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Sample records for liver vessels segmentation

  1. Liver vessel segmentation based on extreme learning machine.

    PubMed

    Zeng, Ye Zhan; Zhao, Yu Qian; Liao, Miao; Zou, Bei Ji; Wang, Xiao Fang; Wang, Wei

    2016-05-01

    Liver-vessel segmentation plays an important role in vessel structure analysis for liver surgical planning. This paper presents a liver-vessel segmentation method based on extreme learning machine (ELM). Firstly, an anisotropic filter is used to remove noise while preserving vessel boundaries from the original computer tomography (CT) images. Then, based on the knowledge of prior shapes and geometrical structures, three classical vessel filters including Sato, Frangi and offset medialness filters together with the strain energy filter are used to extract vessel structure features. Finally, the ELM is applied to segment liver vessels from background voxels. Experimental results show that the proposed method can effectively segment liver vessels from abdominal CT images, and achieves good accuracy, sensitivity and specificity. PMID:27132031

  2. Quantitative evaluation of noise reduction and vesselness filters for liver vessel segmentation on abdominal CTA images

    NASA Astrophysics Data System (ADS)

    Luu, Ha Manh; Klink, Camiel; Moelker, Adriaan; Niessen, Wiro; van Walsum, Theo

    2015-05-01

    Liver vessel segmentation in CTA images is a challenging task, especially in the case of noisy images. This paper investigates whether pre-filtering improves liver vessel segmentation in 3D CTA images. We introduce a quantitative evaluation of several well-known filters based on a proposed liver vessel segmentation method on CTA images. We compare the effect of different diffusion techniques i.e. Regularized Perona-Malik, Hybrid Diffusion with Continuous Switch and Vessel Enhancing Diffusion as well as the vesselness approaches proposed by Sato, Frangi and Erdt. Liver vessel segmentation of the pre-processed images is performed using a histogram-based region grown with local maxima as seed points. Quantitative measurements (sensitivity, specificity and accuracy) are determined based on manual landmarks inside and outside the vessels, followed by T-tests for statistic comparisons on 51 clinical CTA images. The evaluation demonstrates that all the filters make liver vessel segmentation have a significantly higher accuracy than without using a filter (p  <  0.05) Hybrid Diffusion with Continuous Switch achieves the best performance. Compared to the diffusion filters, vesselness filters have a greater sensitivity but less specificity. In addition, the proposed liver vessel segmentation method with pre-filtering is shown to perform robustly on a clinical dataset having a low contrast-to-noise of up to 3 (dB). The results indicate that the pre-filtering step significantly improves liver vessel segmentation on 3D CTA images.

  3. Liver vessel tree segmentation based on a hybrid graph cut / fuzzy connectedness method

    NASA Astrophysics Data System (ADS)

    Chen, Xinjian

    2012-02-01

    In the monitoring of oncological therapy, the prediction of liver tumor growth from consecutive CT scans is an important aspect in deciding the treatment planning. The accurate segmentation of liver vessel tree is fundamental for successful prediction of the tumor growth. In this paper, we report a 3D liver vessel tree segmentation method based on the hybrid graph cut (GC) / fuzzy connectedness (FC) method. GC is a popular image segmentation technique. However, it is not always efficient when segmenting thin elongated objects due to its "shrinking bias". To overcome this problem, we propose to impose an additional connectivity prior, which comes from the FC segmentation results. The proposed method synergistically combines the GC with FC methods. The proposed method consists of two main steps. First, the FC method is applied to initially segment the liver vessel tree, which provided the connectivity prior to the subsequent GC method. Second, the connectivity prior integrated GC method is employed to refine the segmented liver vessel tree. The proposed method was tested on 10 clinical portal venous phase CT data sets. The preliminary results showed the feasibility and efficiency of the proposed method. The accuracy of segmentation on this dataset, expressed in sensitivity, was 60%, 92% and 100% for vessel diameters in the range of 0.5 to 1, 1 to 2 and >2 mm, respectively.

  4. Blood vessel-based liver segmentation through the portal phase of a CT dataset

    NASA Astrophysics Data System (ADS)

    Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Moriyama, Noriyuki; Utsunomiya, Toru; Shimada, Mitsuo

    2013-02-01

    Blood vessels are dispersed throughout the human body organs and carry unique information for each person. This information can be used to delineate organ boundaries. The proposed method relies on abdominal blood vessels (ABV) to segment the liver considering the potential presence of tumors through the portal phase of a CT dataset. ABV are extracted and classified into hepatic (HBV) and nonhepatic (non-HBV) with a small number of interactions. HBV and non-HBV are used to guide an automatic segmentation of the liver. HBV are used to individually segment the core region of the liver. This region and non-HBV are used to construct a boundary surface between the liver and other organs to separate them. The core region is classified based on extracted posterior distributions of its histogram into low intensity tumor (LIT) and non-LIT core regions. Non-LIT case includes normal part of liver, HBV, and high intensity tumors if exist. Each core region is extended based on its corresponding posterior distribution. Extension is completed when it reaches either a variation in intensity or the constructed boundary surface. The method was applied to 80 datasets (30 Medical Image Computing and Computer Assisted Intervention (MICCAI) and 50 non-MICCAI data) including 60 datasets with tumors. Our results for the MICCAI-test data were evaluated by sliver07 [1] with an overall score of 79.7, which ranks seventh best on the site (December 2013). This approach seems a promising method for extraction of liver volumetry of various shapes and sizes and low intensity hepatic tumors.

  5. Probabilistic retinal vessel segmentation

    NASA Astrophysics Data System (ADS)

    Wu, Chang-Hua; Agam, Gady

    2007-03-01

    Optic fundus assessment is widely used for diagnosing vascular and non-vascular pathology. Inspection of the retinal vasculature may reveal hypertension, diabetes, arteriosclerosis, cardiovascular disease and stroke. Due to various imaging conditions retinal images may be degraded. Consequently, the enhancement of such images and vessels in them is an important task with direct clinical applications. We propose a novel technique for vessel enhancement in retinal images that is capable of enhancing vessel junctions in addition to linear vessel segments. This is an extension of vessel filters we have previously developed for vessel enhancement in thoracic CT scans. The proposed approach is based on probabilistic models which can discern vessels and junctions. Evaluation shows the proposed filter is better than several known techniques and is comparable to the state of the art when evaluated on a standard dataset. A ridge-based vessel tracking process is applied on the enhanced image to demonstrate the effectiveness of the enhancement filter.

  6. Segmentation of hepatic vessels from MRI images for planning of electroporation-based treatments in the liver

    PubMed Central

    Marcan, Marija; Pavliha, Denis; Music, Maja Marolt; Fuckan, Igor; Magjarevic, Ratko; Miklavcic, Damijan

    2014-01-01

    Introduction. Electroporation-based treatments rely on increasing the permeability of the cell membrane by high voltage electric pulses delivered to tissue via electrodes. To ensure that the whole tumor is covered by the sufficiently high electric field, accurate numerical models are built based on individual patient geometry. For the purpose of reconstruction of hepatic vessels from MRI images we searched for an optimal segmentation method that would meet the following initial criteria: identify major hepatic vessels, be robust and work with minimal user input. Materials and methods. We tested the approaches based on vessel enhancement filtering, thresholding, and their combination in local thresholding. The methods were evaluated on a phantom and clinical data. Results Results show that thresholding based on variance minimization provides less error than the one based on entropy maximization. Best results were achieved by performing local thresholding of the original de-biased image in the regions of interest which were determined through previous vessel-enhancement filtering. In evaluation on clinical cases the proposed method scored in average sensitivity of 93.68%, average symmetric surface distance of 0.89 mm and Hausdorff distance of 4.04 mm. Conclusions The proposed method to segment hepatic vessels from MRI images based on local thresholding meets all the initial criteria set at the beginning of the study and necessary to be used in treatment planning of electroporation-based treatments: it identifies the major vessels, provides results with consistent accuracy and works completely automatically. Whether the achieved accuracy is acceptable or not for treatment planning models remains to be verified through numerical modeling of effects of the segmentation error on the distribution of the electric field. PMID:25177241

  7. Vascular active contour for vessel tree segmentation.

    PubMed

    Shang, Yanfeng; Deklerck, Rudi; Nyssen, Edgard; Markova, Aneta; de Mey, Johan; Yang, Xin; Sun, Kun

    2011-04-01

    In this paper, a novel active contour model is proposed for vessel tree segmentation. First, we introduce a region competition-based active contour model exploiting the gaussian mixture model, which mainly segments thick vessels. Second, we define a vascular vector field to evolve the active contour along its center line into the thin and weak vessels. The vector field is derived from the eigenanalysis of the Hessian matrix of the image intensity in a multiscale framework. Finally, a dual curvature strategy, which uses a vesselness measure-dependent function selecting between a minimal principal curvature and a mean curvature criterion, is added to smoothen the surface of the vessel without changing its shape. The developed model is used to extract the liver and lung vessel tree as well as the coronary artery from high-resolution volumetric computed tomography images. Comparisons are made with several classical active contour models and manual extraction. The experiments show that our model is more accurate and robust than these classical models and is, therefore, more suited for automatic vessel tree extraction. PMID:21138795

  8. Vessel segmentation in screening mammograms

    NASA Astrophysics Data System (ADS)

    Mordang, J. J.; Karssemeijer, N.

    2015-03-01

    Blood vessels are a major cause of false positives in computer aided detection systems for the detection of breast cancer. Therefore, the purpose of this study is to construct a framework for the segmentation of blood vessels in screening mammograms. The proposed framework is based on supervised learning using a cascade classifier. This cascade classifier consists of several stages where in each stage a GentleBoost classifier is trained on Haar-like features. A total of 30 cases were included in this study. In each image, vessel pixels were annotated by selecting pixels on the centerline of the vessel, control samples were taken by annotating a region without any visible vascular structures. This resulted in a total of 31,000 pixels marked as vascular and over 4 million control pixels. After training, the classifier assigns a vesselness likelihood to the pixels. The proposed framework was compared to three other vessel enhancing methods, i) a vesselness filter, ii) a gaussian derivative filter, and iii) a tubeness filter. The methods were compared in terms of area under the receiver operating characteristics curves, the Az values. The Az value of the cascade approach is 0:85. This is superior to the vesselness, Gaussian, and tubeness methods, with Az values of 0:77, 0:81, and 0:78, respectively. From these results, it can be concluded that our proposed framework is a promising method for the detection of vessels in screening mammograms.

  9. Iterative Vessel Segmentation of Fundus Images.

    PubMed

    Roychowdhury, Sohini; Koozekanani, Dara D; Parhi, Keshab K

    2015-07-01

    This paper presents a novel unsupervised iterative blood vessel segmentation algorithm using fundus images. First, a vessel enhanced image is generated by tophat reconstruction of the negative green plane image. An initial estimate of the segmented vasculature is extracted by global thresholding the vessel enhanced image. Next, new vessel pixels are identified iteratively by adaptive thresholding of the residual image generated by masking out the existing segmented vessel estimate from the vessel enhanced image. The new vessel pixels are, then, region grown into the existing vessel, thereby resulting in an iterative enhancement of the segmented vessel structure. As the iterations progress, the number of false edge pixels identified as new vessel pixels increases compared to the number of actual vessel pixels. A key contribution of this paper is a novel stopping criterion that terminates the iterative process leading to higher vessel segmentation accuracy. This iterative algorithm is robust to the rate of new vessel pixel addition since it achieves 93.2-95.35% vessel segmentation accuracy with 0.9577-0.9638 area under ROC curve (AUC) on abnormal retinal images from the STARE dataset. The proposed algorithm is computationally efficient and consistent in vessel segmentation performance for retinal images with variations due to pathology, uneven illumination, pigmentation, and fields of view since it achieves a vessel segmentation accuracy of about 95% in an average time of 2.45, 3.95, and 8 s on images from three public datasets DRIVE, STARE, and CHASE_DB1, respectively. Additionally, the proposed algorithm has more than 90% segmentation accuracy for segmenting peripapillary blood vessels in the images from the DRIVE and CHASE_DB1 datasets. PMID:25700436

  10. Unsupervised Retinal Vessel Segmentation Using Combined Filters.

    PubMed

    Oliveira, Wendeson S; Teixeira, Joyce Vitor; Ren, Tsang Ing; Cavalcanti, George D C; Sijbers, Jan

    2016-01-01

    Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods. PMID:26919587

  11. Unsupervised Retinal Vessel Segmentation Using Combined Filters

    PubMed Central

    Oliveira, Wendeson S.; Teixeira, Joyce Vitor; Ren, Tsang Ing; Cavalcanti, George D. C.; Sijbers, Jan

    2016-01-01

    Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels’ appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi’s filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods. PMID:26919587

  12. Texton-based segmentation of retinal vessels.

    PubMed

    Adjeroh, Donald A; Kandaswamy, Umasankar; Odom, J Vernon

    2007-05-01

    With improvements in fundus imaging technology and the increasing use of digital images in screening and diagnosis, the issue of automated analysis of retinal images is gaining more serious attention. We consider the problem of retinal vessel segmentation, a key issue in automated analysis of digital fundus images. We propose a texture-based vessel segmentation algorithm based on the notion of textons. Using a weak statistical learning approach, we construct textons for retinal vasculature by designing filters that are specifically tuned to the structural and photometric properties of retinal vessels. We evaluate the performance of the proposed approach using a standard database of retinal images. On the DRIVE data set, the proposed method produced an average performance of 0.9568 specificity at 0.7346 sensitivity. This compares well with the best-published results on the data set 0.9773 specificity at 0.7194 sensitivity [Proc. SPIE5370, 648 (2004)]. PMID:17429484

  13. Texton-based segmentation of retinal vessels

    NASA Astrophysics Data System (ADS)

    Adjeroh, Donald A.; Kandaswamy, Umasankar; Odom, J. Vernon

    2007-05-01

    With improvements in fundus imaging technology and the increasing use of digital images in screening and diagnosis, the issue of automated analysis of retinal images is gaining more serious attention. We consider the problem of retinal vessel segmentation, a key issue in automated analysis of digital fundus images. We propose a texture-based vessel segmentation algorithm based on the notion of textons. Using a weak statistical learning approach, we construct textons for retinal vasculature by designing filters that are specifically tuned to the structural and photometric properties of retinal vessels. We evaluate the performance of the proposed approach using a standard database of retinal images. On the DRIVE data set, the proposed method produced an average performance of 0.9568 specificity at 0.7346 sensitivity. This compares well with the best-published results on the data set 0.9773 specificity at 0.7194 sensitivity [Proc. SPIE5370, 648 (2004)].

  14. New automatic liver segmentation and extraction method

    NASA Astrophysics Data System (ADS)

    Zhang, Pinzheng; Xu, Qinzheng; Wang, Zheng

    2007-12-01

    Liver segmentation is critical in designing and developing computer-assisted systems that have been used for liver disease diagnosis before surgery or transplantation. The purpose of this study is to develop a computerized system for extracting liver contours and reconstructing liver volume using contrast-enhanced hepatic CT images. The automatic liver segmentation method adopted the graph optimal algorithm with ratio contour as its salient measure. This new cost function encoded the Gestalt laws and synthesized the gap length, the liver region area, the length of the closed contour and the average curvature of the closed boundary. With the extracted liver contours, a promising system to exclude tissues outside the liver was developed. It promised to save time and simplify liver volume reconstruction by minimizing intervention operations. Some 3D-rendered reconstruction results were also created to demonstrate the final results of our system.

  15. Segmentation and separation of venous vasculatures in liver CT images

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Hansen, Christian; Zidowitz, Stephan; Hahn, Horst K.

    2014-03-01

    Computer-aided analysis of venous vasculatures including hepatic veins and portal veins is important in liver surgery planning. The analysis normally consists of two important pre-processing tasks: segmenting both vasculatures and separating them from each other by assigning different labels. During the acquisition of multi-phase CT images, both of the venous vessels are enhanced by injected contrast agent and acquired either in a common phase or in two individual phases. The enhanced signals established by contrast agent are often not stably acquired due to non-optimal acquisition time. Inadequate contrast and the presence of large lesions in oncological patients, make the segmentation task quite challenging. To overcome these diffculties, we propose a framework with minimal user interactions to analyze venous vasculatures in multi-phase CT images. Firstly, presented vasculatures are automatically segmented adopting an efficient multi-scale Hessian-based vesselness filter. The initially segmented vessel trees are then converted to a graph representation, on which a series of graph filters are applied in post-processing steps to rule out irrelevant structures. Eventually, we develop a semi-automatic workow to refine the segmentation in the areas of inferior vena cava and entrance of portal veins, and to simultaneously separate hepatic veins from portal veins. Segmentation quality was evaluated with intensive tests enclosing 60 CT images from both healthy liver donors and oncological patients. To quantitatively measure the similarities between segmented and reference vessel trees, we propose three additional metrics: skeleton distance, branch coverage, and boundary surface distance, which are dedicated to quantifying the misalignment induced by both branching patterns and radii of two vessel trees.

  16. Iterative contextual CV model for liver segmentation

    NASA Astrophysics Data System (ADS)

    Ji, Hongwei; He, Jiangping; Yang, Xin

    2014-01-01

    In this paper, we propose a novel iterative active contour algorithm, i.e. Iterative Contextual CV Model (ICCV), and apply it to automatic liver segmentation from 3D CT images. ICCV is a learning-based method and can be divided into two stages. At the first stage, i.e. the training stage, given a set of abdominal CT training images and the corresponding manual liver labels, our task is to construct a series of self-correcting classifiers by learning a mapping between automatic segmentations (in each round) and manual reference segmentations via context features. At the second stage, i.e. the segmentation stage, first the basic CV model is used to segment the image and subsequently Contextual CV Model (CCV), which combines the image information and the current shape model, is iteratively performed to improve the segmentation result. The current shape model is obtained by inputting the previous automatic segmentation result into the corresponding self-correcting classifier. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that we obtain more and more accurate segmentation results by the iterative steps and satisfying results are obtained after about six iterations. Also, our method is comparable to the state-of-the-art work on liver segmentation.

  17. A fuzzy clustering vessel segmentation method incorporating line-direction information

    NASA Astrophysics Data System (ADS)

    Wang, Zhimin; Xiong, Wei; Huang, Weimin; Zhou, Jiayin; Venkatesh, Sudhakar K.

    2012-02-01

    A data clustering based vessel segmentation method is proposed for automatic liver vasculature segmentation in CT images. It consists of a novel similarity measure which incorporates the spatial context, vesselness information and line-direction information in a unique way. By combining the line-direction information and spatial information into the data clustering process, the proposed method is able to take care of the fine details of the vessel tree and suppress the image noise and artifacts at the same time. The proposed algorithm has been evaluated on the real clinical contrast-enhanced CT images, and achieved excellent segmentation accuracy without any experimentally set parameters.

  18. Fully automated liver segmentation from SPIR image series.

    PubMed

    Göçeri, Evgin; Gürcan, Metin N; Dicle, Oğuz

    2014-10-01

    Accurate liver segmentation is an important component of surgery planning for liver transplantation, which enables patients with liver disease a chance to survive. Spectral pre-saturation inversion recovery (SPIR) image sequences are useful for liver vessel segmentation because vascular structures in the liver are clearly visible in these sequences. Although level-set based segmentation techniques are frequently used in liver segmentation due to their flexibility to adapt to different problems by incorporating prior knowledge, the need to initialize the contours on each slice is a common drawback of such techniques. In this paper, we present a fully automated variational level set approach for liver segmentation from SPIR image sequences. Our approach is designed to be efficient while achieving high accuracy. The efficiency is achieved by (1) automatically defining an initial contour for each slice, and (2) automatically computing weight values of each term in the applied energy functional at each iteration during evolution. Automated detection and exclusion of spurious structures (e.g. cysts and other bright white regions on the skin) in the pre-processing stage increases the accuracy and robustness. We also present a novel approach to reduce computational cost by employing binary regularization of level set function. A signed pressure force function controls the evolution of the active contour. The method was applied to ten data sets. In each image, the performance of the algorithm was measured using the receiver operating characteristics method in terms of accuracy, sensitivity and specificity. The accuracy of the proposed method was 96%. Quantitative analyses of results indicate that the proposed method can accurately, efficiently and consistently segment liver images. PMID:25192606

  19. Segmentation of liver region with tumorous tissues

    NASA Astrophysics Data System (ADS)

    Zhang, Xuejun; Lee, Gobert; Tajima, Tetsuji; Kitagawa, Teruhiko; Kanematsu, Masayuki; Zhou, Xiangrong; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Hoshi, Hiroaki; Nawano, Shigeru; Shinozaki, Kenji

    2007-03-01

    Segmentation of an abnormal liver region based on CT or MR images is a crucial step in surgical planning. However, precisely carrying out this step remains a challenge due to either connectivities of the liver to other organs or the shape, internal texture, and homogeneity of liver that maybe extensively affected in case of liver diseases. Here, we propose a non-density based method for extracting the liver region containing tumor tissues by edge detection processing. False extracted regions are eliminated by a shape analysis method and thresholding processing. If the multi-phased images are available then the overall outcome of segmentation can be improved by subtracting two phase images, and the connectivities can be further eliminated by referring to the intensity on another phase image. Within an edge liver map, tumor candidates are identified by their different gray values relative to the liver. After elimination of the small and nonspherical over-extracted regions, the final liver region integrates the tumor region with the liver tissue. In our experiment, 40 cases of MDCT images were used and the result showed that our fully automatic method for the segmentation of liver region is effective and robust despite the presence of hepatic tumors within the liver.

  20. Robust vessel segmentation in fundus images.

    PubMed

    Budai, A; Bock, R; Maier, A; Hornegger, J; Michelson, G

    2013-01-01

    One of the most common modalities to examine the human eye is the eye-fundus photograph. The evaluation of fundus photographs is carried out by medical experts during time-consuming visual inspection. Our aim is to accelerate this process using computer aided diagnosis. As a first step, it is necessary to segment structures in the images for tissue differentiation. As the eye is the only organ, where the vasculature can be imaged in an in vivo and noninterventional way without using expensive scanners, the vessel tree is one of the most interesting and important structures to analyze. The quality and resolution of fundus images are rapidly increasing. Thus, segmentation methods need to be adapted to the new challenges of high resolutions. In this paper, we present a method to reduce calculation time, achieve high accuracy, and increase sensitivity compared to the original Frangi method. This method contains approaches to avoid potential problems like specular reflexes of thick vessels. The proposed method is evaluated using the STARE and DRIVE databases and we propose a new high resolution fundus database to compare it to the state-of-the-art algorithms. The results show an average accuracy above 94% and low computational needs. This outperforms state-of-the-art methods. PMID:24416040

  1. Automatic segmentation of abdominal vessels for improved pancreas localization

    NASA Astrophysics Data System (ADS)

    Farag, Amal; Liu, Jiamin; Summers, Ronald M.

    2014-03-01

    Accurate automatic detection and segmentation of abdominal organs from CT images is important for quantitative and qualitative organ tissue analysis as well as computer-aided diagnosis. The large variability of organ locations, the spatial interaction between organs that appear similar in medical scans and orientation and size variations are among the major challenges making the task very difficult. The pancreas poses these challenges in addition to its flexibility which allows for the shape of the tissue to vastly change. Due to the close proximity of the pancreas to numerous surrounding organs within the abdominal cavity the organ shifts according to the conditions of the organs within the abdomen, as such the pancreas is constantly changing. Combining these challenges with typically found patient-to-patient variations and scanning conditions the pancreas becomes harder to localize. In this paper we focus on three abdominal vessels that almost always abut the pancreas tissue and as such useful landmarks to identify the relative location of the pancreas. The splenic and portal veins extend from the hila of the spleen and liver, respectively, travel through the abdominal cavity and join at a position close to the head of the pancreas known as the portal confluence. A third vein, the superior mesenteric vein, anastomoses with the other two veins at the portal confluence. An automatic segmentation framework for obtaining the splenic vein, portal confluence and superior mesenteric vein is proposed using 17 contrast enhanced computed-tomography datasets. The proposed method uses outputs from the multi-organ multi-atlas label fusion and Frangi vesselness filter to obtain automatic seed points for vessel tracking and generation of statistical models of the desired vessels. The approach shows ability to identify the vessels and improve localization of the pancreas within the abdomen.

