour for a given case using the atlases of different clinicians. The algorithm was applied to prostate MR images of 15 patients manually contoured by 5 clinicians. The automatic consensus contours were compared to manual consensus contours where a median Dice similarity coefficient (DSC) of 88% was achieved.

Quantifying Contaminant Mass for the Feasibility Study of the DuPont Chambers Works FUSRAP Site - 13510

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

Young, Carl; Rahman, Mahmudur; Johnson, Ann

2013-07-01

The U.S. Army Corps of Engineers (USACE) - Philadelphia District is conducting an environmental restoration at the DuPont Chambers Works in Deepwater, New Jersey under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Discrete locations are contaminated with natural uranium, thorium-230 and radium-226. The USACE is proposing a preferred remedial alternative consisting of excavation and offsite disposal to address soil contamination followed by monitored natural attenuation to address residual groundwater contamination. Methods were developed to quantify the error associated with contaminant volume estimates and use mass balance calculations of the uranium plume to estimate the removal efficiency of the proposedmore » alternative. During the remedial investigation, the USACE collected approximately 500 soil samples at various depths. As the first step of contaminant mass estimation, soil analytical data was segmented into several depth intervals. Second, using contouring software, analytical data for each depth interval was contoured to determine lateral extent of contamination. Six different contouring algorithms were used to generate alternative interpretations of the lateral extent of the soil contamination. Finally, geographical information system software was used to produce a three dimensional model in order to present both lateral and vertical extent of the soil contamination and to estimate the volume of impacted soil for each depth interval. The average soil volume from all six contouring methods was used to determine the estimated volume of impacted soil. This method also allowed an estimate of a standard deviation of the waste volume estimate. It was determined that the margin of error for the method was plus or minus 17% of the waste volume, which is within the acceptable construction contingency for cost estimation. USACE collected approximately 190 groundwater samples from 40 monitor wells. It is expected that excavation and disposal of contaminated soil will remove the contaminant source zone and significantly reduce contaminant concentrations in groundwater. To test this assumption, a mass balance evaluation was performed to estimate the amount of dissolved uranium that would remain in the groundwater after completion of soil excavation. As part of this evaluation, average groundwater concentrations for the pre-excavation and post-excavation aquifer plume area were calculated to determine the percentage of plume removed during excavation activities. In addition, the volume of the plume removed during excavation dewatering was estimated. The results of the evaluation show that approximately 98% of the aqueous uranium would be removed during the excavation phase. The USACE expects that residual levels of contamination will remain in groundwater after excavation of soil but at levels well suited for the selection of excavation combined with monitored natural attenuation as a preferred alternative. (authors)« less

The prognostic value of functional and anatomical parameters for the selection of patients receiving yttrium-90 microspheres for the treatment of liver cancer

NASA Astrophysics Data System (ADS)

Mesoloras, Geraldine

Yttrium-90 (90Y) microsphere therapy is being utilized as a treatment option for patients with primary and metastatic liver cancer due to its ability to target tumors within the liver. The success of this treatment is dependent on many factors, including the extent and type of disease and the nature of prior treatments received. Metabolic activity, as determined by PET imaging, may correlate with the number of viable cancer cells and reflect changes in viable cancer cell volume. However, contouring of PET images by hand is labor intensive and introduces an element of irreproducibility into the determination of functional target/tumor volume (FTV). A computer-assisted method to aid in the automatic contouring of FTV has the potential to substantially improve treatment individualization and outcome assessment. Commercial software to determine FTV in FDG-avid primary and metastatic liver tumors has been evaluated and optimized. Volumes determined using the automated technique were compared to those from manually drawn contours identified using the same cutoff in the standard uptake value (SUV). The reproducibility of FTV is improved through the introduction of an optimal threshold value determined from phantom experiments. Application of the optimal threshold value from the phantom experiments to patient scans was in good agreement with hand-drawn determinations of the FTV. It is concluded that computer-assisted contouring of the FTV for primary and metastatic liver tumors improves reproducibility and increases accuracy, especially when combined with the selection of an optimal SUV threshold determined from phantom experiments. A method to link the pre-treatment assessment of functional (PET based) and anatomical (CT based) parameters to post-treatment survival and time to progression was evaluated in 22 patients with colorectal cancer liver metastases treated using 90Y microspheres and chemotherapy. The values for pre-treatment parameters that were the best predictors of response were determined for FTV, anatomical tumor volume, total lesion glycolysis, and the tumor marker, CEA. Of the parameters considered, the best predictors of response were found to be pre-treatment FTV ≤153 cm3, ATV ≤163 cm3, TLG ≤144 g in the chemo-SIRT treated field, and CEA ≤11.6 ng/mL.