  2. Extraction of liver volumetry based on blood vessel from the portal phase CT dataset

    NASA Astrophysics Data System (ADS)

    Maklad, Ahmed S.; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Utsunomiya, Tohru; Shimada, Mitsuo

    2012-02-01

    At liver surgery planning stage, the liver volumetry would be essential for surgeons. Main problem at liver extraction is the wide variability of livers in shapes and sizes. Since, hepatic blood vessels structure varies from a person to another and covers liver region, the present method uses that information for extraction of liver in two stages. The first stage is to extract abdominal blood vessels in the form of hepatic and nonhepatic blood vessels. At the second stage, extracted vessels are used to control extraction of liver region automatically. Contrast enhanced CT datasets at only the portal phase of 50 cases is used. Those data include 30 abnormal livers. A reference for all cases is done through a comparison of two experts labeling results and correction of their inter-reader variability. Results of the proposed method agree with the reference at an average rate of 97.8%. Through application of different metrics mentioned at MICCAI workshop for liver segmentation, it is found that: volume overlap error is 4.4%, volume difference is 0.3%, average symmetric distance is 0.7 mm, Root mean square symmetric distance is 0.8 mm, and maximum distance is 15.8 mm. These results represent the average of overall data and show an improved accuracy compared to current liver segmentation methods. It seems to be a promising method for extraction of liver volumetry of various shapes and sizes.

  3. Robust vessel detection and segmentation in ultrasound images by a data-driven approach

    NASA Astrophysics Data System (ADS)

    Guo, Ping; Wang, Qiang; Wang, Xiaotao; Hao, Zhihui; Xu, Kuanhong; Ren, Haibing; Kim, Jung Bae; Hwang, Youngkyoo

    2014-03-01

    This paper presents a learning based vessel detection and segmentation method in real-patient ultrasound (US) liver images. We aim at detecting multiple shaped vessels robustly and automatically, including vessels with weak and ambiguous boundaries. Firstly, vessel candidate regions are detected by a data-driven approach. Multi-channel vessel enhancement maps with complement performances are generated and aggregated under a Conditional Random Field (CRF) framework. Vessel candidates are obtained by thresholding the saliency map. Secondly, regional features are extracted and the probability of each region being a vessel is modeled by random forest regression. Finally, a fast levelset method is developed to refine vessel boundaries. Experiments have been carried out on an US liver dataset with 98 patients. The dataset contains both normal and abnormal liver images. The proposed method in this paper is compared with a traditional Hessian based method, and the average precision is promoted by 56 percents and 7.8 percents for vessel detection and classification, respectively. This improvement shows that our method is more robust to noise, therefore has a better performance than the Hessian based method for the detection of vessels with weak and ambiguous boundaries.

  4. Segmentation of the liver from abdominal MR images: a level-set approach

    NASA Astrophysics Data System (ADS)

    Abdalbari, Anwar; Huang, Xishi; Ren, Jing

    2015-03-01

    The usage of prior knowledge in segmentation of abdominal MR images enables more accurate and comprehensive interpretation about the organ to segment. Prior knowledge about abdominal organ like liver vessels can be employed to get an accurate segmentation of the liver that leads to accurate diagnosis or treatment plan. In this paper, a new method for segmenting the liver from abdominal MR images using liver vessels as prior knowledge is proposed. This paper employs the technique of level set method to segment the liver from MR abdominal images. The speed image used in the level set method is responsible for propagating and stopping region growing at boundaries. As a result of the poor contrast of the MR images between the liver and the surrounding organs i.e. stomach, kidneys, and heart causes leak of the segmented liver to those organs that lead to inaccurate or incorrect segmentation. For that reason, a second speed image is developed, as an extra term to the level set, to control the front propagation at weak edges with the help of the original speed image. The basic idea of the proposed approach is to use the second speed image as a boundary surface which is approximately orthogonal to the area of the leak. The aim of the new speed image is to slow down the level set propagation and prevent the leak in the regions close to liver boundary. The new speed image is a surface created by filling holes to reconstruct the liver surface. These holes are formed as a result of the exit and the entry of the liver vessels, and are considered the main cause of the segmentation leak. The result of the proposed method shows superior outcome than other methods in the literature.

  5. Automatic segmentation and diameter measurement of coronary artery vessels

    NASA Astrophysics Data System (ADS)

    Zhao, Kun; Tang, Zhenyu; Pauli, Josef

    2011-03-01

    This work presents a hybrid method for 2D artery vessel segmentation and diameter measurement in X-Ray angiograms. The proposed method is novel in that tracking-based and model-based approaches are combined. A robust and efficient tracking template, the "annular template", is devised for vessel tracking. It can readily be applied on X-Ray angiograms without any preprocessing. Starting from an initial tracking point given by the user the tracking algorithm iteratively repositions the annular template and thereby detects the vessel boundaries and possible bifurcations. With a user selected end point the tracking process results in a set of points that describes the contour and topology of an artery vessel segment between the initial and end points. A "boundary correction and interpolation" operation refines the extracted points which initialize the Snakes algorithm. Boundary correction adjusts the points to ensure that they lie on the vessel segment of interest. Boundary interpolation adds more points, so that there are sufficiently many points for the Snakes algorithm to generate a smooth and accurate vessel segmentation. After the application of Snakes the resulting points are sequentially connected to represent the vessel contour. Then, the diameters are measured along the extracted vessel contour. The segmentation and measurement results are compared with manually extracted and measured vessel segments. The average Precision, Recall and Jaccard Index of 21 vessel samples are 91.5%, 92.1% and 84.9%, respectively. Compared with ground truth measurements of diameters the average relative error is 8.2%, and the average absolute error is 1.13 pixels.

  6. Segmentation of Retinal Blood Vessels Based on Cake Filter

    PubMed Central

    Bao, Xi-Rong; Ge, Xin; She, Li-Huang; Zhang, Shi

    2015-01-01

    Segmentation of retinal blood vessels is significant to diagnosis and evaluation of ocular diseases like glaucoma and systemic diseases such as diabetes and hypertension. The retinal blood vessel segmentation for small and low contrast vessels is still a challenging problem. To solve this problem, a new method based on cake filter is proposed. Firstly, a quadrature filter band called cake filter band is made up in Fourier field. Then the real component fusion is used to separate the blood vessel from the background. Finally, the blood vessel network is got by a self-adaption threshold. The experiments implemented on the STARE database indicate that the new method has a better performance than the traditional ones on the small vessels extraction, average accuracy rate, and true and false positive rate. PMID:26636095

  7. Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

    SciTech Connect

    Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

    2012-03-15

    Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

  8. Lung vessel segmentation in CT images using graph-cuts

    NASA Astrophysics Data System (ADS)

    Zhai, Zhiwei; Staring, Marius; Stoel, Berend C.

    2016-03-01

    Accurate lung vessel segmentation is an important operation for lung CT analysis. Filters that are based on analyzing the eigenvalues of the Hessian matrix are popular for pulmonary vessel enhancement. However, due to their low response at vessel bifurcations and vessel boundaries, extracting lung vessels by thresholding the vesselness is not sufficiently accurate. Some methods turn to graph-cuts for more accurate segmentation, as it incorporates neighbourhood information. In this work, we propose a new graph-cuts cost function combining appearance and shape, where CT intensity represents appearance and vesselness from a Hessian-based filter represents shape. Due to the amount of voxels in high resolution CT scans, the memory requirement and time consumption for building a graph structure is very high. In order to make the graph representation computationally tractable, those voxels that are considered clearly background are removed from the graph nodes, using a threshold on the vesselness map. The graph structure is then established based on the remaining voxel nodes, source/sink nodes and the neighbourhood relationship of the remaining voxels. Vessels are segmented by minimizing the energy cost function with the graph-cuts optimization framework. We optimized the parameters used in the graph-cuts cost function and evaluated the proposed method with two manually labeled sub-volumes. For independent evaluation, we used 20 CT scans of the VESSEL12 challenge. The evaluation results of the sub-volume data show that the proposed method produced a more accurate vessel segmentation compared to the previous methods, with F1 score 0.76 and 0.69. In the VESSEL12 data-set, our method obtained a competitive performance with an area under the ROC curve of 0.975, especially among the binary submissions.

  9. Fuzzy pulmonary vessel segmentation in contrast enhanced CT data

    NASA Astrophysics Data System (ADS)

    Kaftan, Jens N.; Kiraly, Atilla P.; Bakai, Annemarie; Das, Marco; Novak, Carol L.; Aach, Til

    2008-03-01

    Pulmonary vascular tree segmentation has numerous applications in medical imaging and computer-aided diagnosis (CAD), including detection and visualization of pulmonary emboli (PE), improved lung nodule detection, and quantitative vessel analysis. We present a novel approach to pulmonary vessel segmentation based on a fuzzy segmentation concept, combining the strengths of both threshold and seed point based methods. The lungs of the original image are first segmented and a threshold-based approach identifies core vessel components with a high specificity. These components are then used to automatically identify reliable seed points for a fuzzy seed point based segmentation method, namely fuzzy connectedness. The output of the method consists of the probability of each voxel belonging to the vascular tree. Hence, our method provides the possibility to adjust the sensitivity/specificity of the segmentation result a posteriori according to application-specific requirements, through definition of a minimum vessel-probability required to classify a voxel as belonging to the vascular tree. The method has been evaluated on contrast-enhanced thoracic CT scans from clinical PE cases and demonstrates overall promising results. For quantitative validation we compare the segmentation results to randomly selected, semi-automatically segmented sub-volumes and present the resulting receiver operating characteristic (ROC) curves. Although we focus on contrast enhanced chest CT data, the method can be generalized to other regions of the body as well as to different imaging modalities.

  10. Brain blood vessel segmentation using line-shaped profiles

    NASA Astrophysics Data System (ADS)

    Babin, Danilo; Pižurica, Aleksandra; De Vylder, Jonas; Vansteenkiste, Ewout; Philips, Wilfried

    2013-11-01

    Segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, especially for embolization of cerebral aneurysms and arteriovenous malformations (AVMs). In order to perform embolization of the AVM, the structural and geometric information of blood vessels from 3D images is of utmost importance. For this reason, the in-depth segmentation of cerebral blood vessels is usually done as a fusion of different segmentation techniques, often requiring extensive user interaction. In this paper we introduce the idea of line-shaped profiling with an application to brain blood vessel and AVM segmentation, efficient both in terms of resolving details and in terms of computation time. Our method takes into account both local proximate and wider neighbourhood of the processed pixel, which makes it efficient for segmenting large blood vessel tree structures, as well as fine structures of the AVMs. Another advantage of our method is that it requires selection of only one parameter to perform segmentation, yielding very little user interaction.

  11. A two-stage approach for fully automatic segmentation of venous vascular structures in liver CT images

    NASA Astrophysics Data System (ADS)

    Kaftan, Jens N.; Tek, Hüseyin; Aach, Til

    2009-02-01

    The segmentation of the hepatic vascular tree in computed tomography (CT) images is important for many applications such as surgical planning of oncological resections and living liver donations. In surgical planning, vessel segmentation is often used as basis to support the surgeon in the decision about the location of the cut to be performed and the extent of the liver to be removed, respectively. We present a novel approach to hepatic vessel segmentation that can be divided into two stages. First, we detect and delineate the core vessel components efficiently with a high specificity. Second, smaller vessel branches are segmented by a robust vessel tracking technique based on a medialness filter response, which starts from the terminal points of the previously segmented vessels. Specifically, in the first phase major vessels are segmented using the globally optimal graphcuts algorithm in combination with foreground and background seed detection, while the computationally more demanding tracking approach needs to be applied only locally in areas of smaller vessels within the second stage. The method has been evaluated on contrast-enhanced liver CT scans from clinical routine showing promising results. In addition to the fully-automatic instance of this method, the vessel tracking technique can also be used to easily add missing branches/sub-trees to an already existing segmentation result by adding single seed-points.

  12. A function for quality evaluation of retinal vessel segmentations.

    PubMed

    Gegúndez-Arias, Manuel Emilio; Aquino, Arturo; Bravo, José Manuel; Marín, Diego

    2012-02-01

    Retinal blood vessel assessment plays an important role in the diagnosis of ophthalmic pathologies. The use of digital images for this purpose enables the application of a computerized approach and has fostered the development of multiple methods for automated vascular tree segmentation. Metrics based on contingency tables for binary classification have been widely used for evaluating the performance of these algorithms. Metrics from this family are based on the measurement of a success or failure rate in the detected pixels, obtained by means of pixel-to-pixel comparison between the automated segmentation and a manually-labeled reference image. Therefore, vessel pixels are not considered as a part of a vascular structure with specific features. This paper contributes a function for the evaluation of global quality in retinal vessel segmentations. This function is based on the characterization of vascular structures as connected segments with measurable area and length. Thus, its design is meant to be sensitive to anatomical vascularity features. Comparison of results between the proposed function and other general quality evaluation functions shows that this proposal renders a high matching degree with human quality perception. Therefore, it can be used to enhance quality evaluation in retinal vessel segmentations, supplementing the existing functions. On the other hand, from a general point of view, the applied concept of measuring descriptive properties may be used to design specialized functions aimed at segmentation quality evaluation in other complex structures. PMID:21926018

  13. Blood Vessel Segmentation of Fundus Images by Major Vessel Extraction and Subimage Classification.

    PubMed

    Roychowdhury, Sohini; Koozekanani, Dara D; Parhi, Keshab K

    2015-05-01

    This paper presents a novel three-stage blood vessel segmentation algorithm using fundus photographs. In the first stage, the green plane of a fundus image is preprocessed to extract a binary image after high-pass filtering, and another binary image from the morphologically reconstructed enhanced image for the vessel regions. Next, the regions common to both the binary images are extracted as the major vessels. In the second stage, all remaining pixels in the two binary images are classified using a Gaussian mixture model (GMM) classifier using a set of eight features that are extracted based on pixel neighborhood and first and second-order gradient images. In the third postprocessing stage, the major portions of the blood vessels are combined with the classified vessel pixels. The proposed algorithm is less dependent on training data, requires less segmentation time and achieves consistent vessel segmentation accuracy on normal images as well as images with pathology when compared to existing supervised segmentation methods. The proposed algorithm achieves a vessel segmentation accuracy of 95.2%, 95.15%, and 95.3% in an average of 3.1, 6.7, and 11.7 s on three public datasets DRIVE, STARE, and CHASE_DB1, respectively. PMID:25014980

  14. A Framework for 3D Vessel Analysis using Whole Slide Images of Liver Tissue Sections

    PubMed Central

    Liang, Yanhui; Wang, Fusheng; Treanor, Darren; Magee, Derek; Roberts, Nick; Teodoro, George; Zhu, Yangyang; Kong, Jun

    2015-01-01

    Three-dimensional (3D) high resolution microscopic images have high potential for improving the understanding of both normal and disease processes where structural changes or spatial relationship of disease features are significant. In this paper, we develop a complete framework applicable to 3D pathology analytical imaging, with an application to whole slide images of sequential liver slices for 3D vessel structure analysis. The analysis workflow consists of image registration, segmentation, vessel cross-section association, interpolation, and volumetric rendering. To identify biologically-meaningful correspondence across adjacent slides, we formulate a similarity function for four association cases. The optimal solution is then obtained by constrained Integer Programming. We quantitatively and qualitatively compare our vessel reconstruction results with human annotations. Validation results indicate a satisfactory concordance as measured both by region-based and distance-based metrics. These results demonstrate a promising 3D vessel analysis framework for whole slide images of liver tissue sections. PMID:27034719

  15. Liver segmentation for CT images using GVF snake

    SciTech Connect

    Liu Fan; Zhao Binsheng; Kijewski, Peter K.; Wang Liang; Schwartz, Lawrence H.

    2005-12-15

    Accurate liver segmentation on computed tomography (CT) images is a challenging task especially at sites where surrounding tissues (e.g., stomach, kidney) have densities similar to that of the liver and lesions reside at the liver edges. We have developed a method for semiautomatic delineation of the liver contours on contrast-enhanced CT images. The method utilizes a snake algorithm with a gradient vector flow (GVF) field as its external force. To improve the performance of the GVF snake in the segmentation of the liver contour, an edge map was obtained with a Canny edge detector, followed by modifications using a liver template and a concavity removal algorithm. With the modified edge map, for which unwanted edges inside the liver were eliminated, the GVF field was computed and an initial liver contour was formed. The snake algorithm was then applied to obtain the actual liver contour. This algorithm was extended to segment the liver volume in a slice-by-slice fashion, where the result of the preceding slice constrained the segmentation of the adjacent slice. 551 two-dimensional liver images from 20 volumetric images with colorectal metastases spreading throughout the livers were delineated using this method, and also manually by a radiologist for evaluation. The difference ratio, which is defined as the percentage ratio of mismatching volume between the computer and the radiologist's results, ranged from 2.9% to 7.6% with a median value of 5.3%.

  16. Novel algorithm by low complexity filter on retinal vessel segmentation

    NASA Astrophysics Data System (ADS)

    Rostampour, Samad

    2011-10-01

    This article shows a new method to detect blood vessels in the retina by digital images. Retinal vessel segmentation is important for detection of side effect of diabetic disease, because diabetes can form new capillaries which are very brittle. The research has been done in two phases: preprocessing and processing. Preprocessing phase consists to apply a new filter that produces a suitable output. It shows vessels in dark color on white background and make a good difference between vessels and background. The complexity is very low and extra images are eliminated. The second phase is processing and used the method is called Bayesian. It is a built-in in supervision classification method. This method uses of mean and variance of intensity of pixels for calculate of probability. Finally Pixels of image are divided into two classes: vessels and background. Used images are related to the DRIVE database. After performing this operation, the calculation gives 95 percent of efficiency average. The method also was performed from an external sample DRIVE database which has retinopathy, and perfect result was obtained

  17. A comparison of texture models for automatic liver segmentation

    NASA Astrophysics Data System (ADS)

    Pham, Mailan; Susomboon, Ruchaneewan; Disney, Tim; Raicu, Daniela; Furst, Jacob

    2007-03-01

    Automatic liver segmentation from abdominal computed tomography (CT) images based on gray levels or shape alone is difficult because of the overlap in gray-level ranges and the variation in position and shape of the soft tissues. To address these issues, we propose an automatic liver segmentation method that utilizes low-level features based on texture information; this texture information is expected to be homogenous and consistent across multiple slices for the same organ. Our proposed approach consists of the following steps: first, we perform pixel-level texture extraction; second, we generate liver probability images using a binary classification approach; third, we apply a split-and-merge algorithm to detect the seed set with the highest probability area; and fourth, we apply to the seed set a region growing algorithm iteratively to refine the liver's boundary and get the final segmentation results. Furthermore, we compare the segmentation results from three different texture extraction methods (Co-occurrence Matrices, Gabor filters, and Markov Random Fields (MRF)) to find the texture method that generates the best liver segmentation. From our experimental results, we found that the co-occurrence model led to the best segmentation, while the Gabor model led to the worst liver segmentation. Moreover, co-occurrence texture features alone produced approximately the same segmentation results as those produced when all the texture features from the combined co-occurrence, Gabor, and MRF models were used. Therefore, in addition to providing an automatic model for liver segmentation, we also conclude that Haralick cooccurrence texture features are the most significant texture characteristics in distinguishing the liver tissue in CT scans.

  18. Active contour based segmentation of resected livers in CT images

    NASA Astrophysics Data System (ADS)

    Oelmann, Simon; Oyarzun Laura, Cristina; Drechsler, Klaus; Wesarg, Stefan

    2015-03-01

    The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the active contour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.

  19. Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study.

    PubMed

    Rudyanto, Rina D; Kerkstra, Sjoerd; van Rikxoort, Eva M; Fetita, Catalin; Brillet, Pierre-Yves; Lefevre, Christophe; Xue, Wenzhe; Zhu, Xiangjun; Liang, Jianming; Öksüz, Ilkay; Ünay, Devrim; Kadipaşaoğlu, Kamuran; Estépar, Raúl San José; Ross, James C; Washko, George R; Prieto, Juan-Carlos; Hoyos, Marcela Hernández; Orkisz, Maciej; Meine, Hans; Hüllebrand, Markus; Stöcker, Christina; Mir, Fernando Lopez; Naranjo, Valery; Villanueva, Eliseo; Staring, Marius; Xiao, Changyan; Stoel, Berend C; Fabijanska, Anna; Smistad, Erik; Elster, Anne C; Lindseth, Frank; Foruzan, Amir Hossein; Kiros, Ryan; Popuri, Karteek; Cobzas, Dana; Jimenez-Carretero, Daniel; Santos, Andres; Ledesma-Carbayo, Maria J; Helmberger, Michael; Urschler, Martin; Pienn, Michael; Bosboom, Dennis G H; Campo, Arantza; Prokop, Mathias; de Jong, Pim A; Ortiz-de-Solorzano, Carlos; Muñoz-Barrutia, Arrate; van Ginneken, Bram

    2014-10-01

    The VESSEL12 (VESsel SEgmentation in the Lung) challenge objectively compares the performance of different algorithms to identify vessels in thoracic computed tomography (CT) scans. Vessel segmentation is fundamental in computer aided processing of data generated by 3D imaging modalities. As manual vessel segmentation is prohibitively time consuming, any real world application requires some form of automation. Several approaches exist for automated vessel segmentation, but judging their relative merits is difficult due to a lack of standardized evaluation. We present an annotated reference dataset containing 20 CT scans and propose nine categories to perform a comprehensive evaluation of vessel segmentation algorithms from both academia and industry. Twenty algorithms participated in the VESSEL12 challenge, held at International Symposium on Biomedical Imaging (ISBI) 2012. All results have been published at the VESSEL12 website http://vessel12.grand-challenge.org. The challenge remains ongoing and open to new participants. Our three contributions are: (1) an annotated reference dataset available online for evaluation of new algorithms; (2) a quantitative scoring system for objective comparison of algorithms; and (3) performance analysis of the strengths and weaknesses of the various vessel segmentation methods in the presence of various lung diseases. PMID:25113321

  20. Reactor Vessel and Reactor Vessel Internals Segmentation at Zion Nuclear Power Station - 13230

    SciTech Connect

    Cooke, Conrad; Spann, Holger

    2013-07-01

    Zion Nuclear Power Station (ZNPS) is a dual-unit Pressurized Water Reactor (PWR) nuclear power plant located on the Lake Michigan shoreline, in the city of Zion, Illinois approximately 64 km (40 miles) north of Chicago, Illinois and 67 km (42 miles) south of Milwaukee, Wisconsin. Each PWR is of the Westinghouse design and had a generation capacity of 1040 MW. Exelon Corporation operated both reactors with the first unit starting production of power in 1973 and the second unit coming on line in 1974. The operation of both reactors ceased in 1996/1997. In 2010 the Nuclear Regulatory Commission approved the transfer of Exelon Corporation's license to ZionSolutions, the Long Term Stewardship subsidiary of EnergySolutions responsible for the decommissioning of ZNPS. In October 2010, ZionSolutions awarded Siempelkamp Nuclear Services, Inc. (SNS) the contract to plan, segment, remove, and package both reactor vessels and their respective internals. This presentation discusses the tools employed by SNS to remove and segment the Reactor Vessel Internals (RVI) and Reactor Vessels (RV) and conveys the recent progress. SNS's mechanical segmentation tooling includes the C-HORCE (Circumferential Hydraulically Operated Cutting Equipment), BMT (Bolt Milling Tool), FaST (Former Attachment Severing Tool) and the VRS (Volume Reduction Station). Thermal segmentation of the reactor vessels will be accomplished using an Oxygen- Propane cutting system. The tools for internals segmentation were designed by SNS using their experience from other successful reactor and large component decommissioning and demolition (D and D) projects in the US. All of the designs allow for the mechanical segmentation of the internals remotely in the water-filled reactor cavities. The C-HORCE is designed to saw seven circumferential cuts through the Core Barrel and Thermal Shield walls with individual thicknesses up to 100 mm (4 inches). The BMT is designed to remove the bolts that fasten the Baffle Plates to

  1. A multiatlas segmentation using graph cuts with applications to liver segmentation in CT scans.

    PubMed

    Platero, Carlos; Tobar, M Carmen

    2014-01-01

    An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

  2. A Multiatlas Segmentation Using Graph Cuts with Applications to Liver Segmentation in CT Scans

    PubMed Central

    2014-01-01

    An atlas-based segmentation approach is presented that combines low-level operations, an affine probabilistic atlas, and a multiatlas-based segmentation. The proposed combination provides highly accurate segmentation due to registrations and atlas selections based on the regions of interest (ROIs) and coarse segmentations. Our approach shares the following common elements between the probabilistic atlas and multiatlas segmentation: (a) the spatial normalisation and (b) the segmentation method, which is based on minimising a discrete energy function using graph cuts. The method is evaluated for the segmentation of the liver in computed tomography (CT) images. Low-level operations define a ROI around the liver from an abdominal CT. We generate a probabilistic atlas using an affine registration based on geometry moments from manually labelled data. Next, a coarse segmentation of the liver is obtained from the probabilistic atlas with low computational effort. Then, a multiatlas segmentation approach improves the accuracy of the segmentation. Both the atlas selections and the nonrigid registrations of the multiatlas approach use a binary mask defined by coarse segmentation. We experimentally demonstrate that this approach performs better than atlas selections and nonrigid registrations in the entire ROI. The segmentation results are comparable to those obtained by human experts and to other recently published results. PMID:25276219

  3. Performance benchmarking of liver CT image segmentation and volume estimation

    NASA Astrophysics Data System (ADS)

    Xiong, Wei; Zhou, Jiayin; Tian, Qi; Liu, Jimmy J.; Qi, Yingyi; Leow, Wee Kheng; Han, Thazin; Wang, Shih-chang

    2008-03-01

    In recent years more and more computer aided diagnosis (CAD) systems are being used routinely in hospitals. Image-based knowledge discovery plays important roles in many CAD applications, which have great potential to be integrated into the next-generation picture archiving and communication systems (PACS). Robust medical image segmentation tools are essentials for such discovery in many CAD applications. In this paper we present a platform with necessary tools for performance benchmarking for algorithms of liver segmentation and volume estimation used for liver transplantation planning. It includes an abdominal computer tomography (CT) image database (DB), annotation tools, a ground truth DB, and performance measure protocols. The proposed architecture is generic and can be used for other organs and imaging modalities. In the current study, approximately 70 sets of abdominal CT images with normal livers have been collected and a user-friendly annotation tool is developed to generate ground truth data for a variety of organs, including 2D contours of liver, two kidneys, spleen, aorta and spinal canal. Abdominal organ segmentation algorithms using 2D atlases and 3D probabilistic atlases can be evaluated on the platform. Preliminary benchmark results from the liver segmentation algorithms which make use of statistical knowledge extracted from the abdominal CT image DB are also reported. We target to increase the CT scans to about 300 sets in the near future and plan to make the DBs built available to medical imaging research community for performance benchmarking of liver segmentation algorithms.

  4. A boosted optimal linear learner for retinal vessel segmentation

    NASA Astrophysics Data System (ADS)

    Poletti, E.; Grisan, E.

    2014-03-01

    Ocular fundus images provide important information about retinal degeneration, which may be related to acute pathologies or to early signs of systemic diseases. An automatic and quantitative assessment of vessel morphological features, such as diameters and tortuosity, can improve clinical diagnosis and evaluation of retinopathy. At variance with available methods, we propose a data-driven approach, in which the system learns a set of optimal discriminative convolution kernels (linear learner). The set is progressively built based on an ADA-boost sample weighting scheme, providing seamless integration between linear learner estimation and classification. In order to capture the vessel appearance changes at different scales, the kernels are estimated on a pyramidal decomposition of the training samples. The set is employed as a rotating bank of matched filters, whose response is used by the boosted linear classifier to provide a classification of each image pixel into the two classes of interest (vessel/background). We tested the approach fundus images available from the DRIVE dataset. We show that the segmentation performance yields an accuracy of 0.94.

  5. Automatic pulmonary vessel segmentation in 3D computed tomographic pulmonary angiographic (CTPA) images

    NASA Astrophysics Data System (ADS)

    Zhou, Chuan; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Patel, Smita; Cascade, Philip N.; Sahiner, Berkman; Wei, Jun; Ge, Jun; Kazerooni, Ella A.

    2006-03-01

    Automatic and accurate segmentation of the pulmonary vessels in 3D computed tomographic angiographic images (CTPA) is an essential step for computerized detection of pulmonary embolism (PE) because PEs only occur inside the pulmonary arteries. We are developing an automated method to segment the pulmonary vessels in 3D CTPA images. The lung region is first extracted using thresholding and morphological operations. 3D multiscale filters in combination with a newly developed response function derived from the eigenvalues of Hessian matrices are used to enhance all vascular structures including the vessel bifurcations and suppress non-vessel structures such as the lymphoid tissues surrounding the vessels. At each scale, a volume of interest (VOI) containing the response function value at each voxel is defined. The voxels with a high response indicate that there is an enhanced vessel whose size matches the given filter scale. A hierarchical expectation-maximization (EM) estimation is then applied to the VOI to segment the vessel by extracting the high response voxels at this single scale. The vessel tree is finally reconstructed by combining the segmented vessels at all scales based on a "connected component" analysis. Two experienced thoracic radiologists provided the gold standard of pulmonary arteries by manually tracking the arterial tree and marking the center of the vessels using a computer graphical user interface. Two CTPA cases containing PEs were used to evaluate the performance. One of these two cases also contained other lung diseases. The accuracy of vessel tree segmentation was evaluated by the percentage of the "gold standard" vessel center points overlapping with the segmented vessels. The result shows that 97.3% (1868/1920) and 92.0% (2277/2476) of the manually marked center points overlapped with the segmented vessels for the cases without and with other lung disease, respectively. The results demonstrate that vessel segmentation using our method is

  6. Fetal liver hematopoietic stem cell niches associate with portal vessels

    PubMed Central

    Khan, Jalal A.; Mendelson, Avital; Kunisaki, Yuya; Birbrair, Alexander; Kou, Yan; Arnal-Estapé, Anna; Pinho, Sandra; Ciero, Paul; Nakahara, Fumio; Ma’ayan, Avi; Bergman, Aviv; Merad, Miriam; Frenette, Paul S.

    2015-01-01

    Whereas the cellular basis of the hematopoietic stem cell (HSC) niche in the bone marrow has been characterized, the nature of the fetal liver (FL) niche is not yet elucidated. We show that Nestin+NG2+ pericytes associate with portal vessels, forming a niche promoting HSC expansion. Nestin+NG2+ cells and HSCs scale during development with the fractal branching patterns of portal vessels, tributaries of the umbilical vein. After closure of the umbilical inlet at birth, portal vessels undergo a transition from Neuropilin-1+Ephrin-B2+ artery to EphB4+ vein phenotype, associated with a loss of periportal Nestin+NG2+ cells and emigration of HSCs away from portal vessels. These data support a model in which HSCs are titrated against a periportal vascular niche with a fractal-like organization enabled by placental circulation. PMID:26634440

  7. Automatic multiscale enhancement and segmentation of pulmonary vessels in CT pulmonary angiography images for CAD applications

    SciTech Connect

    Zhou Chuan; Chan, H.-P.; Sahiner, Berkman; Hadjiiski, Lubomir M.; Chughtai, Aamer; Patel, Smita; Wei Jun; Ge Jun; Cascade, Philip N.; Kazerooni, Ella A.

    2007-12-15

    The authors are developing a computerized pulmonary vessel segmentation method for a computer-aided pulmonary embolism (PE) detection system on computed tomographic pulmonary angiography (CTPA) images. Because PE only occurs inside pulmonary arteries, an automatic and accurate segmentation of the pulmonary vessels in 3D CTPA images is an essential step for the PE CAD system. To segment the pulmonary vessels within the lung, the lung regions are first extracted using expectation-maximization (EM) analysis and morphological operations. The authors developed a 3D multiscale filtering technique to enhance the pulmonary vascular structures based on the analysis of eigenvalues of the Hessian matrix at multiple scales. A new response function of the filter was designed to enhance all vascular structures including the vessel bifurcations and suppress nonvessel structures such as the lymphoid tissues surrounding the vessels. An EM estimation is then used to segment the vascular structures by extracting the high response voxels at each scale. The vessel tree is finally reconstructed by integrating the segmented vessels at all scales based on a 'connected component' analysis. Two CTPA cases containing PEs were used to evaluate the performance of the system. One of these two cases also contained pleural effusion disease. Two experienced thoracic radiologists provided the gold standard of pulmonary vessels including both arteries and veins by manually tracking the arterial tree and marking the center of the vessels using a computer graphical user interface. The accuracy of vessel tree segmentation was evaluated by the percentage of the 'gold standard' vessel center points overlapping with the segmented vessels. The results show that 96.2% (2398/2494) and 96.3% (1910/1984) of the manually marked center points in the arteries overlapped with segmented vessels for the case without and with other lung diseases. For the manually marked center points in all vessels including arteries

  8. A general approach to liver lesion segmentation in CT images

    NASA Astrophysics Data System (ADS)

    Cao, Li; Udupa, Jayaram K.; Odhner, Dewey; Huang, Lidong; Tong, Yubing; Torigian, Drew A.

    2016-03-01

    Lesion segmentation has remained a challenge in different body regions. Generalizability is lacking in published methods as variability in results is common, even for a given organ and modality, such that it becomes difficult to establish standardized methods of disease quantification and reporting. This paper makes an attempt at a generalizable method based on classifying lesions along with their background into groups using clinically used visual attributes. Using an Iterative Relative Fuzzy Connectedness (IRFC) delineation engine, the ideas are implemented for the task of liver lesion segmentation in computed tomography (CT) images. For lesion groups with the same background properties, a few subjects are chosen as the training set to obtain the optimal IRFC parameters for the background tissue components. For lesion groups with similar foreground properties, optimal foreground parameters for IRFC are set as the median intensity value of the training lesion subset. To segment liver lesions belonging to a certain group, the devised method requires manual loading of the corresponding parameters, and correct setting of the foreground and background seeds. The segmentation is then completed in seconds. Segmentation accuracy and repeatability with respect to seed specification are evaluated. Accuracy is assessed by the assignment of a delineation quality score (DQS) to each case. Inter-operator repeatability is assessed by the difference between segmentations carried out independently by two operators. Experiments on 80 liver lesion cases show that the proposed method achieves a mean DQS score of 4.03 and inter-operator repeatability of 92.3%.

  9. Vessel segmentation in 3D spectral OCT scans of the retina

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Garvin, Mona K.; van Ginneken, Bram; Sonka, Milan; Abràmoff, Michael D.

    2008-03-01

    The latest generation of spectral optical coherence tomography (OCT) scanners is able to image 3D cross-sectional volumes of the retina at a high resolution and high speed. These scans offer a detailed view of the structure of the retina. Automated segmentation of the vessels in these volumes may lead to more objective diagnosis of retinal vascular disease including hypertensive retinopathy, retinopathy of prematurity. Additionally, vessel segmentation can allow color fundus images to be registered to these 3D volumes, possibly leading to a better understanding of the structure and localization of retinal structures and lesions. In this paper we present a method for automatically segmenting the vessels in a 3D OCT volume. First, the retina is automatically segmented into multiple layers, using simultaneous segmentation of their boundary surfaces in 3D. Next, a 2D projection of the vessels is produced by only using information from certain segmented layers. Finally, a supervised, pixel classification based vessel segmentation approach is applied to the projection image. We compared the influence of two methods for the projection on the performance of the vessel segmentation on 10 optic nerve head centered 3D OCT scans. The method was trained on 5 independent scans. Using ROC analysis, our proposed vessel segmentation system obtains an area under the curve of 0.970 when compared with the segmentation of a human observer.

  10. Semiautomatic segmentation of liver metastases on volumetric CT images

    SciTech Connect

    Yan, Jiayong; Schwartz, Lawrence H.; Zhao, Binsheng

    2015-11-15

    Purpose: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. Methods: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1–10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the “gold standard” for validation of the method’s accuracy. Results: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. Conclusions: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation

  11. Metastatic liver tumour segmentation from discriminant Grassmannian manifolds

    NASA Astrophysics Data System (ADS)

    Kadoury, Samuel; Vorontsov, Eugene; Tang, An

    2015-08-01

    The early detection, diagnosis and monitoring of liver cancer progression can be achieved with the precise delineation of metastatic tumours. However, accurate automated segmentation remains challenging due to the presence of noise, inhomogeneity and the high appearance variability of malignant tissue. In this paper, we propose an unsupervised metastatic liver tumour segmentation framework using a machine learning approach based on discriminant Grassmannian manifolds which learns the appearance of tumours with respect to normal tissue. First, the framework learns within-class and between-class similarity distributions from a training set of images to discover the optimal manifold discrimination between normal and pathological tissue in the liver. Second, a conditional optimisation scheme computes non-local pairwise as well as pattern-based clique potentials from the manifold subspace to recognise regions with similar labelings and to incorporate global consistency in the segmentation process. The proposed framework was validated on a clinical database of 43 CT images from patients with metastatic liver cancer. Compared to state-of-the-art methods, our method achieves a better performance on two separate datasets of metastatic liver tumours from different clinical sites, yielding an overall mean Dice similarity coefficient of 90.7+/- 2.4 in over 50 tumours with an average volume of 27.3 mm3.

  12. Multimodal Retinal Vessel Segmentation from Spectral-Domain Optical Coherence Tomography and Fundus Photography

    PubMed Central

    Hu, Zhihong; Niemeijer, Meindert; Abràmoff, Michael D.; Garvin, Mona K.

    2014-01-01

    Segmenting retinal vessels in optic nerve head (ONH) centered spectral-domain optical coherence tomography (SD-OCT) volumes is particularly challenging due to the projected neural canal opening (NCO) and relatively low visibility in the ONH center. Color fundus photographs provide a relatively high vessel contrast in the region inside the NCO, but have not been previously used to aid the SD-OCT vessel segmentation process. Thus, in this paper, we present two approaches for the segmentation of retinal vessels in SD-OCT volumes that each take advantage of complimentary information from fundus photographs. In the first approach (referred to as the registered-fundus vessel segmentation approach), vessels are first segmented on the fundus photograph directly (using a k-NN pixel classifier) and this vessel segmentation result is mapped to the SD-OCT volume through the registration of the fundus photograph to the SD-OCT volume. In the second approach (referred to as the multimodal vessel segmentation approach), after fundus-to-SD-OCT registration, vessels are simultaneously segmented with a k-NN classifier using features from both modalities. Three-dimensional structural information from the intraretinal layers and neural canal opening obtained through graph-theoretic segmentation approaches of the SD-OCT volume are used in combination with Gaussian filter banks and Gabor wavelets to generate the features. The approach is trained on 15 and tested on 19 randomly chosen independent image pairs of SD-OCT volumes and fundus images from 34 subjects with glaucoma. Based on a receiver operating characteristic (ROC) curve analysis, the present registered-fundus and multimodal vessel segmentation approaches [area under the curve (AUC) of 0.85 and 0.89, respectively] both perform significantly better than the two previous OCT-based approaches (AUC of 0.78 and 0.83, p < 0.05). The multimodal approach overall performs significantly better than the other three approaches (p < 0

  13. Semi-automatic procedure to extract Couinaud liver segments from multislice CT data

    NASA Astrophysics Data System (ADS)

    Varma, Jay; Durgan, Jacob; Subramanyan, Krishna

    2003-05-01

    Liver resection and transplantation surgeries require careful planning and accurate knowledge of the vascular and gross anatomy of the liver. This study aims to create a semi-automatic method for segmenting the liver, along with its entire venous vessel tree from multi-detector computed tomograms. Using fast marching and region-growth techniques along with morphological operations, we have developed a software package which can isolate the liver and the hepatic venous network from a user-selected seed point. The user is then presented with volumetric analysis of the liver and a 3-Dimensional surface rendering. Software tools allow the user to then analyze the lobes of the liver based upon venous anatomy, as defined by Couinaud. The software package also has utilities for data management, key image specification, commenting, and reporting. Seven patients were scanned with contrast on the Mx8000 CT scanner (Philips Medical Systems), the data was analyzed using our method and compared with results found using a manual method. The results show that the semi-automated method utilizes less time than manual methods, with results that are consistent and similar. Also, display of the venous network along with the entire liver in three dimensions is a unique feature of this software.

  14. Computerized detection of pulmonary embolism in computed tomographic pulmonary angiography (CTPA): improvement of vessel segmentation

    NASA Astrophysics Data System (ADS)

    Zhou, Chuan; Chan, Heang-Ping; Kuriakose, Jean W.; Chughtai, Aamer; Hadjiiski, Lubomir M.; Wei, Jun; Patel, Smita; Kazerooni, Ella A.

    2011-03-01

    Vessel segmentation is a fundamental step in an automated pulmonary embolism (PE) detection system. The purpose of this study is to improve the segmentation scheme for pulmonary vessels affected by PE and other lung diseases. We have developed a multiscale hierarchical vessel enhancement and segmentation (MHES) method for pulmonary vessel tree extraction based on the analysis of eigenvalues of Hessian matrices. However, it is difficult to segment the pulmonary vessels accurately when the vessel is occluded by PEs and/or surrounded by lymphoid tissues or lung diseases. In this study, we developed a method that combines MHES with level set refinement (MHES-LSR) to improve vessel segmentation accuracy. The level set was designed to propagate the initial object contours to the regions with relatively high gray-level, high gradient, and high compactness as measured by the smoothness of the curvature along vessel boundaries. Two and eight CTPA scans were randomly selected as training and test data sets, respectively. Forty volumes of interest (VOI) containing "representative" vessels were manually segmented by a radiologist experienced in CTPA interpretation and used as reference standard. The results show that, for the 32 test VOIs, the average percentage volume error relative to the reference standard was improved from 31.7+/-10.9% using the MHES method to 7.7+/-4.7% using the MHES-LSR method. The correlation between the computer-segmented vessel volume and the reference standard was improved from 0.954 to 0.986. The accuracy of vessel segmentation was improved significantly (p<0.05). The MHES-LSR method may have the potential to improve PE detection.

  15. A 2D driven 3D vessel segmentation algorithm for 3D digital subtraction angiography data.

    PubMed

    Spiegel, M; Redel, T; Struffert, T; Hornegger, J; Doerfler, A

    2011-10-01

    Cerebrovascular disease is among the leading causes of death in western industrial nations. 3D rotational angiography delivers indispensable information on vessel morphology and pathology. Physicians make use of this to analyze vessel geometry in detail, i.e. vessel diameters, location and size of aneurysms, to come up with a clinical decision. 3D segmentation is a crucial step in this pipeline. Although a lot of different methods are available nowadays, all of them lack a method to validate the results for the individual patient. Therefore, we propose a novel 2D digital subtraction angiography (DSA)-driven 3D vessel segmentation and validation framework. 2D DSA projections are clinically considered as gold standard when it comes to measurements of vessel diameter or the neck size of aneurysms. An ellipsoid vessel model is applied to deliver the initial 3D segmentation. To assess the accuracy of the 3D vessel segmentation, its forward projections are iteratively overlaid with the corresponding 2D DSA projections. Local vessel discrepancies are modeled by a global 2D/3D optimization function to adjust the 3D vessel segmentation toward the 2D vessel contours. Our framework has been evaluated on phantom data as well as on ten patient datasets. Three 2D DSA projections from varying viewing angles have been used for each dataset. The novel 2D driven 3D vessel segmentation approach shows superior results against state-of-the-art segmentations like region growing, i.e. an improvement of 7.2% points in precision and 5.8% points for the Dice coefficient. This method opens up future clinical applications requiring the greatest vessel accuracy, e.g. computational fluid dynamic modeling. PMID:21908904

  16. A 2D driven 3D vessel segmentation algorithm for 3D digital subtraction angiography data

    NASA Astrophysics Data System (ADS)

    Spiegel, M.; Redel, T.; Struffert, T.; Hornegger, J.; Doerfler, A.

    2011-10-01

    Cerebrovascular disease is among the leading causes of death in western industrial nations. 3D rotational angiography delivers indispensable information on vessel morphology and pathology. Physicians make use of this to analyze vessel geometry in detail, i.e. vessel diameters, location and size of aneurysms, to come up with a clinical decision. 3D segmentation is a crucial step in this pipeline. Although a lot of different methods are available nowadays, all of them lack a method to validate the results for the individual patient. Therefore, we propose a novel 2D digital subtraction angiography (DSA)-driven 3D vessel segmentation and validation framework. 2D DSA projections are clinically considered as gold standard when it comes to measurements of vessel diameter or the neck size of aneurysms. An ellipsoid vessel model is applied to deliver the initial 3D segmentation. To assess the accuracy of the 3D vessel segmentation, its forward projections are iteratively overlaid with the corresponding 2D DSA projections. Local vessel discrepancies are modeled by a global 2D/3D optimization function to adjust the 3D vessel segmentation toward the 2D vessel contours. Our framework has been evaluated on phantom data as well as on ten patient datasets. Three 2D DSA projections from varying viewing angles have been used for each dataset. The novel 2D driven 3D vessel segmentation approach shows superior results against state-of-the-art segmentations like region growing, i.e. an improvement of 7.2% points in precision and 5.8% points for the Dice coefficient. This method opens up future clinical applications requiring the greatest vessel accuracy, e.g. computational fluid dynamic modeling.

  17. A liver registration method for segmented multi-phase CT images

    NASA Astrophysics Data System (ADS)

    Shi, Shuyue; Yuan, Rong; Sun, Zhi; Xie, Qingguo

    2015-03-01

    In order to build high quality geometric models for liver containing vascular system, multi-phase CT series used in a computer-aided diagnosis and surgical planning system aims at liver diseases have to be accurately registered. In this paper we model the segmented liver containing vascular system as a complex shape and propose a two-step registration method. Without any tree modeling for vessel this method can carry out a simultaneous registration for both liver tissue and vascular system inside. Firstly a rigid aligning using vessel as feature is applied on the complex shape model while genetic algorithm is used as the optimization method. Secondly we achieve the elastic shape registration by combine the incremental free form deformation (IFFD) with a modified iterative closest point (ICP) algorithm. Inspired by the concept of demons method, we propose to calculate a fastest diffusion vector (FDV) for each control point on the IFFD lattice to replace the points correspondence needed in ICP iterations. Under the iterative framework of the modified ICP, the optimal solution of control points' displacement in every IFFD level can be obtained efficiently. The method has been quantitatively evaluated on clinical multi-phase CT series.