Critical discussion of evaluation parameters for inter-observer variability in target definition for radiation therapy.

PubMed

Fotina, I; Lütgendorf-Caucig, C; Stock, M; Pötter, R; Georg, D

2012-02-01

Inter-observer studies represent a valid method for the evaluation of target definition uncertainties and contouring guidelines. However, data from the literature do not yet give clear guidelines for reporting contouring variability. Thus, the purpose of this work was to compare and discuss various methods to determine variability on the basis of clinical cases and a literature review. In this study, 7 prostate and 8 lung cases were contoured on CT images by 8 experienced observers. Analysis of variability included descriptive statistics, calculation of overlap measures, and statistical measures of agreement. Cross tables with ratios and correlations were established for overlap parameters. It was shown that the minimal set of parameters to be reported should include at least one of three volume overlap measures (i.e., generalized conformity index, Jaccard coefficient, or conformation number). High correlation between these parameters and scatter of the results was observed. A combination of descriptive statistics, overlap measure, and statistical measure of agreement or reliability analysis is required to fully report the interrater variability in delineation.

Closed geometric models in medical applications

NASA Astrophysics Data System (ADS)

Jagannathan, Lakshmipathy; Nowinski, Wieslaw L.; Raphel, Jose K.; Nguyen, Bonnie T.

1996-04-01

Conventional surface fitting methods give twisted surfaces and complicates capping closures. This is a typical character of surfaces that lack rectangular topology. We suggest an algorithm which overcomes these limitations. The analysis of the algorithm is presented with experimental results. This algorithm assumes the mass center lying inside the object. Both capping closure and twisting are results of inadequate information on the geometric proximity of the points and surfaces which are proximal in the parametric space. Geometric proximity at the contour level is handled by mapping the points along the contour onto a hyper-spherical space. The resulting angular gradation with respect to the centroid is monotonic and hence avoids the twisting problem. Inter-contour geometric proximity is achieved by partitioning the point set based on the angle it makes with the respective centroids. Avoidance of capping complications is achieved by generating closed cross curves connecting curves which are reflections about the abscissa. The method is of immense use for the generation of the deep cerebral structures and is applied to the deep structures generated from the Schaltenbrand- Wahren brain atlas.

SU-E-T-182: Feasibility of Dose Painting by Numbers in Proton Therapy with Contour-Driven Plan Optimization

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

Montero, A Barragan; Differding, S; Lee, J

Purpose: The work aims to 1) prove the feasibility of dose painting by numbers (DPBN) in proton therapy with usual contour-driven plan optimization and 2) compare the achieved plan quality to that of rotational IMRT. Methods: For two patients with head and neck cancers, voxel-by-voxel prescription to the target volume (PTV-PET) was calculated from {sup 18} FDG-PET images and converted to contour-based prescription by defining several sub-contours. Treatments were planned with RayStation (RaySearch Laboratories, Sweden) and proton pencil beam scanning modality. In order to determine the optimal plan parameters to approach the DPBN prescription, the effect of the number ofmore » fields, number of sub-contours and use of range shifter were tested separately on each patient. The number of sub-contours were increased from 3 to 11 while the number of fields were set to 3, 5, 7 and 9. Treatment plans were also optimized on two rotational IMRT systems (TomoTherapy and Varian RapidArc) using previously published guidelines. Results: For both patients, more than 99% of the PTV-PET received at least 95% of the prescribed dose while less than 1% of the PTV-PET received more than 105%, which demonstrates the feasibility of the treatment. Neither the use of a range shifter nor the increase of the number of fields had a significant influence on PTV coverage. Plan quality increased when increasing number of fields up to 7 or 9 and slightly decreased for a bigger number of sub-contours. Good OAR sparing is achieved while keeping high plan quality. Finally, proton therapy achieved significantly better plan quality than rotational IMRT. Conclusion: Voxel-by-voxel prescriptions can be approximated accurately in proton therapy using a contour-driven optimization. Target coverage is nearly insensitive to the number of fields and the use of a range shifter. Finally, plan quality assessment confirmed the superiority of proton therapy compared to rotational IMRT.« less

SU-E-J-134: Optimizing Technical Parameters for Using Atlas Based Automatic Segmentation for Evaluation of Contour Accuracy Experience with Cardiac Structures From NRG Oncology/RTOG 0617