  18. A vessel active contour model for vascular segmentation.

    PubMed

    Tian, Yun; Chen, Qingli; Wang, Wei; Peng, Yu; Wang, Qingjun; Duan, Fuqing; Wu, Zhongke; Zhou, Mingquan

    2014-01-01

    This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field. Firstly, the energy function we define is evaluated along the evolving curve instead of all image points, and the function value at each point on the curve is based on the interior and exterior weighted means in a local neighborhood of the point, which is good for dealing with the intensity inhomogeneity. Secondly, a vascular vector field derived from a vesselness measure is employed to guide the contour to evolve along the vessel central skeleton into thin and weak vessels. Thirdly, an automatic initialization method that makes the model converge rapidly is developed, and it avoids repeated trails in conventional local region active contour models. Finally, a speed-up strategy is implemented by labeling the steadily evolved points, and it avoids the repeated computation of these points in the subsequent iterations. Experiments using synthetic and real vessel images validate the proposed model. Comparisons with the localized active contour model, local binary fitting model, and vascular active contour model show that the proposed model is more accurate, efficient, and suitable for extraction of the vessel tree from different medical images. PMID:25101262

  19. A Vessel Active Contour Model for Vascular Segmentation

    PubMed Central

    Chen, Qingli; Wang, Wei; Peng, Yu; Wang, Qingjun; Wu, Zhongke; Zhou, Mingquan

    2014-01-01

    This paper proposes a vessel active contour model based on local intensity weighting and a vessel vector field. Firstly, the energy function we define is evaluated along the evolving curve instead of all image points, and the function value at each point on the curve is based on the interior and exterior weighted means in a local neighborhood of the point, which is good for dealing with the intensity inhomogeneity. Secondly, a vascular vector field derived from a vesselness measure is employed to guide the contour to evolve along the vessel central skeleton into thin and weak vessels. Thirdly, an automatic initialization method that makes the model converge rapidly is developed, and it avoids repeated trails in conventional local region active contour models. Finally, a speed-up strategy is implemented by labeling the steadily evolved points, and it avoids the repeated computation of these points in the subsequent iterations. Experiments using synthetic and real vessel images validate the proposed model. Comparisons with the localized active contour model, local binary fitting model, and vascular active contour model show that the proposed model is more accurate, efficient, and suitable for extraction of the vessel tree from different medical images. PMID:25101262

  20. Automated three-dimensional choroidal vessel segmentation of 3D 1060 nm OCT retinal data

    PubMed Central

    Kajić, Vedran; Esmaeelpour, Marieh; Glittenberg, Carl; Kraus, Martin F.; Honegger, Joachim; Othara, Richu; Binder, Susanne; Fujimoto, James G.; Drexler, Wolfgang

    2012-01-01

    A fully automated, robust vessel segmentation algorithm has been developed for choroidal OCT, employing multiscale 3D edge filtering and projection of “probability cones” to determine the vessel “core”, even in the tomograms with low signal-to-noise ratio (SNR). Based on the ideal vessel response after registration and multiscale filtering, with computed depth related SNR, the vessel core estimate is dilated to quantify the full vessel diameter. As a consequence, various statistics can be computed using the 3D choroidal vessel information, such as ratios of inner (smaller) to outer (larger) choroidal vessels or the absolute/relative volume of choroid vessels. Choroidal vessel quantification can be displayed in various forms, focused and averaged within a special region of interest, or analyzed as the function of image depth. In this way, the proposed algorithm enables unique visualization of choroidal watershed zones, as well as the vessel size reduction when investigating the choroid from the sclera towards the retinal pigment epithelium (RPE). To the best of our knowledge, this is the first time that an automatic choroidal vessel segmentation algorithm is successfully applied to 1060 nm 3D OCT of healthy and diseased eyes. PMID:23304653

  1. A description of discrete vessel segments in thermal modelling of tissues

    NASA Astrophysics Data System (ADS)

    Kotte, Alexis; van Leeuwen, Gerard; de Bree, Jacob; van der Koijk, John; Crezee, Hans; Lagendijk, Jan

    1996-05-01

    In hyperthermia treatment planning vessels with a diameter larger than 0.5 mm must be treated individually. Such vessels can be described as 3D curves with associated diameters. The temperature profile along the vessel is discretized one dimensionally. Separately the tissue is discretized three dimensionally on a regular grid of voxels. The vessel as well as the tissue are positioned in one global space. Methods are supplied to describe the tissue - vessel interaction, the shift of the blood temperature profile describing the flow of blood along the vessel and the calculation of the vessel wall temperature. The calculation of the interaction is based on tissue temperature samples and the blood temperature together with the distance between the centre of the vessel and the tissue temperature sample. An analytical expression for a vessel inside a coaxial tissue cylinder is then used for the calculation of the heat flow rate across the vessel wall. The basic test system is a vessel segment embedded inside a coaxial tissue cylinder. All the tests use this setup while the following simulation parameters are varied: position and orientation of the vessel relative to the tissue grid, vessel radius, sample density of the blood temperature and power deposition inside the tissue cylinder. The blood temperature profile is examined by calculation of the local estimate of the equilibration length. All tests show excellent agreement with the theory.

  2. Automatic Coronary Artery Segmentation Using Active Search for Branches and Seemingly Disconnected Vessel Segments from Coronary CT Angiography

    PubMed Central

    Shim, Hackjoon; Jeon, Byunghwan; Jang, Yeonggul; Hong, Youngtaek; Jung, Sunghee; Ha, Seongmin; Chang, Hyuk-Jae

    2016-01-01

    We propose a Bayesian tracking and segmentation method of coronary arteries on coronary computed tomographic angiography (CCTA). The geometry of coronary arteries including lumen boundary is estimated in Maximum A Posteriori (MAP) framework. Three consecutive sphere based filtering is combined with a stochastic process that is based on the similarity of the consecutive local neighborhood voxels and the geometric constraint of a vessel. It is also founded on the prior knowledge that an artery can be seen locally disconnected and consist of branches which may be seemingly disconnected due to plaque build up. For such problem, an active search method is proposed to find branches and seemingly disconnected but actually connected vessel segments. Several new measures have been developed for branch detection, disconnection check and planar vesselness measure. Using public domain Rotterdam CT dataset, the accuracy of extracted centerline is demonstrated and automatic reconstruction of coronary artery mesh is shown. PMID:27536939

  3. Automated vessel shadow segmentation of fovea-centered spectral-domain images from multiple OCT devices

    NASA Astrophysics Data System (ADS)

    Wu, Jing; Gerendas, Bianca S.; Waldstein, Sebastian M.; Simader, Christian; Schmidt-Erfurth, Ursula

    2014-03-01

    Spectral-domain Optical Coherence Tomography (SD-OCT) is a non-invasive modality for acquiring high reso- lution, three-dimensional (3D) cross sectional volumetric images of the retina and the subretinal layers. SD-OCT also allows the detailed imaging of retinal pathology, aiding clinicians in the diagnosis of sight degrading diseases such as age-related macular degeneration (AMD) and glaucoma.1 Disease diagnosis, assessment, and treatment requires a patient to undergo multiple OCT scans, possibly using different scanning devices, to accurately and precisely gauge disease activity, progression and treatment success. However, the use of OCT imaging devices from different vendors, combined with patient movement may result in poor scan spatial correlation, potentially leading to incorrect patient diagnosis or treatment analysis. Image registration can be used to precisely compare disease states by registering differing 3D scans to one another. In order to align 3D scans from different time- points and vendors using registration, landmarks are required, the most obvious being the retinal vasculature. Presented here is a fully automated cross-vendor method to acquire retina vessel locations for OCT registration from fovea centred 3D SD-OCT scans based on vessel shadows. Noise filtered OCT scans are flattened based on vendor retinal layer segmentation, to extract the retinal pigment epithelium (RPE) layer of the retina. Voxel based layer profile analysis and k-means clustering is used to extract candidate vessel shadow regions from the RPE layer. In conjunction, the extracted RPE layers are combined to generate a projection image featuring all candidate vessel shadows. Image processing methods for vessel segmentation of the OCT constructed projection image are then applied to optimize the accuracy of OCT vessel shadow segmentation through the removal of false positive shadow regions such as those caused by exudates and cysts. Validation of segmented vessel shadows uses

  4. Blood vessel segmentation using line-direction vector based on Hessian analysis

    NASA Astrophysics Data System (ADS)

    Nimura, Yukitaka; Kitasaka, Takayuki; Mori, Kensaku

    2010-03-01

    For decision of the treatment strategy, grading of stenoses is important in diagnosis of vascular disease such as arterial occlusive disease or thromboembolism. It is also important to understand the vasculature in minimally invasive surgery such as laparoscopic surgery or natural orifice translumenal endoscopic surgery. Precise segmentation and recognition of blood vessel regions are indispensable tasks in medical image processing systems. Previous methods utilize only ``lineness'' measure, which is computed by Hessian analysis. However, difference of the intensity values between a voxel of thin blood vessel and a voxel of surrounding tissue is generally decreased by the partial volume effect. Therefore, previous methods cannot extract thin blood vessel regions precisely. This paper describes a novel blood vessel segmentation method that can extract thin blood vessels with suppressing false positives. The proposed method utilizes not only lineness measure but also line-direction vector corresponding to the largest eigenvalue in Hessian analysis. By introducing line-direction information, it is possible to distinguish between a blood vessel voxel and a voxel having a low lineness measure caused by noise. In addition, we consider the scale of blood vessel. The proposed method can reduce false positives in some line-like tissues close to blood vessel regions by utilization of iterative region growing with scale information. The experimental result shows thin blood vessel (0.5 mm in diameter, almost same as voxel spacing) can be extracted finely by the proposed method.

  5. Vessel Segmentation in Retinal Images Using Multi-scale Line Operator and K-Means Clustering

    PubMed Central

    Saffarzadeh, Vahid Mohammadi; Osareh, Alireza; Shadgar, Bita

    2014-01-01

    Detecting blood vessels is a vital task in retinal image analysis. The task is more challenging with the presence of bright and dark lesions in retinal images. Here, a method is proposed to detect vessels in both normal and abnormal retinal fundus images based on their linear features. First, the negative impact of bright lesions is reduced by using K-means segmentation in a perceptive space. Then, a multi-scale line operator is utilized to detect vessels while ignoring some of the dark lesions, which have intensity structures different from the line-shaped vessels in the retina. The proposed algorithm is tested on two publicly available STARE and DRIVE databases. The performance of the method is measured by calculating the area under the receiver operating characteristic curve and the segmentation accuracy. The proposed method achieves 0.9483 and 0.9387 localization accuracy against STARE and DRIVE respectively. PMID:24761376

  6. Leveraging Multiscale Hessian-Based Enhancement With a Novel Exudate Inpainting Technique for Retinal Vessel Segmentation.

    PubMed

    Annunziata, Roberto; Garzelli, Andrea; Ballerini, Lucia; Mecocci, Alessandro; Trucco, Emanuele

    2016-07-01

    Accurate vessel detection in retinal images is an important and difficult task. Detection is made more challenging in pathological images with the presence of exudates and other abnormalities. In this paper, we present a new unsupervised vessel segmentation approach to address this problem. A novel inpainting filter, called neighborhood estimator before filling, is proposed to inpaint exudates in a way that nearby false positives are significantly reduced during vessel enhancement. Retinal vascular enhancement is achieved with a multiple-scale Hessian approach. Experimental results show that the proposed vessel segmentation method outperforms state-of-the-art algorithms reported in the recent literature, both visually and in terms of quantitative measurements, with overall mean accuracy of 95.62% on the STARE dataset and 95.81% on the HRF dataset. PMID:26054078

  7. Segmentation and reconstruction of cerebral vessels from 3D rotational angiography for AVM embolization planning.

    PubMed

    Li, Fan; Chenoune, Yasmina; Ouenniche, Meriem; Blanc, Raphaël; Petit, Eric

    2014-01-01

    Diagnosis and computer-guided therapy of cerebral Arterio-Venous Malformations (AVM) require an accurate understanding of the cerebral vascular network both from structural and biomechanical point of view. We propose to obtain such information by analyzing three Dimensional Rotational Angiography (3DRA) images. In this paper, we describe a two-step process allowing 1) the 3D automatic segmentation of cerebral vessels from 3DRA images using a region-growing based algorithm and 2) the reconstruction of the segmented vessels using the 3D constrained Delaunay Triangulation method. The proposed algorithm was successfully applied to reconstruct cerebral blood vessels from ten datasets of 3DRA images. This software allows the neuroradiologist to separately analyze cerebral vessels for pre-operative interventions planning and therapeutic decision making. PMID:25571245

  8. A hybrid lung and vessel segmentation algorithm for computer aided detection of pulmonary embolism

    NASA Astrophysics Data System (ADS)

    Raghupathi, Laks; Lakare, Sarang

    2009-02-01

    Advances in multi-detector technology have made CT pulmonary angiography (CTPA) a popular radiological tool for pulmonary emboli (PE) detection. CTPA provide rich detail of lung anatomy and is a useful diagnostic aid in highlighting even very small PE. However analyzing hundreds of slices is laborious and time-consuming for the practicing radiologist which may also cause misdiagnosis due to the presence of various PE look-alike. Computer-aided diagnosis (CAD) can be a potential second reader in providing key diagnostic information. Since PE occurs only in vessel arteries, it is important to mark this region of interest (ROI) during CAD preprocessing. In this paper, we present a new lung and vessel segmentation algorithm for extracting contrast-enhanced vessel ROI in CTPA. Existing approaches to segmentation either provide only the larger lung area without highlighting the vessels or is computationally prohibitive. In this paper, we propose a hybrid lung and vessel segmentation which uses an initial lung ROI and determines the vessels through a series of refinement steps. We first identify a coarse vessel ROI by finding the "holes" from the lung ROI. We then use the initial ROI as seed-points for a region-growing process while carefully excluding regions which are not relevant. The vessel segmentation mask covers 99% of the 259 PE from a real-world set of 107 CTPA. Further, our algorithm increases the net sensitivity of a prototype CAD system by 5-9% across all PE categories in the training and validation data sets. The average run-time of algorithm was only 100 seconds on a standard workstation.

  9. Blood vessel segmentation and width estimation in ultra-wide field scanning laser ophthalmoscopy.

    PubMed

    Pellegrini, Enrico; Robertson, Gavin; Trucco, Emanuele; MacGillivray, Tom J; Lupascu, Carmen; van Hemert, Jano; Williams, Michelle C; Newby, David E; van Beek, Edwin; Houston, Graeme

    2014-12-01

    Features of the retinal vasculature, such as vessel widths, are considered biomarkers for systemic disease. The aim of this work is to present a supervised approach to vessel segmentation in ultra-wide field of view scanning laser ophthalmoscope (UWFoV SLO) images and to evaluate its performance in terms of segmentation and vessel width estimation accuracy. The results of the proposed method are compared with ground truth measurements from human observers and with existing state-of-the-art techniques developed for fundus camera images that we optimized for UWFoV SLO images. Our algorithm is based on multi-scale matched filters, a neural network classifier and hysteresis thresholding. After spline-based refinement of the detected vessel contours, the vessel widths are estimated from the binary maps. Such analysis is performed on SLO images for the first time. The proposed method achieves the best results, both in vessel segmentation and in width estimation, in comparison to other automatic techniques. PMID:25574441

  10. Retinal Vessel Segmentation: An Efficient Graph Cut Approach with Retinex and Local Phase

    PubMed Central

    Zhao, Yitian; Liu, Yonghuai; Wu, Xiangqian; Harding, Simon P.; Zheng, Yalin

    2015-01-01

    Our application concerns the automated detection of vessels in retinal images to improve understanding of the disease mechanism, diagnosis and treatment of retinal and a number of systemic diseases. We propose a new framework for segmenting retinal vasculatures with much improved accuracy and efficiency. The proposed framework consists of three technical components: Retinex-based image inhomogeneity correction, local phase-based vessel enhancement and graph cut-based active contour segmentation. These procedures are applied in the following order. Underpinned by the Retinex theory, the inhomogeneity correction step aims to address challenges presented by the image intensity inhomogeneities, and the relatively low contrast of thin vessels compared to the background. The local phase enhancement technique is employed to enhance vessels for its superiority in preserving the vessel edges. The graph cut-based active contour method is used for its efficiency and effectiveness in segmenting the vessels from the enhanced images using the local phase filter. We have demonstrated its performance by applying it to four public retinal image datasets (3 datasets of color fundus photography and 1 of fluorescein angiography). Statistical analysis demonstrates that each component of the framework can provide the level of performance expected. The proposed framework is compared with widely used unsupervised and supervised methods, showing that the overall framework outperforms its competitors. For example, the achieved sensitivity (0:744), specificity (0:978) and accuracy (0:953) for the DRIVE dataset are very close to those of the manual annotations obtained by the second observer. PMID:25830353

  11. Automatic retinal vessel segmentation based on active contours method in Doppler spectral-domain optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Liu, Wenzhong; Liu, Tan; Song, Wei; Yi, Ji; Zhang, Hao F.

    2013-01-01

    We achieved fast and automatic retinal vessel segmentation by employing the active contours method in Doppler spectral-domain optical coherence tomography (SD-OCT). In a typical OCT B-scan image, we first extracted the phase variations between adjacent A-lines and removed bulk motion. Then we set the initial contour as the boundary of the whole image and iterated until all of the segmented vessel contours became stabilized. Using a typical office computer, the whole segmentation took no more than 50 s, making real-time retinal vessel segmentation possible. We tested the active contours method segmentation in both controlled phantom and in vivo rodent eye images.

  12. Management of excluded segmental bile duct leakage following liver resection

    PubMed Central

    Honoré, Charles; Vibert, Eric; Hoti, Emir; Azoulay, Daniel; Adam, René; Castaing, Denis

    2009-01-01

    Background: Postoperative bile leak secondary to a fistula is a known complication of hepatic surgery. Four different biliary fistula sub-types have been described: type A refers to minor leakage from the bile duct stump; type B to major leakage caused by insufficient closure of the bile duct stump; type C to major leakage caused by injury to the bile duct, and type D (the rarest) to the division and exclusion of a bile duct. This complication results from functional liver parenchyma in which bile drainage is excluded from the main duct. Methods: A retrospective review of the database for 163 patients diagnosed with post-hepatic surgery bile leak from April 1992 to June 2007 was performed. Results: Three patients were found to have type D biliary fistula, with durations of 3–21 months. The bile leak developed after a right hepatectomy in two patients and a right hepatectomy extending to segment IV in one patient. All three patients were rescheduled for surgical exploration, following failure of medical treatment. The procedure consisted of repeat resection of the independent liver parenchyma containing the fistula. One patient developed a postoperative leak from a hepaticojejunal anastomosis (treated conservatively) and the other two patients had an uneventful recovery. No recurrence of bile leak was encountered during their follow-up. Conclusions: Our experience indicates that conservative treatment is deceptive and not efficacious. For this condition, surgical intervention is the treatment of choice because it is very effective and is associated with a low morbidity. PMID:19718366

  13. A Segmentation Algorithm for X-ray 3D Angiography and Vessel Catheterization

    SciTech Connect

    Franchi, Danilo; Rosa, Luigi; Placidi, Giuseppe

    2008-11-06

    Vessel Catheterization is a clinical procedure usually performed by a specialist by means of X-ray fluoroscopic guide with contrast-media. In the present paper, we present a simple and efficient algorithm for vessel segmentation which allows vessel separation and extraction from the background (noise and signal coming from other organs). This would reduce the number of projections (X-ray scans) to reconstruct a complete and accurate 3D vascular model and the radiological risk, in particular for the patient. In what follows, the algorithm is described and some preliminary experimental results are reported illustrating the behaviour of the proposed method.

  14. A web-based procedure for liver segmentation in CT images

    NASA Astrophysics Data System (ADS)

    Yuan, Rong; Luo, Ming; Wang, Luyao; Xie, Qingguo

    2015-03-01

    Liver segmentation in CT images has been acknowledged as a basic and indispensable part in systems of computer aided liver surgery for operation design and risk evaluation. In this paper, we will introduce and implement a web-based procedure for liver segmentation to help radiologists and surgeons get an accurate result efficiently and expediently. Several clinical datasets are used to evaluate the accessibility and the accuracy. This procedure seems a promising approach for extraction of liver volumetry of various shapes. Moreover, it is possible for user to access the segmentation wherever the Internet is available without any specific machine.

  15. Hybrid Features and Mediods Classification based Robust Segmentation of Blood Vessels.

    PubMed

    Waheed, Amna; Akram, M Usman; Khalid, Shehzad; Waheed, Zahra; Khan, Muazzam A; Shaukat, Arslan

    2015-10-01

    Retinal blood vessels are the source to provide oxygen and nutrition to retina and any change in the normal structure may lead to different retinal abnormalities. Automated detection of vascular structure is very important while designing a computer aided diagnostic system for retinal diseases. Most popular methods for vessel segmentation are based on matched filters and Gabor wavelets which give good response against blood vessels. One major drawback in these techniques is that they also give strong response for lesion (exudates, hemorrhages) boundaries which give rise to false vessels. These false vessels may lead to incorrect detection of vascular changes. In this paper, we propose a new hybrid feature set along with new classification technique for accurate detection of blood vessels. The main motivation is to lower the false positives especially from retinal images with severe disease level. A novel region based hybrid feature set is presented for proper discrimination between true and false vessels. A new modified m-mediods based classification is also presented which uses most discriminating features to categorize vessel regions into true and false vessels. The evaluation of proposed system is done thoroughly on publicly available databases along with a locally gathered database with images of advanced level of retinal diseases. The results demonstrate the validity of the proposed system as compared to existing state of the art techniques. PMID:26306876

  16. A new iterative method for liver segmentation from perfusion CT scans

    NASA Astrophysics Data System (ADS)

    Draoua, Ahmed; Albouy-Kissi, Adélaïde; Vacavant, Antoine; Sauvage, Vincent

    2014-03-01

    Liver cancer is the third most common cancer in the world, and the majority of patients with liver cancer will die within one year as a result of the cancer. Liver segmentation in the abdominal area is critical for diagnosis of tumor and for surgical procedures. Moreover, it is a challenging task as liver tissue has to be separated from adjacent organs and substantially the heart. In this paper we present a novel liver segmentation iterative method based on Fuzzy C-means (FCM) coupled with a fast marching segmentation and mutual information. A prerequisite for this method is the determination of slice correspondences between ground truth that is, a few images segmented by an expert, and images that contain liver and heart at the same time.

  17. Automatic segmentation of lymph vessel wall using optimal surface graph cut and hidden Markov Models.

    PubMed

    Jones, Jonathan-Lee; Essa, Ehab; Xie, Xianghua

    2015-08-01

    We present a novel method to segment the lymph vessel wall in confocal microscopy images using Optimal Surface Segmentation (OSS) and hidden Markov Models (HMM). OSS is used to preform a pre-segmentation on the images, to act as the initial state for the HMM. We utilize a steerable filter to determine edge based filters for both of these segmentations, and use these features to build Gaussian probability distributions for both the vessel walls and the background. From this we infer the emission probability for the HMM, and the transmission probability is learned using a Baum-Welch algorithm. We transform the segmentation problem into one of cost minimization, with each node in the graph corresponding to one state, and the weight for each node being defined using its emission probability. We define the inter-relations between neighboring nodes using the transmission probability. Having constructed the problem, it is solved using the Viterbi algorithm, allowing the vessel to be reconstructed. The optimal solution can be found in polynomial time. We present qualitative and quantitative analysis to show the performance of the proposed method. PMID:26736778

  18. A Cross-Modality Learning Approach for Vessel Segmentation in Retinal Images.

    PubMed

    Li, Qiaoliang; Feng, Bowei; Xie, LinPei; Liang, Ping; Zhang, Huisheng; Wang, Tianfu

    2016-01-01

    This paper presents a new supervised method for vessel segmentation in retinal images. This method remolds the task of segmentation as a problem of cross-modality data transformation from retinal image to vessel map. A wide and deep neural network with strong induction ability is proposed to model the transformation, and an efficient training strategy is presented. Instead of a single label of the center pixel, the network can output the label map of all pixels for a given image patch. Our approach outperforms reported state-of-the-art methods in terms of sensitivity, specificity and accuracy. The result of cross-training evaluation indicates its robustness to the training set. The approach needs no artificially designed feature and no preprocessing step, reducing the impact of subjective factors. The proposed method has the potential for application in image diagnosis of ophthalmologic diseases, and it may provide a new, general, high-performance computing framework for image segmentation. PMID:26208306

  19. Adaptive Thresholding Technique for Retinal Vessel Segmentation Based on GLCM-Energy Information

    PubMed Central

    Mapayi, Temitope; Viriri, Serestina; Tapamo, Jules-Raymond

    2015-01-01

    Although retinal vessel segmentation has been extensively researched, a robust and time efficient segmentation method is highly needed. This paper presents a local adaptive thresholding technique based on gray level cooccurrence matrix- (GLCM-) energy information for retinal vessel segmentation. Different thresholds were computed using GLCM-energy information. An experimental evaluation on DRIVE database using the grayscale intensity and Green Channel of the retinal image demonstrates the high performance of the proposed local adaptive thresholding technique. The maximum average accuracy rates of 0.9511 and 0.9510 with maximum average sensitivity rates of 0.7650 and 0.7641 were achieved on DRIVE and STARE databases, respectively. When compared to the widely previously used techniques on the databases, the proposed adaptive thresholding technique is time efficient with a higher average sensitivity and average accuracy rates in the same range of very good specificity. PMID:25802550

  20. Segmentation of Blood Vessels and 3D Representation of CMR Image

    NASA Astrophysics Data System (ADS)

    Jiji, G. W.

    2013-06-01

    Current cardiac magnetic resonance imaging (CMR) technology allows the determination of patient-individual coronary tree structure, detection of infarctions, and assessment of myocardial perfusion. The purpose of this work is to segment heart blood vessels and visualize it in 3D. In this work, 3D visualisation of vessel was performed into four phases. The first step is to detect the tubular structures using multiscale medialness function, which distinguishes tube-like structures from and other structures. Second step is to extract the centrelines of the tubes. From the centreline radius the cylindrical tube model is constructed. The third step is segmentation of the tubular structures. The cylindrical tube model is used in segmentation process. Fourth step is to 3D representation of the tubular structure using Volume . The proposed approach is applied to 10 datasets of patients from the clinical routine and tested the results with radiologists.

  1. Automated multimodality concurrent classification for segmenting vessels in 3D spectral OCT and color fundus images

    NASA Astrophysics Data System (ADS)

    Hu, Zhihong; Abràmoff, Michael D.; Niemeijer, Meindert; Garvin, Mona K.

    2011-03-01

    Segmenting vessels in spectral-domain optical coherence tomography (SD-OCT) volumes is particularly challenging in the region near and inside the neural canal opening (NCO). Furthermore, accurately segmenting them in color fundus photographs also presents a challenge near the projected NCO. However, both modalities also provide complementary information to help indicate vessels, such as a better NCO contrast from the NCO-aimed OCT projection image and a better vessel contrast inside the NCO from fundus photographs. We thus present a novel multimodal automated classification approach for simultaneously segmenting vessels in SD-OCT volumes and fundus photographs, with a particular focus on better segmenting vessels near and inside the NCO by using a combination of their complementary features. In particular, in each SD-OCT volume, the algorithm pre-segments the NCO using a graph-theoretic approach and then applies oriented Gabor wavelets with oriented NCO-based templates to generate OCT image features. After fundus-to-OCT registration, the fundus image features are computed using Gaussian filter banks and combined with OCT image features. A k-NN classifier is trained on 5 and tested on 10 randomly chosen independent image pairs of SD-OCT volumes and fundus images from 15 subjects with glaucoma. Using ROC analysis, we demonstrate an improvement over two closest previous works performed in single modal SD-OCT volumes with an area under the curve (AUC) of 0.87 (0.81 for our and 0.72 for Niemeijer's single modal approach) in the region around the NCO and 0.90 outside the NCO (0.84 for our and 0.81 for Niemeijer's single modal approach).

  2. Retinal vessel segmentation using multi-scale textons derived from keypoints.

    PubMed

    Zhang, Lei; Fisher, Mark; Wang, Wenjia

    2015-10-01

    This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter parameters are derived from a smaller set of image features that we call keypoints. A Gabor filter bank, parameterised empirically by ROC analysis, is used to extract keypoints representing significant scale specific vessel features using an approach inspired by the SIFT algorithm. We first determine keypoints using a validation set and then derive seeds from these points to initialise a k-means clustering algorithm which builds a texton dictionary from another training set. During testing we use a simple 1-NN classifier to identify vessel/non-vessel pixels and evaluate our system using the DRIVE database. We achieve average values of sensitivity, specificity and accuracy of 78.12%, 96.68% and 95.05%, respectively. We find that clusters of filter responses from keypoints are more robust than those derived from hand-labelled pixels. This, in turn yields textons more representative of vessel/non-vessel classes and mitigates problems arising due to intra and inter-observer variability. PMID:26265241

  3. Automatic 2D and 3D segmentation of liver from Computerised Tomography

    NASA Astrophysics Data System (ADS)

    Evans, Alun

    As part of the diagnosis of liver disease, a Computerised Tomography (CT) scan is taken of the patient, which the clinician then uses for assistance in determining the presence and extent of the disease. This thesis presents the background, methodology, results and future work of a project that employs automated methods to segment liver tissue. The clinical motivation behind this work is the desire to facilitate the diagnosis of liver disease such as cirrhosis or cancer, assist in volume determination for liver transplantation, and possibly assist in measuring the effect of any treatment given to the liver. Previous attempts at automatic segmentation of liver tissue have relied on 2D, low-level segmentation techniques, such as thresholding and mathematical morphology, to obtain the basic liver structure. The derived boundary can then be smoothed or refined using more advanced methods. The 2D results presented in this thesis improve greatly on this previous work by using a topology adaptive active contour model to accurately segment liver tissue from CT images. The use of conventional snakes for liver segmentation is difficult due to the presence of other organs closely surrounding the liver this new technique avoids this problem by adding an inflationary force to the basic snake equation, and initialising the snake inside the liver. The concepts underlying the 2D technique are extended to 3D, and results of full 3D segmentation of the liver are presented. The 3D technique makes use of an inflationary active surface model which is adaptively reparameterised, according to its size and local curvature, in order that it may more accurately segment the organ. Statistical analysis of the accuracy of the segmentation is presented for 18 healthy liver datasets, and results of the segmentation of unhealthy livers are also shown. The novel work developed during the course of this project has possibilities for use in other areas of medical imaging research, for example the

  4. A method for automatic liver segmentation from multi-phase contrast-enhanced CT images

    NASA Astrophysics Data System (ADS)

    Yuan, Rong; Luo, Ming; Wang, Shaofa; Wang, Luyao; Xie, Qingguo

    2014-03-01

    Liver segmentation is a basic and indispensable function in systems of computer aided liver surgery for volume calculation, operation designing and risk evaluation. Traditional manual segmentation is very time consuming because of the complicated contours of liver and the big amount of images. For increasing the efficiency of the clinical work, in this paper, a fully-automatic method was proposed to segment the liver from multi-phase contrast-enhanced computed tomography (CT) images. As an advanced region growing method, we applied various pre- and post-processing to get better segmentation from the different phases. Fifteen sets of clinical abdomens CT images of five patients were segmented by our algorithm, and the results were acceptable and evaluated by an experienced surgeon. The running-time is about 30 seconds for a single-phase data which includes more than 200 slices.

  5. Atlas-based liver segmentation and hepatic fat-fraction assessment for clinical trials.

    PubMed

    Yan, Zhennan; Zhang, Shaoting; Tan, Chaowei; Qin, Hongxing; Belaroussi, Boubakeur; Yu, Hui Jing; Miller, Colin; Metaxas, Dimitris N

    2015-04-01

    Automated assessment of hepatic fat-fraction is clinically important. A robust and precise segmentation would enable accurate, objective and consistent measurement of hepatic fat-fraction for disease quantification, therapy monitoring and drug development. However, segmenting the liver in clinical trials is a challenging task due to the variability of liver anatomy as well as the diverse sources the images were acquired from. In this paper, we propose an automated and robust framework for liver segmentation and assessment. It uses single statistical atlas registration to initialize a robust deformable model to obtain fine segmentation. Fat-fraction map is computed by using chemical shift based method in the delineated region of liver. This proposed method is validated on 14 abdominal magnetic resonance (MR) volumetric scans. The qualitative and quantitative comparisons show that our proposed method can achieve better segmentation accuracy with less variance comparing with two other atlas-based methods. Experimental results demonstrate the promises of our assessment framework. PMID:24962337

  6. Automatic Liver Segmentation from CT Images Using Single-Block Linear Detection

    PubMed Central

    2016-01-01

    Automatic liver segmentation not only plays an important role in the analysis of liver disease, but also reduces the cost and humanity's impact in segmentation. In addition, liver segmentation is a very challenging task due to countless anatomical variations and technical difficulties. Many methods have been designed to overcome these challenges, but these methods still need to be improved to obtain the desired segmentation precision. In this paper, a fast algorithm is proposed for liver extraction from CT images with single-block linear detection. The proposed method does not require iteration; thus, the computational time and complexity are decreased enormously. In addition, the initialization is not crucial in the algorithm, so the algorithm's robustness and specificity are improved. The experimental evaluation of the proposed method revealed effective segmentation in normal and abnormal (liver hemangioma and liver cancer) abdominal CT images. The average sensitivity, accuracy, and specificity for liver cancer are 96.59%, 98.65%, and 99.03%, respectively. The results of image segmentation approximate the manual segmentation results by the technical doctor. Moreover, our method shows superior flexibility to newly published method with comparable performance. The advantage of our method is verified with experimental results, which is described in detail.

  7. Segmentation of retinal vessels by means of directional response vector similarity and region growing.

    PubMed

    Lázár, István; Hajdu, András

    2015-11-01

    This paper presents a novel retinal vessel segmentation method. Opposed to the general approach in similar directional methods, where only the maximal or summed responses of a pixel are used, here, the directional responses of a pixel are considered as a vector. The segmentation method is a unique region growing procedure which combines a hysteresis thresholding scheme with the response vector similarity of adjacent pixels. A vessel score map is constructed as the combination of the statistical measures of the response vectors and its local maxima to provide the seeds for the region growing procedure. A nearest neighbor classifier based on a rotation invariant response vector similarity measure is used to filter the seed points. Many techniques in the literature that capture the Gaussian-like cross-section of vessels suffer from the drawback of giving false high responses to the steep intensity transitions at the boundary of the optic disc and bright lesions. To overcome this issue, we also propose a symmetry constrained multiscale matched filtering technique. The proposed vessel segmentation method has been tested on three publicly available image sets, where its performance proved to be competitive with the state-of-the-art and comparable to the accuracy of a human observer, as well. PMID:26432200

  8. CT liver volumetry using geodesic active contour segmentation with a level-set algorithm

    NASA Astrophysics Data System (ADS)

    Suzuki, Kenji; Epstein, Mark L.; Kohlbrenner, Ryan; Obajuluwa, Ademola; Xu, Jianwu; Hori, Masatoshi; Baron, Richard

    2010-03-01

    Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.

  9. Segmentation and quantification of blood vessels for OCT-based micro-angiograms using hybrid shape/intensity compounding

    PubMed Central

    Yousefi, Siavash; Liu, Ting; Wang, Ruikang K.

    2014-01-01

    Optical coherence tomography (OCT) based microangiography is capable of visualizing 3D functional blood vessel networks within microcirculatory tissue beds in vivo. To provide the quantitative information of vasculature from the microangiograms such as vessel diameter and morphology, it is necessary to develop efficient vessel segmentation algorithms. In this paper, we propose to develop a hybrid Hessian/intensity based method to segment and quantify shape and diameter of the blood vessels innervating capillary beds that are imaged by functional OCT in vivo. The proposed method utilizes the multi-scale Hessian filters to segment tubular structures such as blood vessels, but compounded by the intensity-based segmentation method to mitigate the limitations of Hessian filter's sensitivity to the selection of scale parameters. Such compounding segmentation scheme takes the advantage of morphological nature of Hessian filters while correcting for the scale parameter selection by intensity-based segmentation. The proposed algorithm is tested on a wound healing model and its performance of segmentation vessels is quantified by a publicly available manual segmentation dataset. We believe that this method will play an important role in the quantification of micro-angiograms for microcirculation research in ophthalmology and diagnosing retinal eye diseases involved with microcirculation. PMID:25283347

  10. Detection and characterization of flaws in segments of light water reactor pressure vessels

    SciTech Connect

    Cook, K.V.; Cunningham, R.A. Jr.; McClung, R.W.

    1987-01-01

    Studies have been conducted to determine flaw density in segments cut from light water reactor (LWR) pressure vessels as part of the Oak Ridge National Laboratory's Heavy-Section Steel Technology (HSST) Program. Segments from the Hope Creek Unit 2 vessil and the Pilgrim Unit 2 Vessel were purchased from salvage dealers. Hope Creek was a boiling water reactor (BWR) design and Pilgrim was a pressurized water reactor (PWR) design. Neither were ever placed in service. Objectives were to evaluate these LWR segments for flaws with ultrasonic and liquid penetrant techniques. Both objectives were successfully completed. One significant indication was detected in a Hope Creek seam weld by ultrasonic techniques and characterized by further analyses terminating with destructive correlation. This indication (with a through-wall dimension of approx.6 mm (approx.0.24 in.)) was detected in only 3 m (10 ft) of weldment and offers extremely limited data when compared to the extent of welding even in a single pressure vessel. However, the detection and confirmation of the flaw in the arbitrarily selected sections implies the Marshall report estimates (and others) are nonconservative for such small flaws. No significant indications were detected in the Pilgrim material by ultrasonic techniques. Unfortunately, the Pilgrim segments contained relatively little weldment; thus, we limited our ultrasonic examinations to the cladding and subcladding regions. Fluorescent liquid penetrant inspection of the cladding surfaces for both LWR segments detected no significant indications (i.e., for a total of approximately 6.8 m/sup 2/ (72 ft/sup 2/) of cladding surface).

  11. Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring

    PubMed Central

    Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

    2016-01-01

    Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis play an important role in the choice of therapeutic strategies for liver diseases and treatment monitoring. In this paper, a new segmentation method for liver tumors from contrast-enhanced CT imaging is proposed. As manual segmentation of tumors for liver treatment planning is both labor intensive and time-consuming, a highly accurate automatic tumor segmentation is desired. The proposed framework is fully automatic requiring no user interaction. The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. The proposed method was able to achieve one of the highest accuracies reported in the literature for liver tumor segmentation compared to other segmentation methods with a mean overlap error of 22.78 % and dice similarity coefficient of 0.75 in 3Dircadb dataset and a mean overlap error of 15.61 % and dice similarity coefficient of 0.81 in MIDAS dataset. The proposed method was able to outperform most other tumor segmentation methods reported in the literature while representing an overlap error improvement of 6 % compared to one of the best performing automatic methods in the literature. The proposed framework was able to provide consistently accurate results considering the number of tumors and the variations in tumor contrast enhancements and tumor appearances while the tumor burden was estimated with a mean error of 0.84 % in 3Dircadb dataset. PMID:27540353

  12. Automatic liver tumor segmentation on computed tomography for patient treatment planning and monitoring.

    PubMed

    Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M Iqbal Bin

    2016-01-01

    Segmentation of liver tumors from Computed Tomography (CT) and tumor burden analysis play an important role in the choice of therapeutic strategies for liver diseases and treatment monitoring. In this paper, a new segmentation method for liver tumors from contrast-enhanced CT imaging is proposed. As manual segmentation of tumors for liver treatment planning is both labor intensive and time-consuming, a highly accurate automatic tumor segmentation is desired. The proposed framework is fully automatic requiring no user interaction. The proposed segmentation evaluated on real-world clinical data from patients is based on a hybrid method integrating cuckoo optimization and fuzzy c-means algorithm with random walkers algorithm. The accuracy of the proposed method was validated using a clinical liver dataset containing one of the highest numbers of tumors utilized for liver tumor segmentation containing 127 tumors in total with further validation of the results by a consultant radiologist. The proposed method was able to achieve one of the highest accuracies reported in the literature for liver tumor segmentation compared to other segmentation methods with a mean overlap error of 22.78 % and dice similarity coefficient of 0.75 in 3Dircadb dataset and a mean overlap error of 15.61 % and dice similarity coefficient of 0.81 in MIDAS dataset. The proposed method was able to outperform most other tumor segmentation methods reported in the literature while representing an overlap error improvement of 6 % compared to one of the best performing automatic methods in the literature. The proposed framework was able to provide consistently accurate results considering the number of tumors and the variations in tumor contrast enhancements and tumor appearances while the tumor burden was estimated with a mean error of 0.84 % in 3Dircadb dataset. PMID:27540353

  13. Phantom-based ground-truth generation for cerebral vessel segmentation and pulsatile deformation analysis

    NASA Astrophysics Data System (ADS)

    Schetelig, Daniel; Säring, Dennis; Illies, Till; Sedlacik, Jan; Kording, Fabian; Werner, René

    2016-03-01

    Hemodynamic and mechanical factors of the vascular system are assumed to play a major role in understanding, e.g., initiation, growth and rupture of cerebral aneurysms. Among those factors, cardiac cycle-related pulsatile motion and deformation of cerebral vessels currently attract much interest. However, imaging of those effects requires high spatial and temporal resolution and remains challenging { and similarly does the analysis of the acquired images: Flow velocity changes and contrast media inflow cause vessel intensity variations in related temporally resolved computed tomography and magnetic resonance angiography data over the cardiac cycle and impede application of intensity threshold-based segmentation and subsequent motion analysis. In this work, a flow phantom for generation of ground-truth images for evaluation of appropriate segmentation and motion analysis algorithms is developed. The acquired ground-truth data is used to illustrate the interplay between intensity fluctuations and (erroneous) motion quantification by standard threshold-based segmentation, and an adaptive threshold-based segmentation approach is proposed that alleviates respective issues. The results of the phantom study are further demonstrated to be transferable to patient data.

  14. Quantitative evaluation of six graph based semi-automatic liver tumor segmentation techniques using multiple sets of reference segmentation

    NASA Astrophysics Data System (ADS)

    Su, Zihua; Deng, Xiang; Chefd'hotel, Christophe; Grady, Leo; Fei, Jun; Zheng, Dong; Chen, Ning; Xu, Xiaodong

    2011-03-01

    Graph based semi-automatic tumor segmentation techniques have demonstrated great potential in efficiently measuring tumor size from CT images. Comprehensive and quantitative validation is essential to ensure the efficacy of graph based tumor segmentation techniques in clinical applications. In this paper, we present a quantitative validation study of six graph based 3D semi-automatic tumor segmentation techniques using multiple sets of expert segmentation. The six segmentation techniques are Random Walk (RW), Watershed based Random Walk (WRW), LazySnapping (LS), GraphCut (GHC), GrabCut (GBC), and GrowCut (GWC) algorithms. The validation was conducted using clinical CT data of 29 liver tumors and four sets of expert segmentation. The performance of the six algorithms was evaluated using accuracy and reproducibility. The accuracy was quantified using Normalized Probabilistic Rand Index (NPRI), which takes into account of the variation of multiple expert segmentations. The reproducibility was evaluated by the change of the NPRI from 10 different sets of user initializations. Our results from the accuracy test demonstrated that RW (0.63) showed the highest NPRI value, compared to WRW (0.61), GWC (0.60), GHC (0.58), LS (0.57), GBC (0.27). The results from the reproducibility test indicated that GBC is more sensitive to user initialization than the other five algorithms. Compared to previous tumor segmentation validation studies using one set of reference segmentation, our evaluation methods use multiple sets of expert segmentation to address the inter or intra rater variability issue in ground truth annotation, and provide quantitative assessment for comparing different segmentation algorithms.

  15. Liver segmentation with new supervised method to create initial curve for active contour.

    PubMed

    Zareei, Abouzar; Karimi, Abbas

    2016-08-01

    The liver performs a critical task in the human body; therefore, detecting liver diseases and preparing a robust plan for treating them are both crucial. Liver diseases kill nearly 25,000 Americans every year. A variety of image segmentation methods are available to determine the liver's position and to detect possible liver tumors. Among these is the Active Contour Model (ACM), a framework which has proven very sensitive to initial contour delineation and control parameters. In the proposed method based on image energy, we attempted to obtain an initial segmentation close to the liver's boundary, and then implemented an ACM to improve the initial segmentation. The ACM used in this work incorporates gradient vector flow (GVF) and balloon energy in order to overcome ACM limitations, such as local minima entrapment and initial contour dependency. Additionally, in order to adjust active contour control parameters, we applied a genetic algorithm to produce a proper parameter set close to the optimal solution. The pre-processing method has a better ability to segment the liver tissue during a short time with respect to other mentioned methods in this paper. The proposed method was performed using Sliver CT image datasets. The results show high accuracy, precision, sensitivity, specificity and low overlap error, MSD and runtime with few ACM iterations. PMID:27286186

  16. Exploratory Dijkstra forest based automatic vessel segmentation: applications in video indirect ophthalmoscopy (VIO).

    PubMed

    Estrada, Rolando; Tomasi, Carlo; Cabrera, Michelle T; Wallace, David K; Freedman, Sharon F; Farsiu, Sina

    2012-02-01

    We present a methodology for extracting the vascular network in the human retina using Dijkstra's shortest-path algorithm. Our method preserves vessel thickness, requires no manual intervention, and follows vessel branching naturally and efficiently. To test our method, we constructed a retinal video indirect ophthalmoscopy (VIO) image database from pediatric patients and compared the segmentations achieved by our method and state-of-the-art approaches to a human-drawn gold standard. Our experimental results show that our algorithm outperforms prior state-of-the-art methods, for both single VIO frames and automatically generated, large field-of-view enhanced mosaics. We have made the corresponding dataset and source code freely available online. PMID:22312585

  17. An ensemble classification-based approach applied to retinal blood vessel segmentation.

    PubMed

    Fraz, Muhammad Moazam; Remagnino, Paolo; Hoppe, Andreas; Uyyanonvara, Bunyarit; Rudnicka, Alicja R; Owen, Christopher G; Barman, Sarah A

    2012-09-01

    This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. This method uses an ensemble system of bagged and boosted decision trees and utilizes a feature vector based on the orientation analysis of gradient vector field, morphological transformation, line strength measures, and Gabor filter responses. The feature vector encodes information to handle the healthy as well as the pathological retinal image. The method is evaluated on the publicly available DRIVE and STARE databases, frequently used for this purpose and also on a new public retinal vessel reference dataset CHASE_DB1 which is a subset of retinal images of multiethnic children from the Child Heart and Health Study in England (CHASE) dataset. The performance of the ensemble system is evaluated in detail and the incurred accuracy, speed, robustness, and simplicity make the algorithm a suitable tool for automated retinal image analysis. PMID:22736688

  18. Computational study of pulsatile blood flow in prototype vessel geometries of coronary segments.

    PubMed

    Chaniotis, A K; Kaiktsis, L; Katritsis, D; Efstathopoulos, E; Pantos, I; Marmarellis, V

    2010-01-01

    The spatial and temporal distributions of wall shear stress (WSS) in prototype vessel geometries of coronary segments are investigated via numerical simulation, and the potential association with vascular disease and specifically atherosclerosis and plaque rupture is discussed. In particular, simulation results of WSS spatio-temporal distributions are presented for pulsatile, non-Newtonian blood flow conditions for: (a) curved pipes with different curvatures, and (b) bifurcating pipes with different branching angles and flow division. The effects of non-Newtonian flow on WSS (compared to Newtonian flow) are found to be small at Reynolds numbers representative of blood flow in coronary arteries. Specific preferential sites of average low WSS (and likely atherogenesis) were found at the outer regions of the bifurcating branches just after the bifurcation, and at the outer-entry and inner-exit flow regions of the curved vessel segment. The drop in WSS was more dramatic at the bifurcating vessel sites (less than 5% of the pre-bifurcation value). These sites were also near rapid gradients of WSS changes in space and time - a fact that increases the risk of rupture of plaque likely to develop at these sites. The time variation of the WSS spatial distributions was very rapid around the start and end of the systolic phase of the cardiac cycle, when strong fluctuations of intravascular pressure were also observed. These rapid and strong changes of WSS and pressure coincide temporally with the greatest flexion and mechanical stresses induced in the vessel wall by myocardial motion (ventricular contraction). The combination of these factors may increase the risk of plaque rupture and thrombus formation at these sites. PMID:20400349

  19. A quantum mechanics-based algorithm for vessel segmentation in retinal images

    NASA Astrophysics Data System (ADS)

    Youssry, Akram; El-Rafei, Ahmed; Elramly, Salwa

    2016-03-01

    Blood vessel segmentation is an important step in retinal image analysis. It is one of the steps required for computer-aided detection of ophthalmic diseases. In this paper, a novel quantum mechanics-based algorithm for retinal vessel segmentation is presented. The algorithm consists of three major steps. The first step is the preprocessing of the images to prepare the images for further processing. The second step is feature extraction where a set of four features is generated at each image pixel. These features are then combined using a nonlinear transformation for dimensionality reduction. The final step is applying a recently proposed quantum mechanics-based framework for image processing. In this step, pixels are mapped to quantum systems that are allowed to evolve from an initial state to a final state governed by Schrödinger's equation. The evolution is controlled by the Hamiltonian operator which is a function of the extracted features at each pixel. A measurement step is consequently performed to determine whether the pixel belongs to vessel or non-vessel classes. Many functional forms of the Hamiltonian are proposed, and the best performing form was selected. The algorithm is tested on the publicly available DRIVE database. The average results for sensitivity, specificity, and accuracy are 80.29, 97.34, and 95.83 %, respectively. These results are compared to some recently published techniques showing the superior performance of the proposed method. Finally, the implementation of the algorithm on a quantum computer and the challenges facing this implementation are introduced.