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

Yu, J; Gong, Y; Bar-Ad, V

Purpose: Accurate contour delineation is crucial for radiotherapy. Atlas based automatic segmentation tools can be used to increase the efficiency of contour accuracy evaluation. This study aims to optimize technical parameters utilized in the tool by exploring the impact of library size and atlas number on the accuracy of cardiac contour evaluation. Methods: Patient CT DICOMs from RTOG 0617 were used for this study. Five experienced physicians delineated the cardiac structures including pericardium, atria and ventricles following an atlas guideline. The consistency of cardiac structured delineation using the atlas guideline was verified by a study with four observers and seventeenmore » patients. The CT and cardiac structure DICOM files were then used for the ABAS technique.To study the impact of library size (LS) and atlas number (AN) on automatic contour accuracy, automatic contours were generated with varied technique parameters for five randomly selected patients. Three LS (20, 60, and 100) were studied using commercially available software. The AN was four, recommended by the manufacturer. Using the manual contour as the gold standard, Dice Similarity Coefficient (DSC) was calculated between the manual and automatic contours. Five-patient averaged DSCs were calculated for comparison for each cardiac structure.In order to study the impact of AN, the LS was set 100, and AN was tested from one to five. The five-patient averaged DSCs were also calculated for each cardiac structure. Results: DSC values are highest when LS is 100 and AN is four. The DSC is 0.90±0.02 for pericardium, 0.75±0.06 for atria, and 0.86±0.02 for ventricles. Conclusion: By comparing DSC values, the combination AN=4 and LS=100 gives the best performance. This project was supported by NCI grants U24CA12014, U24CA180803, U10CA180868, U10CA180822, PA CURE grant and Bristol-Myers Squibb and Eli Lilly.« less

Is interpolation cognitively encapsulated? Measuring the effects of belief on Kanizsa shape discrimination and illusory contour formation

PubMed Central

Keane, Brian P.; Lu, Hongjing; Papathomas, Thomas V.; Silverstein, Steven M.; Kellman, Philip J.

2012-01-01

Contour interpolation is a perceptual process that fills-in missing edges on the basis of how surrounding edges (inducers) are spatiotemporally related. Cognitive encapsulation refers to the degree to which perceptual mechanisms act in isolation from beliefs, expectations, and utilities (Pylyshyn, 1999). Is interpolation encapsulated from belief? We addressed this question by having subjects discriminate briefly-presented, partially-visible fat and thin shapes, the edges of which either induced or did not induce illusory contours (relatable and non-relatable conditions, respectively). Half the trials in each condition incorporated task-irrelevant distractor lines, known to disrupt the filling-in of contours. Half of the observers were told that the visible parts of the shape belonged to a single thing (group strategy); the other half were told that the visible parts were disconnected (ungroup strategy). It was found that distractor lines strongly impaired performance in the relatable condition, but minimally in the non-relatable condition; that strategy did not alter the effects of the distractor lines for either the relatable or non-relatable stimuli; and that cognitively grouping relatable fragments improved performance whereas cognitively grouping non-relatable fragments did not. These results suggest that 1) filling-in effects during illusory contour formation cannot be easily removed via strategy; 2) filling-in effects cannot be easily manufactured from stimuli that fail to elicit interpolation; and 3) actively grouping fragments can readily improve discrimination performance, but only when those fragments form interpolated contours. Taken together, these findings indicate that discriminating filled-in shapes depends on strategy but filling-in itself may be encapsulated from belief. PMID:22440789

Sulci segmentation using geometric active contours

NASA Astrophysics Data System (ADS)

Torkaman, Mahsa; Zhu, Liangjia; Karasev, Peter; Tannenbaum, Allen

2017-02-01

Sulci are groove-like regions lying in the depth of the cerebral cortex between gyri, which together, form a folded appearance in human and mammalian brains. Sulci play an important role in the structural analysis of the brain, morphometry (i.e., the measurement of brain structures), anatomical labeling and landmark-based registration.1 Moreover, sulcal morphological changes are related to cortical thickness, whose measurement may provide useful information for studying variety of psychiatric disorders. Manually extracting sulci requires complying with complex protocols, which make the procedure both tedious and error prone.2 In this paper, we describe an automatic procedure, employing geometric active contours, which extract the sulci. Sulcal boundaries are obtained by minimizing a certain energy functional whose minimum is attained at the boundary of the given sulci.

X-ray Crystal Structure of Aristolochene Synthase from Aspergillus terreus and Evolution of Templates for the Cyclization of Farnesyl Diphosphate

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

Shishova,E.; Di Costanzo, L.; Cane, D.