  20. A quantum mechanics-based algorithm for vessel segmentation in retinal images

    NASA Astrophysics Data System (ADS)

    Youssry, Akram; El-Rafei, Ahmed; Elramly, Salwa

    2016-06-01

    Blood vessel segmentation is an important step in retinal image analysis. It is one of the steps required for computer-aided detection of ophthalmic diseases. In this paper, a novel quantum mechanics-based algorithm for retinal vessel segmentation is presented. The algorithm consists of three major steps. The first step is the preprocessing of the images to prepare the images for further processing. The second step is feature extraction where a set of four features is generated at each image pixel. These features are then combined using a nonlinear transformation for dimensionality reduction. The final step is applying a recently proposed quantum mechanics-based framework for image processing. In this step, pixels are mapped to quantum systems that are allowed to evolve from an initial state to a final state governed by Schrödinger's equation. The evolution is controlled by the Hamiltonian operator which is a function of the extracted features at each pixel. A measurement step is consequently performed to determine whether the pixel belongs to vessel or non-vessel classes. Many functional forms of the Hamiltonian are proposed, and the best performing form was selected. The algorithm is tested on the publicly available DRIVE database. The average results for sensitivity, specificity, and accuracy are 80.29, 97.34, and 95.83 %, respectively. These results are compared to some recently published techniques showing the superior performance of the proposed method. Finally, the implementation of the algorithm on a quantum computer and the challenges facing this implementation are introduced.

  1. Swarm Intelligence Integrated Graph-Cut for Liver Segmentation from 3D-CT Volumes

    PubMed Central

    Eapen, Maya; Korah, Reeba; Geetha, G.

    2015-01-01

    The segmentation of organs in CT volumes is a prerequisite for diagnosis and treatment planning. In this paper, we focus on liver segmentation from contrast-enhanced abdominal CT volumes, a challenging task due to intensity overlapping, blurred edges, large variability in liver shape, and complex background with cluttered features. The algorithm integrates multidiscriminative cues (i.e., prior domain information, intensity model, and regional characteristics of liver in a graph-cut image segmentation framework). The paper proposes a swarm intelligence inspired edge-adaptive weight function for regulating the energy minimization of the traditional graph-cut model. The model is validated both qualitatively (by clinicians and radiologists) and quantitatively on publically available computed tomography (CT) datasets (MICCAI 2007 liver segmentation challenge, 3D-IRCAD). Quantitative evaluation of segmentation results is performed using liver volume calculations and a mean score of 80.8% and 82.5% on MICCAI and IRCAD dataset, respectively, is obtained. The experimental result illustrates the efficiency and effectiveness of the proposed method. PMID:26689833

  2. Tumor Burden Analysis on Computed Tomography by Automated Liver and Tumor Segmentation

    PubMed Central

    Linguraru, Marius George; Richbourg, William J.; Liu, Jianfei; Watt, Jeremy M.; Pamulapati, Vivek; Wang, Shijun; Summers, Ronald M.

    2013-01-01

    The paper presents the automated computation of hepatic tumor burden from abdominal CT images of diseased populations with images with inconsistent enhancement. The automated segmentation of livers is addressed first. A novel three-dimensional (3D) affine invariant shape parameterization is employed to compare local shape across organs. By generating a regular sampling of the organ's surface, this parameterization can be effectively used to compare features of a set of closed 3D surfaces point-to-point, while avoiding common problems with the parameterization of concave surfaces. From an initial segmentation of the livers, the areas of atypical local shape are determined using training sets. A geodesic active contour corrects locally the segmentations of the livers in abnormal images. Graph cuts segment the hepatic tumors using shape and enhancement constraints. Liver segmentation errors are reduced significantly and all tumors are detected. Finally, support vector machines and feature selection are employed to reduce the number of false tumor detections. The tumor detection true position fraction of 100% is achieved at 2.3 false positives/case and the tumor burden is estimated with 0.9% error. Results from the test data demonstrate the method's robustness to analyze livers from difficult clinical cases to allow the temporal monitoring of patients with hepatic cancer. PMID:22893379

  3. 3D active surfaces for liver segmentation in multisequence MRI images.

    PubMed

    Bereciartua, Arantza; Picon, Artzai; Galdran, Adrian; Iriondo, Pedro

    2016-08-01

    Biopsies for diagnosis can sometimes be replaced by non-invasive techniques such as CT and MRI. Surgeons require accurate and efficient methods that allow proper segmentation of the organs in order to ensure the most reliable intervention planning. Automated liver segmentation is a difficult and open problem where CT has been more widely explored than MRI. MRI liver segmentation represents a challenge due to the presence of characteristic artifacts, such as partial volumes, noise and low contrast. In this paper, we present a novel method for multichannel MRI automatic liver segmentation. The proposed method consists of the minimization of a 3D active surface by means of the dual approach to the variational formulation of the underlying problem. This active surface evolves over a probability map that is based on a new compact descriptor comprising spatial and multisequence information which is further modeled by means of a liver statistical model. This proposed 3D active surface approach naturally integrates volumetric regularization in the statistical model. The advantages of the compact visual descriptor together with the proposed approach result in a fast and accurate 3D segmentation method. The method was tested on 18 healthy liver studies and results were compared to a gold standard made by expert radiologists. Comparisons with other state-of-the-art approaches are provided by means of nine well established quality metrics. The obtained results improve these methodologies, achieving a Dice Similarity Coefficient of 98.59. PMID:27282235

  4. 3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images.

    PubMed

    Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

    2016-08-01

    Automatic 3D liver segmentation is a fundamental step in the liver disease diagnosis and surgery planning. This paper presents a novel fully automatic algorithm for 3D liver segmentation in clinical 3D computed tomography (CT) images. Based on image features, we propose a new Mahalanobis distance cost function using an active shape model (ASM). We call our method MD-ASM. Unlike the standard active shape model (ST-ASM), the proposed method introduces a new feature-constrained Mahalanobis distance cost function to measure the distance between the generated shape during the iterative step and the mean shape model. The proposed Mahalanobis distance function is learned from a public database of liver segmentation challenge (MICCAI-SLiver07). As a refinement step, we propose the use of a 3D graph-cut segmentation. Foreground and background labels are automatically selected using texture features of the learned Mahalanobis distance. Quantitatively, the proposed method is evaluated using two clinical 3D CT scan databases (MICCAI-SLiver07 and MIDAS). The evaluation of the MICCAI-SLiver07 database is obtained by the challenge organizers using five different metric scores. The experimental results demonstrate the availability of the proposed method by achieving an accurate liver segmentation compared to the state-of-the-art methods. PMID:26501155

  5. Radiographic Response to Yttrium-90 Radioembolization in Anterior Versus Posterior Liver Segments

    SciTech Connect

    Ibrahim, Saad M.; Lewandowski, Robert J.; Ryu, Robert K.; Sato, Kent T.; Gates, Vanessa L.; Mulcahy, Mary F.; Kulik, Laura; Larson, Andrew C.; Omary, Reed A.; Salem, Riad

    2008-11-15

    The purpose of our study was to determine if preferential radiographic tumor response occurs in tumors located in posterior versus anterior liver segments following radioembolization with yttrium-90 glass microspheres. One hundred thirty-seven patients with chemorefractory liver metastases of various primaries were treated with yttrium-90 glass microspheres. Of these, a subset analysis was performed on 89 patients who underwent 101 whole-right-lobe infusions to liver segments V, VI, VII, and VIII. Pre- and posttreatment imaging included either triphasic contrast material-enhanced CT or gadolinium-enhanced MRI. Responses to treatment were compared in anterior versus posterior right lobe lesions using both RECIST and WHO criteria. Statistical comparative studies were conducted in 42 patients with both anterior and posterior segment lesions using the paired-sample t-test. Pearson correlation was used to determine the relationship between pretreatment tumor size and posttreatment tumor response. Median administered activity, delivered radiation dose, and treatment volume were 2.3 GBq, 118.2 Gy, and 1,072 cm{sup 3}, respectively. Differences between the pretreatment tumor size of anterior and posterior liver segments were not statistically significant (p = 0.7981). Differences in tumor response between anterior and posterior liver segments were not statistically significant using WHO criteria (p = 0.8557). A statistically significant correlation did not exist between pretreatment tumor size and posttreatment tumor response (r = 0.0554, p = 0.4434). On imaging follow-up using WHO criteria, for anterior and posterior regions of the liver, (1) response rates were 50% (PR = 50%) and 45% (CR = 9%, PR = 36%), and (2) mean changes in tumor size were -41% and -40%. In conclusion, this study did not find evidence of preferential radiographic tumor response in posterior versus anterior liver segments treated with yttrium-90 glass microspheres.

  6. 3-D segmentation of retinal blood vessels in spectral-domain OCT volumes of the optic nerve head

    NASA Astrophysics Data System (ADS)

    Lee, Kyungmoo; Abràmoff, Michael D.; Niemeijer, Meindert; Garvin, Mona K.; Sonka, Milan

    2010-03-01

    Segmentation of retinal blood vessels can provide important information for detecting and tracking retinal vascular diseases including diabetic retinopathy, arterial hypertension, arteriosclerosis and retinopathy of prematurity (ROP). Many studies on 2-D segmentation of retinal blood vessels from a variety of medical images have been performed. However, 3-D segmentation of retinal blood vessels from spectral-domain optical coherence tomography (OCT) volumes, which is capable of providing geometrically accurate vessel models, to the best of our knowledge, has not been previously studied. The purpose of this study is to develop and evaluate a method that can automatically detect 3-D retinal blood vessels from spectral-domain OCT scans centered on the optic nerve head (ONH). The proposed method utilized a fast multiscale 3-D graph search to segment retinal surfaces as well as a triangular mesh-based 3-D graph search to detect retinal blood vessels. An experiment on 30 ONH-centered OCT scans (15 right eye scans and 15 left eye scans) from 15 subjects was performed, and the mean unsigned error in 3-D of the computer segmentations compared with the independent standard obtained from a retinal specialist was 3.4 +/- 2.5 voxels (0.10 +/- 0.07 mm).

  7. Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts.

    PubMed

    Wu, Weiwei; Zhou, Zhuhuang; Wu, Shuicai; Zhang, Yanhua

    2016-01-01

    Accurate segmentation of liver from abdominal CT scans is critical for computer-assisted diagnosis and therapy. Despite many years of research, automatic liver segmentation remains a challenging task. In this paper, a novel method was proposed for automatic delineation of liver on CT volume images using supervoxel-based graph cuts. To extract the liver volume of interest (VOI), the region of abdomen was firstly determined based on maximum intensity projection (MIP) and thresholding methods. Then, the patient-specific liver VOI was extracted from the region of abdomen by using a histogram-based adaptive thresholding method and morphological operations. The supervoxels of the liver VOI were generated using the simple linear iterative clustering (SLIC) method. The foreground/background seeds for graph cuts were generated on the largest liver slice, and the graph cuts algorithm was applied to the VOI supervoxels. Thirty abdominal CT images were used to evaluate the accuracy and efficiency of the proposed algorithm. Experimental results show that the proposed method can detect the liver accurately with significant reduction of processing time, especially when dealing with diseased liver cases. PMID:27127536

  8. Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts

    PubMed Central

    Wu, Weiwei; Zhou, Zhuhuang; Wu, Shuicai; Zhang, Yanhua

    2016-01-01

    Accurate segmentation of liver from abdominal CT scans is critical for computer-assisted diagnosis and therapy. Despite many years of research, automatic liver segmentation remains a challenging task. In this paper, a novel method was proposed for automatic delineation of liver on CT volume images using supervoxel-based graph cuts. To extract the liver volume of interest (VOI), the region of abdomen was firstly determined based on maximum intensity projection (MIP) and thresholding methods. Then, the patient-specific liver VOI was extracted from the region of abdomen by using a histogram-based adaptive thresholding method and morphological operations. The supervoxels of the liver VOI were generated using the simple linear iterative clustering (SLIC) method. The foreground/background seeds for graph cuts were generated on the largest liver slice, and the graph cuts algorithm was applied to the VOI supervoxels. Thirty abdominal CT images were used to evaluate the accuracy and efficiency of the proposed algorithm. Experimental results show that the proposed method can detect the liver accurately with significant reduction of processing time, especially when dealing with diseased liver cases. PMID:27127536

  9. Automatic seed selection for segmentation of liver cirrhosis in laparoscopic sequences

    NASA Astrophysics Data System (ADS)

    Sinha, Rahul; Marcinczak, Jan Marek; Grigat, Rolf-Rainer

    2014-03-01

    For computer aided diagnosis based on laparoscopic sequences, image segmentation is one of the basic steps which define the success of all further processing. However, many image segmentation algorithms require prior knowledge which is given by interaction with the clinician. We propose an automatic seed selection algorithm for segmentation of liver cirrhosis in laparoscopic sequences which assigns each pixel a probability of being cirrhotic liver tissue or background tissue. Our approach is based on a trained classifier using SIFT and RGB features with PCA. Due to the unique illumination conditions in laparoscopic sequences of the liver, a very low dimensional feature space can be used for classification via logistic regression. The methodology is evaluated on 718 cirrhotic liver and background patches that are taken from laparoscopic sequences of 7 patients. Using a linear classifier we achieve a precision of 91% in a leave-one-patient-out cross-validation. Furthermore, we demonstrate that with logistic probability estimates, seeds with high certainty of being cirrhotic liver tissue can be obtained. For example, our precision of liver seeds increases to 98.5% if only seeds with more than 95% probability of being liver are used. Finally, these automatically selected seeds can be used as priors in Graph Cuts which is demonstrated in this paper.

  10. SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization

    SciTech Connect

    Li, Dengwang; Wang, Jie; Kapp, Daniel S.; Xing, Lei

    2015-06-15

    Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is

  11. Automatic plaque characterization and vessel wall segmentation in magnetic resonance images of atherosclerotic carotid arteries

    NASA Astrophysics Data System (ADS)

    Adame, Isabel M.; van der Geest, Rob J.; Wasserman, Bruce A.; Mohamed, Mona; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.

    2004-05-01

    Composition and structure of atherosclerotic plaque is a primary focus of cardiovascular research. In vivo MRI provides a meanse to non-invasively image and assess the morphological features of athersclerotic and normal human carotid arteries. To quantitatively assess the vulnerability and the type of plaque, the contours of the lumen, outer boundary of the vessel wall and plaque components, need to be traced. To achieve this goal, we have developed an automated contou detection technique, which consists of three consecutive steps: firstly, the outer boundary of the vessel wall is detected by means of an ellipse-fitting procedure in order to obtain smoothed shapes; secondly, the lumen is segnented using fuzzy clustering. Thre region to be classified is that within the outer vessel wall boundary obtained from the previous step; finally, for plaque detection we follow the same approach as for lumen segmentation: fuzzy clustering. However, plaque is more difficult to segment, as the pixel gray value can differ considerably from one region to another, even when it corresponds to the same type of tissue. That makes further processing necessary. All these three steps might be carried out combining information from different sequences (PD-, T2-, T1-weighted images, pre- and post-contrast), to improve the contour detection. The algorithm has been validated in vivo on 58 high-resolution PD and T1 weighted MR images (19 patients). The results demonstrate excellent correspondence between automatic and manual area measurements: lumen (r=0.94), outer (r=0.92), and acceptable for fibrous cap thickness (r=0.76).

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

    SciTech Connect

    Yuan, Yading Chao, Ming; Sheu, Ren-Dih; Rosenzweig, Kenneth; Lo, Yeh-Chi

    2015-07-15

    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. 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

  13. 3D liver segmentation using multiple region appearances and graph cuts

    SciTech Connect

    Peng, Jialin Zhang, Hongbo; Hu, Peijun; Lu, Fang; Kong, Dexing; Peng, Zhiyi

    2015-12-15

    Purpose: Efficient and accurate 3D liver segmentations from contrast-enhanced computed tomography (CT) images play an important role in therapeutic strategies for hepatic diseases. However, inhomogeneous appearances, ambiguous boundaries, and large variance in shape often make it a challenging task. The existence of liver abnormalities poses further difficulty. Despite the significant intensity difference, liver tumors should be segmented as part of the liver. This study aims to address these challenges, especially when the target livers contain subregions with distinct appearances. Methods: The authors propose a novel multiregion-appearance based approach with graph cuts to delineate the liver surface. For livers with multiple subregions, a geodesic distance based appearance selection scheme is introduced to utilize proper appearance constraint for each subregion. A special case of the proposed method, which uses only one appearance constraint to segment the liver, is also presented. The segmentation process is modeled with energy functions incorporating both boundary and region information. Rather than a simple fixed combination, an adaptive balancing weight is introduced and learned from training sets. The proposed method only calls initialization inside the liver surface. No additional constraints from user interaction are utilized. Results: The proposed method was validated on 50 3D CT images from three datasets, i.e., Medical Image Computing and Computer Assisted Intervention (MICCAI) training and testing set, and local dataset. On MICCAI testing set, the proposed method achieved a total score of 83.4 ± 3.1, outperforming nonexpert manual segmentation (average score of 75.0). When applying their method to MICCAI training set and local dataset, it yielded a mean Dice similarity coefficient (DSC) of 97.7% ± 0.5% and 97.5% ± 0.4%, respectively. These results demonstrated the accuracy of the method when applied to different computed tomography (CT) datasets

  14. A multi-scale tensor voting approach for small retinal vessel segmentation in high resolution fundus images.

    PubMed

    Christodoulidis, Argyrios; Hurtut, Thomas; Tahar, Houssem Ben; Cheriet, Farida

    2016-09-01

    Segmenting the retinal vessels from fundus images is a prerequisite for many CAD systems for the automatic detection of diabetic retinopathy lesions. So far, research efforts have concentrated mainly on the accurate localization of the large to medium diameter vessels. However, failure to detect the smallest vessels at the segmentation step can lead to false positive lesion detection counts in a subsequent lesion analysis stage. In this study, a new hybrid method for the segmentation of the smallest vessels is proposed. Line detection and perceptual organization techniques are combined in a multi-scale scheme. Small vessels are reconstructed from the perceptual-based approach via tracking and pixel painting. The segmentation was validated in a high resolution fundus image database including healthy and diabetic subjects using pixel-based as well as perceptual-based measures. The proposed method achieves 85.06% sensitivity rate, while the original multi-scale line detection method achieves 81.06% sensitivity rate for the corresponding images (p<0.05). The improvement in the sensitivity rate for the database is 6.47% when only the smallest vessels are considered (p<0.05). For the perceptual-based measure, the proposed method improves the detection of the vasculature by 7.8% against the original multi-scale line detection method (p<0.05). PMID:27341026

  15. [Laparoscopic resection of a liver metastasis from segment VII. Case report].

    PubMed

    Dede, Kristóf; Papp, Géza; Salamon, Ferenc; Uhlyarik, Andrea; Bursics, Attila

    2016-05-15

    The technique and clinical results of liver surgery are constantly evolving in recent years, and this development felt most intensely in the field of laparoscopic liver surgery. Based on the results of comparative studies reported to date, laparoscopic surgery is not inferior to open surgery. Although a very small percentage of liver resections are performed with laparoscopic technique, clearly it has a role in oncological surgery. The minor, major, anatomical, or even multi-stage liver resections can be performed with laparoscopy. The previously general recommendation, that lesions in the front segments of the liver are recommended for the minimally invasive technique is currently outdated. The authors present the history of a 70-year-old female, who underwent complex oncosurgical treatment of a locally advanced rectum carcinoma and a pure laparoscopic resection of a solitary hepatic metastasis of segment VII. With this case report the authors want to underline that malignant lesions in the posterior segments of the liver can be removed safely with laparoscopy. PMID:27156527

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. Random feature subspace ensemble based Extreme Learning Machine for liver tumor detection and segmentation.

    PubMed

    Huang, Weimin; Yang, Yongzhong; Lin, Zhiping; Huang, Guang-Bin; Zhou, Jiayin; Duan, Yuping; Xiong, Wei

    2014-01-01

    This paper presents a new approach to detect and segment liver tumors. The detection and segmentation of liver tumors can be formulized as novelty detection or two-class classification problem. Each voxel is characterized by a rich feature vector, and a classifier using random feature subspace ensemble is trained to classify the voxels. Since Extreme Learning Machine (ELM) has advantages of very fast learning speed and good generalization ability, it is chosen to be the base classifier in the ensemble. Besides, majority voting is incorporated for fusion of classification results from the ensemble of base classifiers. In order to further increase testing accuracy, ELM autoencoder is implemented as a pre-training step. In automatic liver tumor detection, ELM is trained as a one-class classifier with only healthy liver samples, and the performance is compared with two-class ELM. In liver tumor segmentation, a semi-automatic approach is adopted by selecting samples in 3D space to train the classifier. The proposed method is tested and evaluated on a group of patients' CT data and experiment show promising results. PMID:25571035

  18. Low level arsenic promotes progressive inflammatory angiogenesis and liver blood vessel remodeling in mice

    SciTech Connect

    Straub, Adam C.; Stolz, Donna B.; Vin, Harina; Ross, Mark A.; Soucy, Nicole V.; Klei, Linda R.; Barchowsky, Aaron

    2007-08-01

    The vascular effects of arsenic in drinking water are global health concerns contributing to human disease worldwide. Arsenic targets the endothelial cells lining blood vessels, and endothelial cell activation or dysfunction may underlie the pathogenesis of both arsenic-induced vascular diseases and arsenic-enhanced tumorigenesis. The purpose of the current studies was to demonstrate that exposing mice to drinking water containing environmentally relevant levels of arsenic promoted endothelial cell dysfunction and pathologic vascular remodeling. Increased angiogenesis, neovascularization, and inflammatory cell infiltration were observed in Matrigel plugs implanted in C57BL/6 mice following 5-week exposures to 5-500 ppb arsenic [Soucy, N.V., Mayka, D., Klei, L.R., Nemec, A.A., Bauer, J.A., Barchowsky, A., 2005. Neovascularization and angiogenic gene expression following chronic arsenic exposure in mice. Cardiovasc.Toxicol 5, 29-42]. Therefore, functional in vivo effects of arsenic on endothelial cell function and vessel remodeling in an endogenous vascular bed were investigated in the liver. Liver sinusoidal endothelial cells (LSEC) became progressively defenestrated and underwent capillarization to decrease vessel porosity following exposure to 250 ppb arsenic for 2 weeks. Sinusoidal expression of PECAM-1 and laminin-1 proteins, a hallmark of capillarization, was also increased by 2 weeks of exposure. LSEC caveolin-1 protein and caveolae expression were induced after 2 weeks of exposure indicating a compensatory change. Likewise, CD45/CD68-positive inflammatory cells did not accumulate in the livers until after LSEC porosity was decreased, indicating that inflammation is a consequence and not a cause of the arsenic-induced LSEC phenotype. The data demonstrate that the liver vasculature is an early target of pathogenic arsenic effects and that the mouse liver vasculature is a sensitive model for investigating vascular health effects of arsenic.

  19. A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding.

    PubMed

    BahadarKhan, Khan; A Khaliq, Amir; Shahid, Muhammad

    2016-01-01

    Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts. PMID:27441646

  20. A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region Based Otsu Thresholding

    PubMed Central

    BahadarKhan, Khan; A Khaliq, Amir; Shahid, Muhammad

    2016-01-01

    Diabetic Retinopathy (DR) harm retinal blood vessels in the eye causing visual deficiency. The appearance and structure of blood vessels in retinal images play an essential part in the diagnoses of an eye sicknesses. We proposed a less computational unsupervised automated technique with promising results for detection of retinal vasculature by using morphological hessian based approach and region based Otsu thresholding. Contrast Limited Adaptive Histogram Equalization (CLAHE) and morphological filters have been used for enhancement and to remove low frequency noise or geometrical objects, respectively. The hessian matrix and eigenvalues approach used has been in a modified form at two different scales to extract wide and thin vessel enhanced images separately. Otsu thresholding has been further applied in a novel way to classify vessel and non-vessel pixels from both enhanced images. Finally, postprocessing steps has been used to eliminate the unwanted region/segment, non-vessel pixels, disease abnormalities and noise, to obtain a final segmented image. The proposed technique has been analyzed on the openly accessible DRIVE (Digital Retinal Images for Vessel Extraction) and STARE (STructured Analysis of the REtina) databases along with the ground truth data that has been precisely marked by the experts. PMID:27441646

  1. Intracellular pH regulation in resting and contracting segments of rat mesenteric resistance vessels.

    PubMed Central

    Aalkjaer, C; Cragoe, E J

    1988-01-01

    1. The pH-sensitive dye 2',7'-bis-(2-carboxyethyl)-5 (and -6)-carboxyfluorescein (BCECF) was used to measure intracellular pH (pHi) in segments of rat resistance vessels (internal diameter about 200 microns) with the vessels mounted in a myograph for simultaneous measurements of isometric contraction. 2. BCECF loaded slowly into the vessels over 1 h and did not affect the maximal contractility of the vessels. There was a loss of dye with time which, however, was very slow when the segments were only excited for 2 s/min, suggesting that the loss was mainly due to dye bleaching with only a very slow leak. 3. The ratio of the emissions (at 540 nm) with excitation at 495 and 450 nm was calibrated in terms of pH using the K+-H+ ionophore nigericin. This calibration gave a pHi value of 7.15 +/- 0.02 (n = 20), suggesting that hydrogen ions are not in electrochemical equilibrium in these vascular smooth muscles which have a membrane potential of about -60 mV. 4. Addition of 10 mM-NH4Cl caused a transient alkalinization and wash-out of 10 mM-NH4Cl a transient acidification. Increasing CO2 with maintained bicarbonate caused a rapid acidification followed by an incomplete recovery. Removal of CO2 and bicarbonate (HEPES-buffered solution) with constant extracellular pH caused a transient alkalinization but steady-state pHi was not significantly altered. 5. In bicarbonate-free buffer the Na+-H+ exchange blocker 5-(N-ethyl-N-isopropyl) amiloride (EIPA) and sodium-free conditions caused a slow acidification. In bicarbonate buffer (PSS) EIPA had no detectable effect after 10 min but the anion exchange blocker diisothio-cyanatostilbenedisulphonic acid (DIDS) caused a small acidification over that time course. 6. The rate of recovery after an acid load was about 50% lower in HEPES buffer compared to PSS and it was inhibited by EIPA. In PSS amiloride and EIPA each had a small inhibitory effect on the pH recovery after an acid load. DIDS also inhibited the recovery from an acid load

  2. Automatic segmentation of hepatocellular structure from HE-stained liver tissue

    NASA Astrophysics Data System (ADS)

    Ishikawa, Masahiro; Ahi, Sercan Taha; Murakami, Yuri; Kimura, Fumikazu; Yamaguchi, Masahiro; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie

    2013-03-01

    The analysis of hepatic tissue structure is required for quantitative assessment of liver histology. Especially, a cord-like structure of liver cells, called trabecura, has important information in the diagnosis of hepatocellular carcinoma (HCC). However, the extraction of trabeculae is thought to be difficult because liver cells take on various colors and appearances depending on tissue conditions. In this paper, we propose an approach to extract trabeculae from images of hematoxyline and eosin stained liver tissue slide by extracting the rest of trabeculae: sinusoids and stromal area. The sinusoids are simply extracted based on the color information, where the image is corrected by an orientation selective filtering before segmentaion. The stromal area mainly consists of fiber, and often includes lymphocytes densely. Therefore, in the proposed method, fiber region and lymphocytes are extracted separately, then, stromal region is determined based on the extracted results. The determination of stroma is performed based on superpixels, to obtain precise boundaries. Once the regions of sinusoids and stroma are obtained, trabeculae can be segmented as the remaining region. The proposed method was applied to 10 test images of normal and HCC liver tissues, and the results were evaluated based on the manual segmentation. As a result, we confirmed that both sensitivity and specificity of the extraction of trabeculae reach around 90%.

  3. Anatomical liver resection of segment 4a en bloc with the caudate lobe.

    PubMed

    Silvestrini, Nicola; Coppola, Alessandro; Ardito, Francesco; Nuzzo, Gennaro; Giuliante, Felice

    2016-05-01

    Anatomical segmentectomy is the complete resection of an area supplied by a segmental portal branch. Among segmentectomies, isolated segmentectomy 4 is a technically demanding procedure because there are two transection planes: on the left side along the umbilical fissure and, on the right side, along the middle hepatic vein. Although there are several reports on anatomic segmentectomies, only few regard the anatomic segmentectomy 4a. We report here the case of a 60-year-old man who underwent anatomical segmentectomy 4a en bloc with the caudate lobe to resect a colorectal liver metastasis located in segment 4a and involving the paracaval portion of the caudate lobe. This type of procedure was planned in order to maximize the postoperative functional hepatic reserve, thereby reducing the risk of postoperative liver failure and ultimately allowing the possibility for future repeat hepatectomy in case of recurrence. J. Surg. Oncol. 2016;113:665-667. © 2016 Wiley Periodicals, Inc. PMID:26891129

  4. Automatic detection and segmentation of liver metastatic lesions on serial CT examinations

    NASA Astrophysics Data System (ADS)

    Ben Cohen, Avi; Diamant, Idit; Klang, Eyal; Amitai, Michal; Greenspan, Hayit

    2014-03-01

    In this paper we present a fully automated method for detection and segmentation of liver metastases on serial CT examinations (portal phase) given a 2D baseline segmentation mask. Our database contains 27 CT scans, baselines and follow-ups, of 12 patients and includes 22 test cases. Our method is based on the information given in the baseline CT scan which contains the lesion's segmentation mask marked manually by a radiologist. We use the 2D baseline segmentation mask to identify the lesion location in the follow-up CT scan using non-rigid image registration. The baseline CT scan is also used to locate regions of tissues surrounding the lesion and to map them onto the follow-up CT scan, in order to reduce the search area on the follow-up CT scan. Adaptive region-growing and mean-shift segmentation are used to obtain the final lesion segmentation. The segmentation results are compared to those obtained by a human radiologist. Compared to the reference standard our method made a correct RECIST 1.1 assessment for 21 out of 22 test cases. The average Dice index was 0.83 +/- 0.07, average Hausdorff distance was 7.85+/- 4.84 mm, average sensitivity was 0.87 +/- 0.11 and positive predictive value was 0.81 +/- 0.10. The segmentation performance and the RECIST assessment results look promising. We are pursuing the methodology further with expansion to 3D segmentation while increasing the dataset we are collecting from the CT abdomen unit at Sheba medical center.

  5. Segmental Bile Duct-Targeted Liver Resection for Right-Sided Intrahepatic Stones

    PubMed Central

    Li, Shao-Qiang; Hua, Yun-Peng; Shen, Shun-Li; Hu, Wen-Jie; Peng, Bao-Gang; Liang, Li-Jian

    2015-01-01

    Abstract Hepatectomy is a safe and effective treatment for intrahepatic stones (IHSs). However, the resection plane for right-sided stones distributed within 2 segments is obstacle because of atrophy-hypertrophy complex formation of the liver and difficult dissection of segmental pedicle within the Glissonean plate by conventional approach. Thus, we devised segmental bile duct-targeted liver resection (SBDLR) for IHS, which aimed at completely resection of diseased bile ducts. This study aimed to evaluate the outcomes of SBDLR for right-sided IHSs. From January 2009 to December 2013, 107 patients with IHS treated by SBDLR in our center were reviewed in a prospective database. Patients’ intermediate and long-term outcomes after SBDLR were analyzed. A total of 40 (37.4%) patients with localized right-sided stone and 67 (62.7%) patients with bilateral stones underwent SBDLR alone and SBDLR combined with left-sided hepatectomy, respectively. There was no hospital mortality of this cohort of patients. The postoperative morbidity was 35.5%. The mean intraoperative blood loss was 414 mL (range: 100–2500). Twenty-one (19.6%) patients needed red blood cells transfusion. The intermediate stone clearance rate was 94.4%; the final clearance rate reached 100% after subsequent postoperative cholangioscopic lithotomy. Only 2.8% patients developed stone recurrence in a median follow-up period of 38.3 months. SBDLR is a safe and effective treatment for right-sided IHS distributed within 2 segments. It is especially suitable for a subgroup of patients with bilateral stones whose right-sided stones are within 2 segments and bilateral liver resection is needed. PMID:26181559

  6. Segmental Bile Duct-Targeted Liver Resection for Right-Sided Intrahepatic Stones.

    PubMed

    Li, Shao-Qiang; Hua, Yun-Peng; Shen, Shun-Li; Hu, Wen-Jie; Peng, Bao-Gang; Liang, Li-Jian

    2015-07-01

    Hepatectomy is a safe and effective treatment for intrahepatic stones (IHSs). However, the resection plane for right-sided stones distributed within 2 segments is obstacle because of atrophy-hypertrophy complex formation of the liver and difficult dissection of segmental pedicle within the Glissonean plate by conventional approach. Thus, we devised segmental bile duct-targeted liver resection (SBDLR) for IHS, which aimed at completely resection of diseased bile ducts. This study aimed to evaluate the outcomes of SBDLR for right-sided IHSs. From January 2009 to December 2013, 107 patients with IHS treated by SBDLR in our center were reviewed in a prospective database. Patients' intermediate and long-term outcomes after SBDLR were analyzed. A total of 40 (37.4%) patients with localized right-sided stone and 67 (62.7%) patients with bilateral stones underwent SBDLR alone and SBDLR combined with left-sided hepatectomy, respectively. There was no hospital mortality of this cohort of patients. The postoperative morbidity was 35.5%. The mean intraoperative blood loss was 414  mL (range: 100-2500). Twenty-one (19.6%) patients needed red blood cells transfusion. The intermediate stone clearance rate was 94.4%; the final clearance rate reached 100% after subsequent postoperative cholangioscopic lithotomy. Only 2.8% patients developed stone recurrence in a median follow-up period of 38.3 months. SBDLR is a safe and effective treatment for right-sided IHS distributed within 2 segments. It is especially suitable for a subgroup of patients with bilateral stones whose right-sided stones are within 2 segments and bilateral liver resection is needed. PMID:26181559

  7. Comparison and evaluation of methods for liver segmentation from CT datasets.

    PubMed

    Heimann, Tobias; van Ginneken, Bram; Styner, Martin A; Arzhaeva, Yulia; Aurich, Volker; Bauer, Christian; Beck, Andreas; Becker, Christoph; Beichel, Reinhard; Bekes, György; Bello, Fernando; Binnig, Gerd; Bischof, Horst; Bornik, Alexander; Cashman, Peter M M; Chi, Ying; Cordova, Andrés; Dawant, Benoit M; Fidrich, Márta; Furst, Jacob D; Furukawa, Daisuke; Grenacher, Lars; Hornegger, Joachim; Kainmüller, Dagmar; Kitney, Richard I; Kobatake, Hidefumi; Lamecker, Hans; Lange, Thomas; Lee, Jeongjin; Lennon, Brian; Li, Rui; Li, Senhu; Meinzer, Hans-Peter; Nemeth, Gábor; Raicu, Daniela S; Rau, Anne-Mareike; van Rikxoort, Eva M; Rousson, Mikaël; Rusko, László; Saddi, Kinda A; Schmidt, Günter; Seghers, Dieter; Shimizu, Akinobu; Slagmolen, Pieter; Sorantin, Erich; Soza, Grzegorz; Susomboon, Ruchaneewan; Waite, Jonathan M; Wimmer, Andreas; Wolf, Ivo

    2009-08-01

    This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided to train and tune algorithms in advance. Participants were also allowed to use additional proprietary training data for that purpose. All teams then had to apply their methods to 10 test datasets and submit the obtained results. Employed algorithms include statistical shape models, atlas registration, level-sets, graph-cuts and rule-based systems. All results were compared to reference segmentations five error measures that highlight different aspects of segmentation accuracy. All measures were combined according to a specific scoring system relating the obtained values to human expert variability. In general, interactive methods reached higher average scores than automatic approaches and featured a better consistency of segmentation quality. However, the best automatic methods (mainly based on statistical shape models with some additional free deformation) could compete well on the majority of test images. The study provides an insight in performance of different segmentation approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques. PMID:19211338

  8. Improved registration of DCE-MR images of the liver using a prior segmentation of the region of interest

    NASA Astrophysics Data System (ADS)

    Zhang, Tian; Li, Zhang; Runge, Jurgen H.; Lavini, Cristina; Stoker, Jaap; van Gulik, Thomas; van Vliet, Lucas J.; Vos, Frans M.

    2016-03-01

    In Dynamic Contrast-Enhanced MRI (DCE-MRI) of the liver, a series of images is acquired over a period of 20 minutes. Due to the patient's breathing, the liver is subject to a substantial displacement between acquisitions. Furthermore, due to its location in the abdomen, the liver also undergoes marked deformation. The large deformations combined with variation in image contrast make accurate liver registration challenging. We present a registration framework that incorporates a liver segmentation to improve the registration accuracy. The segmented liver serves as region-of-interest to our in-house developed registration method called ALOST (autocorrelation of local image structure). ALOST is a continuous optimization method that uses local phase features to overcome space-variant intensity distortions. The proposed framework can confine the solution field to the liver and allow for ALOST to obtain a more accurate solution. For the segmentation part, we use a level-set method to delineate the liver in a so-called contrast enhancement map. This map is obtained by computing the difference between the last and registered first volume from the DCE series. Subsequently, we slightly dilate the segmentation, and apply it as the mask to the other DCE-MRI volumes during registration. It is shown that the registration result becomes more accurate compared with the original ALOST approach.

  9. A Heuristic Framework for Image Filtering and Segmentation: Application to Blood Vessel Immunohistochemistry.

    PubMed

    Tsou, Chi-Hsuan; Lu, Yi-Chien; Yuan, Ang; Chang, Yeun-Chung; Chen, Chung-Ming

    2015-01-01

    The blood vessel density in a cancerous tissue sample may represent increased levels of tumor growth. However, identifying blood vessels in the histological (tissue) image is difficult and time-consuming and depends heavily on the observer's experience. To overcome this drawback, computer-aided image analysis frameworks have been investigated in order to boost object identification in histological images. We present a novel algorithm to automatically abstract the salient regions in blood vessel images. Experimental results show that the proposed framework is capable of deriving vessel boundaries that are comparable to those demarcated manually, even for vessel regions with weak contrast between the object boundaries and background clutter. PMID:26819914

  10. A Heuristic Framework for Image Filtering and Segmentation: Application to Blood Vessel Immunohistochemistry

    PubMed Central

    Tsou, Chi-Hsuan; Lu, Yi-Chien; Yuan, Ang; Chang, Yeun-Chung; Chen, Chung-Ming

    2015-01-01

    The blood vessel density in a cancerous tissue sample may represent increased levels of tumor growth. However, identifying blood vessels in the histological (tissue) image is difficult and time-consuming and depends heavily on the observer's experience. To overcome this drawback, computer-aided image analysis frameworks have been investigated in order to boost object identification in histological images. We present a novel algorithm to automatically abstract the salient regions in blood vessel images. Experimental results show that the proposed framework is capable of deriving vessel boundaries that are comparable to those demarcated manually, even for vessel regions with weak contrast between the object boundaries and background clutter. PMID:26819914

  11. Evaluation of an improved technique for lumen path definition and lumen segmentation of atherosclerotic vessels in CT angiography.

    PubMed

    van Velsen, Evert F S; Niessen, Wiro J; de Weert, Thomas T; de Monyé, Cécile; van der Lugt, Aad; Meijering, Erik; Stokking, Rik

    2007-07-01

    Vessel image analysis is crucial when considering therapeutical options for (cardio-) vascular diseases. Our method, VAMPIRE (Vascular Analysis using Multiscale Paths Inferred from Ridges and Edges), involves two parts: a user defines a start- and endpoint upon which a lumen path is automatically defined, and which is used for initialization; the automatic segmentation of the vessel lumen on computed tomographic angiography (CTA) images. Both parts are based on the detection of vessel-like structures by analyzing intensity, edge, and ridge information. A multi-observer evaluation study was performed to compare VAMPIRE with a conventional method on the CTA data of 15 patients with carotid artery stenosis. In addition to the start- and endpoint, the two radiologists required on average 2.5 (SD: 1.9) additional points to define a lumen path when using the conventional method, and 0.1 (SD: 0.3) when using VAMPIRE. The segmentation results were quantitatively evaluated using Similarity Indices, which were slightly lower between VAMPIRE and the two radiologists (respectively 0.90 and 0.88) compared with the Similarity Index between the radiologists (0.92). The evaluation shows that the improved definition of a lumen path requires minimal user interaction, and that using this path as initialization leads to good automatic lumen segmentation results. PMID:17077978

  12. Adaptive Mesh Expansion Model (AMEM) for Liver Segmentation from CT Image

    PubMed Central

    Wang, Xuehu; Yang, Jian; Ai, Danni; Zheng, Yongchang; Tang, Songyuan; Wang, Yongtian

    2015-01-01

    This study proposes a novel adaptive mesh expansion model (AMEM) for liver segmentation from computed tomography images. The virtual deformable simplex model (DSM) is introduced to represent the mesh, in which the motion of each vertex can be easily manipulated. The balloon, edge, and gradient forces are combined with the binary image to construct the external force of the deformable model, which can rapidly drive the DSM to approach the target liver boundaries. Moreover, tangential and normal forces are combined with the gradient image to control the internal force, such that the DSM degree of smoothness can be precisely controlled. The triangular facet of the DSM is adaptively decomposed into smaller triangular components, which can significantly improve the segmentation accuracy of the irregularly sharp corners of the liver. The proposed method is evaluated on the basis of different criteria applied to 10 clinical data sets. Experiments demonstrate that the proposed AMEM algorithm is effective and robust and thus outperforms six other up-to-date algorithms. Moreover, AMEM can achieve a mean overlap error of 6.8% and a mean volume difference of 2.7%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 1.3 mm and 2.7 mm, respectively. PMID:25769030

  13. A self-calibrating approach for the segmentation of retinal vessels by template matching and contour reconstruction.

    PubMed

    Kovács, György; Hajdu, András

    2016-04-01

    The automated processing of retinal images is a widely researched area in medical image analysis. Screening systems based on the automated and accurate recognition of retinopathies enable the earlier diagnosis of diseases like diabetic retinopathy, hypertension and their complications. The segmentation of the vascular system is a crucial task in the field: on the one hand, the accurate extraction of the vessel pixels aids the detection of other anatomical parts (like the optic disc Hoover and Goldbaum, 2003) and lesions (like microaneurysms Sopharak et al., 2013); on the other hand, the geometrical features of the vascular system and their temporal changes are shown to be related to diseases, like the vessel tortuosity to Fabry disease Sodi et al., 2013 and the arteriolar-to-venus (A/V) ratio to hypertension (Pakter et al., 2005). In this study, a novel technique based on template matching and contour reconstruction is proposed for the segmentation of the vasculature. In the template matching step generalized Gabor function based templates are used to extract the center lines of vessels. Then, the intensity characteristics of vessel contours measured in training databases are reconstructed. The method was trained and tested on two publicly available databases, DRIVE and STARE; and reached an average accuracy of 0.9494 and 0.9610, respectively. We have also carried out cross-database tests and found that the accuracy scores are higher than that of any previous technique trained and tested on the same database. PMID:26766207

  14. Three-Dimensional Quantitative Evaluation of the Segmental Functional Reserve in the Cirrhotic Liver Using Multi-Modality Imaging

    PubMed Central

    Xiang, Canhong; Chen, Yingmao; Shao, Mingzhe; Li, Can; Huang, Xin; Gong, Lei; Li, Ang; Duan, Weidong; Zhang, Aiqun; Dong, Jiahong

    2016-01-01

    Abstract To quantitatively evaluate the regional functional reserve in the cirrhotic liver and to seek related index that reflects diminished segmental liver function. A 3D system for quantitative evaluation of the liver was used to fuse technetium-99m galactosyl human serum albumin single-photon emission computed tomography and computed tomography images from 20 patients with cirrhotic liver and hepatocellular carcinoma. A set of parameters reflecting liver function including morphological liver volume, functional liver volume, functional liver density (FLD), and the drug absorption rate constant for hepatic cells (GSA-K) was calculated. Differences in FLD and GSA-K in intrahepatic segments were compared in patients with a tumor embolus (Group Y) and those without such an embolus (Group N) in the right portal vein. Differences in FLD and GSA-K in tumor-bearing (T+ group) and tumor-free (T− group) segments in patients with no tumor embolus (Group N) were also compared. Eleven living donor liver transplantation donor served as the control group. The FLD of the liver as a whole was significantly lower in patients with cirrhosis than in the control group (0.53 ± 0.13 vs 0.68 ± 0.10, P = 0.010). The FLD in segments of the right hemiliver was significantly lower than that in segments of the left hemiliver in Group Y (0.31 ± 0.21 vs 0.58 ± 0.12, P = 0.002) but not in Group N (0.60 ± 0.19 vs 0.55 ± 0.13, P = 0.294). FLD was 0.45 ± 0.17 in the T+ group and 0.60 ± 0.08 in the T− group (P = 0.008). Differences in GSA-K in intrahepatic segments were not significant. In the control group, differences in FLD and GSA-K in intrahepatic segments were not significant. The segmental liver functional reserve can be quantitatively calculated. FLD, but not GSA-K, is an index that reflects diminished regional liver function caused by portal flow obstruction or tumor compression. PMID:26945357

  15. Three-Dimensional Quantitative Evaluation of the Segmental Functional Reserve in the Cirrhotic Liver Using Multi-Modality Imaging.

    PubMed

    Xiang, Canhong; Chen, Yingmao; Shao, Mingzhe; Li, Can; Huang, Xin; Gong, Lei; Li, Ang; Duan, Weidong; Zhang, Aiqun; Dong, Jiahong

    2016-03-01

    To quantitatively evaluate the regional functional reserve in the cirrhotic liver and to seek related index that reflects diminished segmental liver function. A 3D system for quantitative evaluation of the liver was used to fuse technetium-99m galactosyl human serum albumin single-photon emission computed tomography and computed tomography images from 20 patients with cirrhotic liver and hepatocellular carcinoma. A set of parameters reflecting liver function including morphological liver volume, functional liver volume, functional liver density (FLD), and the drug absorption rate constant for hepatic cells (GSA-K) was calculated. Differences in FLD and GSA-K in intrahepatic segments were compared in patients with a tumor embolus (Group Y) and those without such an embolus (Group N) in the right portal vein. Differences in FLD and GSA-K in tumor-bearing (T+ group) and tumor-free (T- group) segments in patients with no tumor embolus (Group N) were also compared. Eleven living donor liver transplantation donor served as the control group. The FLD of the liver as a whole was significantly lower in patients with cirrhosis than in the control group (0.53 ± 0.13 vs 0.68 ± 0.10, P = 0.010). The FLD in segments of the right hemiliver was significantly lower than that in segments of the left hemiliver in Group Y (0.31 ± 0.21 vs 0.58 ± 0.12, P = 0.002) but not in Group N (0.60 ± 0.19 vs 0.55 ± 0.13, P = 0.294). FLD was 0.45 ± 0.17 in the T+ group and 0.60 ± 0.08 in the T- group (P = 0.008). Differences in GSA-K in intrahepatic segments were not significant. In the control group, differences in FLD and GSA-K in intrahepatic segments were not significant. The segmental liver functional reserve can be quantitatively calculated. FLD, but not GSA-K, is an index that reflects diminished regional liver function caused by portal flow obstruction or tumor compression. PMID:26945357

  16. Evolution of anterior segment reconstruction after live donor adult liver transplantation: a single-center experience.

    PubMed

    Pomposelli, James J; Akoad, Mohamed; Khwaja, Khalid; Lewis, W D; Cheah, Yee L; Verbesey, Jennifer; Jenkins, Roger L; Pomfret, Elizabeth A

    2012-01-01

    Controversy exists regarding the best method for venous outflow reconstruction after live donor liver transplantation using right lobe grafts. Some authors advocate routine inclusion of the middle hepatic vein with the graft, whereas others favor a more selective approach. In this report, we examine the evolution of our decision making and technique of selective anterior venous segment reconstruction during live donor adult liver transplantation performed in 226 recipients. We have developed a simplified back-bench procedure using sequential-composite anastomosis using various vascular conduits with syndactylization to the right hepatic vein creating a single large-outflow anastomosis in the recipient. Conduits used include iliac artery or vein allograft, recanalized umbilical vein, cryopreserved iliac artery allograft, and 6-mm synthetic expanded polytetrafluoroethylene vascular graft. This technique can be performed quickly, safely, and under cold storage conditions and results in excellent outcome while minimizing donor risk. PMID:21980936

  17. Pulmonary vessel segmentation utilizing curved planar reformation and optimal path finding (CROP) in computed tomographic pulmonary angiography (CTPA) for CAD applications

    NASA Astrophysics Data System (ADS)

    Zhou, Chuan; Chan, Heang-Ping; Kuriakose, Jean W.; Chughtai, Aamer; Wei, Jun; Hadjiiski, Lubomir M.; Guo, Yanhui; Patel, Smita; Kazerooni, Ella A.