2007-01-01

Aristolochene synthase from Aspergillus terreus catalyzes the cyclization of the universal sesquiterpene precursor, farnesyl diphosphate, to form the bicyclic hydrocarbon aristolochene. The 2.2 {angstrom} resolution X-ray crystal structure of aristolochene synthase reveals a tetrameric quaternary structure in which each subunit adopts the {alpha}-helical class I terpene synthase fold with the active site in the 'open', solvent-exposed conformation. Intriguingly, the 2.15 {angstrom} resolution crystal structure of the complex with Mg{sup 2+}{sub 3}-pyrophosphate reveals ligand binding only to tetramer subunit D, which is stabilized in the 'closed' conformation required for catalysis. Tetramer assembly may hinder conformational changes required for the transition frommore » the inactive open conformation to the active closed conformation, thereby accounting for the attenuation of catalytic activity with an increase in enzyme concentration. In both conformations, but especially in the closed conformation, the active site contour is highly complementary in shape to that of aristolochene, and a catalytic function is proposed for the pyrophosphate anion based on its orientation with regard to the presumed binding mode of aristolochene. A similar active site contour is conserved in aristolochene synthase from Penicillium roqueforti despite the substantial divergent evolution of these two enzymes, while strikingly different active site contours are found in the sesquiterpene cyclases 5-epi-aristolochene synthase and trichodiene synthase. Thus, the terpenoid cyclase active site plays a critical role as a template in binding the flexible polyisoprenoid substrate in the proper conformation for catalysis. Across the greater family of terpenoid cyclases, this template is highly evolvable within a conserved {alpha}-helical fold for the synthesis of terpene natural products of diverse structure and stereochemistry.« less

[Development of a Software for Automatically Generated Contours in Eclipse TPS].

PubMed

Xie, Zhao; Hu, Jinyou; Zou, Lian; Zhang, Weisha; Zou, Yuxin; Luo, Kelin; Liu, Xiangxiang; Yu, Luxin

2015-03-01

The automatic generation of planning targets and auxiliary contours have achieved in Eclipse TPS 11.0. The scripting language autohotkey was used to develop a software for automatically generated contours in Eclipse TPS. This software is named Contour Auto Margin (CAM), which is composed of operational functions of contours, script generated visualization and script file operations. RESULTS Ten cases in different cancers have separately selected, in Eclipse TPS 11.0 scripts generated by the software could not only automatically generate contours but also do contour post-processing. For different cancers, there was no difference between automatically generated contours and manually created contours. The CAM is a user-friendly and powerful software, and can automatically generated contours fast in Eclipse TPS 11.0. With the help of CAM, it greatly save plan preparation time and improve working efficiency of radiation therapy physicists.

Design optimization of highly asymmetrical layouts by 2D contour metrology

NASA Astrophysics Data System (ADS)

Hu, C. M.; Lo, Fred; Yang, Elvis; Yang, T. H.; Chen, K. C.

2018-03-01

As design pitch shrinks to the resolution limit of up-to-date optical lithography technology, the Critical Dimension (CD) variation tolerance has been dramatically decreased for ensuring the functionality of device. One of critical challenges associates with the narrower CD tolerance for whole chip area is the proximity effect control on asymmetrical layout environments. To fulfill the tight CD control of complex features, the Critical Dimension Scanning Electron Microscope (CD-SEM) based measurement results for qualifying process window and establishing the Optical Proximity Correction (OPC) model become insufficient, thus 2D contour extraction technique [1-5] has been an increasingly important approach for complementing the insufficiencies of traditional CD measurement algorithm. To alleviate the long cycle time and high cost penalties for product verification, manufacturing requirements are better to be well handled at design stage to improve the quality and yield of ICs. In this work, in-house 2D contour extraction platform was established for layout design optimization of 39nm half-pitch Self-Aligned Double Patterning (SADP) process layer. Combining with the adoption of Process Variation Band Index (PVBI), the contour extraction platform enables layout optimization speedup as comparing to traditional methods. The capabilities of identifying and handling lithography hotspots in complex layout environments of 2D contour extraction platform allow process window aware layout optimization to meet the manufacturing requirements.

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.

Contour detection improved by context-adaptive surround suppression.

PubMed

Sang, Qiang; Cai, Biao; Chen, Hao

2017-01-01

Recently, many image processing applications have taken advantage of a psychophysical and neurophysiological mechanism, called "surround suppression" to extract object contour from a natural scene. However, these traditional methods often adopt a single suppression model and a fixed input parameter called "inhibition level", which needs to be manually specified. To overcome these drawbacks, we propose a novel model, called "context-adaptive surround suppression", which can automatically control the effect of surround suppression according to image local contextual features measured by a surface estimator based on a local linear kernel. Moreover, a dynamic suppression method and its stopping mechanism are introduced to avoid manual intervention. The proposed algorithm is demonstrated and validated by a broad range of experimental results.