    2012-03-01

    Vessel segmentation is a fundamental step in an automated pulmonary embolism (PE) detection system. The purpose of this study is to improve the segmentation scheme for pulmonary vessels affected by PE and other lung diseases. We have developed a multiscale hierarchical vessel enhancement and segmentation (MHES) method for pulmonary vessel tree extraction based on the analysis of eigenvalues of Hessian matrices. However, it is difficult to segment the pulmonary vessels accurately under suboptimal conditions, such as vessels occluded by PEs, surrounded by lymphoid tissues or lung diseases, and crossing with other vessels. In this study, we developed a new vessel refinement method utilizing curved planar reformation (CPR) technique combined with optimal path finding method (MHES-CROP). The MHES segmented vessels straightened in the CPR volume was refined using adaptive gray level thresholding where the local threshold was obtained from least-square estimation of a spline curve fitted to the gray levels of the vessel along the straightened volume. An optimal path finding method based on Dijkstra's algorithm was finally used to trace the correct path for the vessel of interest. Two and eight CTPA scans were randomly selected as training and test data sets, respectively. Forty volumes of interest (VOIs) containing "representative" vessels were manually segmented by a radiologist experienced in CTPA interpretation and used as reference standard. The results show that, for the 32 test VOIs, the average percentage volume error relative to the reference standard was improved from 32.9+/-10.2% using the MHES method to 9.9+/-7.9% using the MHES-CROP method. The accuracy of vessel segmentation was improved significantly (p<0.05). The intraclass correlation coefficient (ICC) of the segmented vessel volume between the automated segmentation and the reference standard was improved from 0.919 to 0.988. Quantitative comparison of the MHES method and the MHES-CROP method with the

  18. Volume change of segments II and III of the liver after gastrectomy in patients with gastric cancer

    PubMed Central

    Ozutemiz, Can; Obuz, Funda; Taylan, Abdullah; Atila, Koray; Bora, Seymen; Ellidokuz, Hulya

    2016-01-01

    PURPOSE We aimed to evaluate the relationship between gastrectomy and the volume of liver segments II and III in patients with gastric cancer. METHODS Computed tomography images of 54 patients who underwent curative gastrectomy for gastric adenocarcinoma were retrospectively evaluated by two blinded observers. Volumes of the total liver and segments II and III were measured. The difference between preoperative and postoperative volume measurements was compared. RESULTS Total liver volumes measured by both observers in the preoperative and postoperative scans were similar (P > 0.05). High correlation was found between both observers (preoperative r=0.99; postoperative r=0.98). Total liver volumes showed a mean reduction of 13.4% after gastrectomy (P = 0.977). The mean volume of segments II and III showed similar decrease in measurements of both observers (38.4% vs. 36.4%, P = 0.363); the correlation between the observers were high (preoperative r=0.97, P < 0.001; postoperative r=0.99, P < 0.001). Volume decrease in the rest of the liver was not different between the observers (8.2% vs. 9.1%, P = 0.388). Time had poor correlation with volume change of segments II and III and the total liver for each observer (observer 1, rseg2/3=0.32, rtotal=0.13; observer 2, rseg2/3=0.37, rtotal=0.16). CONCLUSION Segments II and III of the liver showed significant atrophy compared with the rest of the liver and the total liver after gastrectomy. Volume reduction had poor correlation with time. PMID:26899148

  19. Living donor liver transplantation for neonatal hemochromatosis using non-anatomically resected segments II and III: a case report

    PubMed Central

    2010-01-01

    Introduction Neonatal hemochromatosis is the most common cause of liver failure and liver transplantation in the newborn. The size of the infant determines the liver volume that can be transplanted safely without incurring complications arising from a large graft. Transplantation of monosegments II or III is a standard method for the newborns with liver failure. Case presentation A three-week old African-American male neonate was diagnosed with acute liver failure secondary to neonatal hemochromatosis. Living-related liver transplantation was considered after the failure of intensive medical therapy. Intra-operatively a non-anatomical resection and transplantation of segments II and III was performed successfully. The boy is growing normally two years after the transplantation. Conclusion Non-anatomical resection and transplantation of liver segments II and III is preferred to the transplantation of anatomically resected monosegements, especially when the left lobe is thin and flat. It allows the use of a reduced-size donor liver with intact hilar structures and outflow veins. In an emergency, living-related liver transplantation should be offered to infants with liver failure secondary to neonatal hemochromatosis who fail to respond to medical treatment. PMID:21092086

  20. Co-option of Liver Vessels and Not Sprouting Angiogenesis Drives Acquired Sorafenib Resistance in Hepatocellular Carcinoma

    PubMed Central

    Kuczynski, Elizabeth A.; Yin, Melissa; Bar-Zion, Avinoam; Lee, Christina R.; Butz, Henriett; Man, Shan; Daley, Frances; Vermeulen, Peter B.; Yousef, George M.; Foster, F. Stuart

    2016-01-01

    Background: The anti-angiogenic Sorafenib is the only approved systemic therapy for advanced hepatocellular carcinoma (HCC). However, acquired resistance limits its efficacy. An emerging theory to explain intrinsic resistance to other anti-angiogenic drugs is ‘vessel co-option,’ ie, the ability of tumors to hijack the existing vasculature in organs such as the lungs or liver, thus limiting the need for sprouting angiogenesis. Vessel co-option has not been evaluated as a potential mechanism for acquired resistance to anti-angiogenic agents. Methods: To study sorafenib resistance mechanisms, we used an orthotopic human HCC model (n = 4-11 per group), where tumor cells are tagged with a secreted protein biomarker to monitor disease burden and response to therapy. Histopathology, vessel perfusion assessed by contrast-enhanced ultrasound, and miRNA sequencing and quantitative real-time polymerase chain reaction were used to monitor changes in tumor biology. Results: While sorafenib initially inhibited angiogenesis and stabilized tumor growth, no angiogenic ‘rebound’ effect was observed during development of resistance unless therapy was stopped. Instead, resistant tumors became more locally infiltrative, which facilitated extensive incorporation of liver parenchyma and the co-option of liver-associated vessels. Up to 75% (±10.9%) of total vessels were provided by vessel co-option in resistant tumors relative to 23.3% (±10.3%) in untreated controls. miRNA sequencing implicated pro-invasive signaling and epithelial-to-mesenchymal-like transition during resistance development while functional imaging further supported a shift from angiogenesis to vessel co-option. Conclusions: This is the first documentation of vessel co-option as a mechanism of acquired resistance to anti-angiogenic therapy and could have important implications including the potential therapeutic benefits of targeting vessel co-option in conjunction with vascular endothelial growth factor

  1. Automated segmentation and quantification of liver and spleen from CT images using normalized probabilistic atlases and enhancement estimation

    PubMed Central

    Linguraru, Marius George; Sandberg, Jesse K.; Li, Zhixi; Shah, Furhawn; Summers, Ronald M.

    2010-01-01

    Purpose: To investigate the potential of the normalized probabilistic atlases and computer-aided medical image analysis to automatically segment and quantify livers and spleens for extracting imaging biomarkers (volume and height). Methods: A clinical tool was developed to segment livers and spleen from 257 abdominal contrast-enhanced CT studies. There were 51 normal livers, 44 normal spleens, 128 splenomegaly, 59 hepatomegaly, and 23 partial hepatectomy cases. 20 more contrast-enhanced CT scans from a public site with manual segmentations of mainly pathological livers were used to test the method. Data were acquired on a variety of scanners from different manufacturers and at varying resolution. Probabilistic atlases of livers and spleens were created using manually segmented data from ten noncontrast CT scans (five male and five female). The organ locations were modeled in the physical space and normalized to the position of an anatomical landmark, the xiphoid. The construction and exploitation of liver and spleen atlases enabled the automated quantifications of liver∕spleen volumes and heights (midhepatic liver height and cephalocaudal spleen height) from abdominal CT data. The quantification was improved incrementally by a geodesic active contour, patient specific contrast-enhancement characteristics passed to an adaptive convolution, and correction for shape and location errors. Results: The livers and spleens were robustly segmented from normal and pathological cases. For the liver, the Dice∕Tanimoto volume overlaps were 96.2%∕92.7%, the volume∕height errors were 2.2%∕2.8%, the root-mean-squared error (RMSE) was 2.3 mm, and the average surface distance (ASD) was 1.2 mm. The spleen quantification led to 95.2%∕91% Dice∕Tanimoto overlaps, 3.3%∕1.7% volume∕height errors, 1.1 mm RMSE, and 0.7 ASD. The correlations (R2) with clinical∕manual height measurements were 0.97 and 0.93 for the spleen and liver, respectively (p<0.0001). No significant

  2. ANGY: A Rule-Based Expert System for Automatic Segmentation of Coronary Vessels From Digital Subtracted Angiograms.

    PubMed

    Stansfield, S A

    1986-02-01

    This paper details the design and implementation of ANGY, a rule-based expert system in the domain of medical image processing. Given a subtracted digital angiogram of the chest, ANGY identifies and isolates the coronary vessels, while ignoring any nonvessel structures which may have arisen from noise, variations in background contrast, imperfect subtraction, and irrelevent anatomical detail. The overall system is modularized into three stages: the preprocessing stage and the two stages embodied in the expert itself. In the preprocessing stage, low-level image processing routines written in C are used to create a segmented representation of the input image. These routines are applied sequentially. The expert system is rule-based and is written in OPS5 and LISP. It is separated into two stages: The low-level image processing stage embodies a domain-independent knowledge of segmentation, grouping, and shape analysis. Working with both edges and regions, it determines such relations as parallel and adjacent and attempts to refine the segmentation begun by the preprocessing. The high-level medical stage embodies a domain-dependent knowledge of cardiac anatomy and physiology. Applying this knowledge to the objects and relations determined in the preceding two stages, it identifies those objects which are vessels and eliminates all others. PMID:21869337

  3. Maintenance of liver functions in rat hepatocytes cultured as spheroids in a rotating wall vessel.

    PubMed

    Brown, Lanika A; Arterburn, Linda M; Miller, Ana P; Cowger, Nancy L; Hartley, Sonya M; Andrews, Annette; Silber, Paul M; Li, Albert P

    2003-01-01

    Rat hepatocytes were cultured initially as spheroids on culture plates and then transferred into a rotating wall vessel (high-aspect ratio vessel [HARV]) for further culturing. Morphological evaluation based on electron microscopy showed that hepatocyte spheroids cultured for 30 d in the HARV had a compact structure with tight cell-cell junctions, numerous smooth and rough endoplasmic reticulum, intact mitochondria, and bile canaliculi lined with microvilli. The viability and differentiated properties of the hepatocytes cultured in the HARV were further substantiated by the presence of both phase I oxidation and phase II conjugation drug-metabolizing enzyme activities, as well as albumin synthesis. Homogenates prepared from freshly isolated hepatocytes and hepatocytes cultured in the HARV showed similar cytochrome P450 2B activities measured as pentoxyresorufin-O-dealkylase and testosterone 16beta-hydroxylase. Further, intact hepatocytes cultured in the HARV were found to metabolize chlorzoxazone to 6-hydroxychlorzoxazone; dextromethorphan to dextrorphan, 3-methoxymorphinan, and 3-hydroxymorphinan; midazolam to 1-hydroxymidazolam and 4-hydroxymidazolam; and 7-hydroxycoumarin to its glucuronide and sulfate conjugates. In conclusion, we found that hepatocyte spheroids could be cultured in a HARV to retain cellular and physiological properties of the intact liver, including drug-metabolizing enzyme activities, plasma protein production, and long-term (1 mo) maintenance of viability and cellular function. PMID:12892522

  4. A region-appearance-based adaptive variational model for 3D liver segmentation

    SciTech Connect

    Peng, Jialin; Dong, Fangfang; Chen, Yunmei; Kong, Dexing

    2014-04-15

    Purpose: Liver segmentation from computed tomography images is a challenging task owing to pixel intensity overlapping, ambiguous edges, and complex backgrounds. The authors address this problem with a novel active surface scheme, which minimizes an energy functional combining both edge- and region-based information. Methods: In this semiautomatic method, the evolving surface is principally attracted to strong edges but is facilitated by the region-based information where edge information is missing. As avoiding oversegmentation is the primary challenge, the authors take into account multiple features and appearance context information. Discriminative cues, such as multilayer consecutiveness and local organ deformation are also implicitly incorporated. Case-specific intensity and appearance constraints are included to cope with the typically large appearance variations over multiple images. Spatially adaptive balancing weights are employed to handle the nonuniformity of image features. Results: Comparisons and validations on difficult cases showed that the authors’ model can effectively discriminate the liver from adhering background tissues. Boundaries weak in gradient or with no local evidence (e.g., small edge gaps or parts with similar intensity to the background) were delineated without additional user constraint. With an average surface distance of 0.9 mm and an average volume overlap of 93.9% on the MICCAI data set, the authors’ model outperformed most state-of-the-art methods. Validations on eight volumes with different initial conditions had segmentation score variances mostly less than unity. Conclusions: The proposed model can efficiently delineate ambiguous liver edges from complex tissue backgrounds with reproducibility. Quantitative validations and comparative results demonstrate the accuracy and efficacy of the model.

  5. Flaw density examinations of a clad boiling water reactor pressure vessel segment

    SciTech Connect

    Cook, K.V.; McClung, R.W.

    1986-01-01

    Flaw density is the greatest uncertainty involved in probabilistic analyses of reactor pressure vessel failure. As part of the Heavy-Section Steel Technology (HSST) Program, studies have been conducted to determine flaw density in a section of reactor pressure vessel cut from the Hope Creek Unit 2 vessel (nominally 0.7 by 3 m (2 by 10 ft)). This section (removed from the scrapped vessel that was never in service) was evaluated nondestructively to determine the as-fabricated status. We had four primary objectives: (1) evaluate longitudinal and girth welds for flaws with manual ultrasonics, (2) evaluate the zone under the nominal 6.3-mm (0.25-in.) clad for cracking (again with manual ultrasonics), (3) evaluate the cladding for cracks with a high-sensitivity fluorescent penetrant method, and (4) determine the source of indications detected.

  6. 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. PMID:17215103

  7. Safety and Efficacy Assessment of Flow Redistribution by Occlusion of Intrahepatic Vessels Prior to Radioembolization in the Treatment of Liver Tumors

    SciTech Connect

    Bilbao, Jose I.; Garrastachu, Puy; Herraiz, Maria J.; Rodriguez, Macarena; Inarrairaegui, Mercedes; Rodriguez, Javier; Hernandez, Carmen; Cuesta, Antonio Martinez de la; Arbizu, Javier; Sangro, Bruno

    2010-06-15

    We evaluated the feasibility, safety, and efficacy of radioembolization (administered from one or two vascular points) after the redistribution of arterial blood flow in the liver in patients with hepatic neoplasms and arterial anatomic peculiarities (AAP). Twenty-four patients with liver neoplasms and AAP (graded according to Michel's classification) were included in the study. During pretreatment angiographic planning, all extrahepatic vessels that could feed the tumor were embolized and the intrahepatic vessels occluded in order to redistribute blood flow. The distribution of microspheres was initially assessed by using technetium-99m-labeled macroaggregated albumin ({sup 99m}Tc-MAA) from one of two vascular points before the administration of yttrium-90 ({sup 90}Y)-radiolabeled resin microspheres. Perfusion of lesions situated in the redistributed segments (L-RS) and nonredistributed segments (L-NRS) were compared by assessing the distribution of {sup 99m}Tc-MAA by SPECT/CT. Perfusion was graded as normal, reduced, or absent. {sup 90}Y resin microspheres were then injected from the same arterial sites as {sup 99m}Tc-MAA and the tumor response recorded 3 months later. The tumor response in L-RS was compared with that in L-NRS and graded as better, similar, or worse. Among 11 patients with type I AAP in whom mainly vessels in segments I-III or IV were occluded, perfusion of L-RS was graded as similar (n = 7) or reduced (n = 4). Among the remaining 13 patients with AAP types III (n = 3), V (n = 4), VIII (n = 3), and others (n = 3) in which aberrant arteries were occluded, perfusion of L-RS was graded as similar (n = 9), reduced (n = 3), or absent (n = 1). Overall, {sup 99m}Tc-MAA was present in the L-RS of 95.8% patients and the distribution of {sup 99m}Tc-MAA in L-RS and L-NRS were graded as similar in 66.6% of patients. Compared with lesions in the L-NRS, tumor response in L-RS was similar in 23 cases and worse in 1 case. No complications were recorded after the

  8. Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images.

    PubMed

    Hatanaka, Yuji; Nagahata, Yuuki; Muramatsu, Chisako; Okumura, Susumu; Ogohara, Kazunori; Sawada, Akira; Ishida, Kyoko; Yamamoto, Tetsuya; Fujita, Hiroshi

    2014-01-01

    Glaucoma is a leading cause of permanent blindness. Retinal imaging is useful for early detection of glaucoma. In order to evaluate the presence of glaucoma, ophthalmologists may determine the cup and disc areas and diagnose glaucoma using a vertical optic cup-to-disc (C/D) ratio and a rim-to-disc (R/D) ratio. Previously we proposed a method to determine cup edge by analyzing a vertical profile of pixel values, but this method provided a cup edge smaller than that of an ophthalmologist. This paper describes an improved method using the locations of the blood vessel bends. The blood vessels were detected by a concentration feature determined from the density gradient. The blood vessel bends were detected by tracking the blood vessels from the disc edge to the primary cup edge, which was determined by our previous method. Lastly, the vertical C/D ratio and the R/D ratio were calculated. Using forty-four images, including 32 glaucoma images, the AUCs of both the vertical C/D ratio and R/D ratio by this proposed method were 0.966 and 0.936, respectively. PMID:25569913

  9. Insufficient Portal Vein Inflow in Children without Major Shunt Vessels During Living Donor Liver Transplantation.

    PubMed

    Matsuura, Toshiharu; Yoshimaru, Koichiro; Yanagi, Yusuke; Esumi, Genshiro; Hayashida, Makoto; Taguchi, Tomoaki

    2016-01-01

    BACKGROUND Liver cirrhosis is frequently accompanied by insufficient portal vein inflow (IPVF) with large portosystemic shunts. However, pediatric cases often manifested IPVF without any apparent major portosystemic shunts. Although IPVF is a very critical issue, the intraoperative assessment has not been well established. In this study, we reviewed the intraoperative approach and the outcome of the IPVF cases at our department. MATERIAL AND METHODS Eighty-three living donor liver transplantations (LDLT) were performed from 1996 to 2014. The IPVF occurred in 5 cases and necessitated some additional assessments and intraoperative PV flow modulations. We retrospectively reviewed the operative records and analyzed the risk factors and the outcome of the IPVF. RESULTS All 5 IPVF cases were biliary atresia and the mean age at LDLT was 0.74±0.19 years old. The mean recipient PV diameter was 4.3±0.8 mm and the donor IMV patch grafts were applied. To increase the PV inflow, the collaterals around the spleen were ligated in all cases. Intraoperative portal venography was performed in 1 case for selective shunt vessel ligation. In 1 case, the graft was removed and returned to the back table to prevent graft loss during the IPVF. As a result, the final PVF/GV increased to 66.4±20.0 ml/min/100 g. CONCLUSIONS IPVF is a very critical problem. Intraoperative portal venography is helpful and collateral veins ligation is crucial. In some cases, returning the graft to the back table during the PV inflow modulation can prevent graft loss. PMID:27306916

  10. Single hepatocellular carcinoma ≤ 3 cm in left lateral segment: Liver resection or radiofrequency ablation?

    PubMed Central

    Kim, Jong Man; Kang, Tae Wook; Kwon, Choon Hyuck David; Joh, Jae-Won; Ko, Justin Sangwook; Park, Jae Berm; Rhim, Hyunchul; Lee, Joon Hyeok; Kim, Sung Joo; Paik, Seung Woon

    2014-01-01

    AIM: To evaluate the long-term results of radiofrequency ablation (RFA) compared to left lateral sectionectomy (LLS) in patients with Child-Pugh class A disease for the treatment of single and small hepatocellular carcinoma (HCC) in the left lateral segments. METHODS: We retrospectively reviewed the data of 133 patients with single HCC (≤ 3 cm) in their left lateral segments who underwent curative LLS (n = 66) or RFA (n = 67) between 2006 and 2010. RESULTS: The median follow-up period was 33.5 mo in the LLS group and 29 mo in the RFA group (P = 0.060). Most patients had hepatitis B virus-related HCC. The hospital stay was longer in the LLS group than in the RFA group (8 d vs 2 d, P < 0.001). The 1-, 2-, and 3-year disease-free survival and overall survival rates were 80.0%, 68.2%, and 60.0%, and 95.4%, 92.3%, and 92.3%, respectively, for the LLS group; and 80.8%, 59.9%, and 39.6%, and 98.2%, 92.0%, and 74.4%, respectively, for the RFA group. The disease-free survival curve and overall survival curve were higher in the LLS group than in the RFA group (P = 0.012 and P = 0.013, respectively). Increased PIVKA-II levels and small tumor size were associated with HCC recurrence in multivariate analysis. CONCLUSION: Liver resection is suitable for single HCC ≤ 3 cm in the left lateral segments. PMID:24744596

  11. Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI images.

    PubMed

    Pavliha, Denis; Mušič, Maja M; Serša, Gregor; Miklavčič, Damijan

    2013-01-01

    Electroporation is the phenomenon that occurs when a cell is exposed to a high electric field, which causes transient cell membrane permeabilization. A paramount electroporation-based application is electrochemotherapy, which is performed by delivering high-voltage electric pulses that enable the chemotherapeutic drug to more effectively destroy the tumor cells. Electrochemotherapy can be used for treating deep-seated metastases (e.g. in the liver, bone, brain, soft tissue) using variable-geometry long-needle electrodes. To treat deep-seated tumors, patient-specific treatment planning of the electroporation-based treatment is required. Treatment planning is based on generating a 3D model of the organ and target tissue subject to electroporation (i.e. tumor nodules). The generation of the 3D model is done by segmentation algorithms. We implemented and evaluated three automatic liver segmentation algorithms: region growing, adaptive threshold, and active contours (snakes). The algorithms were optimized using a seven-case dataset manually segmented by the radiologist as a training set, and finally validated using an additional four-case dataset that was previously not included in the optimization dataset. The presented results demonstrate that patient's medical images that were not included in the training set can be successfully segmented using our three algorithms. Besides electroporation-based treatments, these algorithms can be used in applications where automatic liver segmentation is required. PMID:23936315

  12. Automated detection of kinks from blood vessels for optic cup segmentation in retinal images

    NASA Astrophysics Data System (ADS)

    Wong, D. W. K.; Liu, J.; Lim, J. H.; Li, H.; Wong, T. Y.

    2009-02-01

    The accurate localization of the optic cup in retinal images is important to assess the cup to disc ratio (CDR) for glaucoma screening and management. Glaucoma is physiologically assessed by the increased excavation of the optic cup within the optic nerve head, also known as the optic disc. The CDR is thus an important indicator of risk and severity of glaucoma. In this paper, we propose a method of determining the cup boundary using non-stereographic retinal images by the automatic detection of a morphological feature within the optic disc known as kinks. Kinks are defined as the bendings of small vessels as they traverse from the disc to the cup, providing physiological validation for the cup boundary. To detect kinks, localized patches are first generated from a preliminary cup boundary obtained via level set. Features obtained using edge detection and wavelet transform are combined using a statistical approach rule to identify likely vessel edges. The kinks are then obtained automatically by analyzing the detected vessel edges for angular changes, and these kinks are subsequently used to obtain the cup boundary. A set of retinal images from the Singapore Eye Research Institute was obtained to assess the performance of the method, with each image being clinically graded for the CDR. From experiments, when kinks were used, the error on the CDR was reduced to less than 0.1 CDR units relative to the clinical CDR, which is within the intra-observer variability of 0.2 CDR units.

  13. Label-free optical lymphangiography: development of an automatic segmentation method applied to optical coherence tomography to visualize lymphatic vessels using Hessian filters

    NASA Astrophysics Data System (ADS)

    Yousefi, Siavash; Qin, Jia; Zhi, Zhongwei; Wang, Ruikang K.

    2013-08-01

    Lymphatic vessels are a part of the circulatory system that collect plasma and other substances that have leaked from the capillaries into interstitial fluid (lymph) and transport lymph back to the circulatory system. Since lymph is transparent, lymphatic vessels appear as dark hallow vessel-like regions in optical coherence tomography (OCT) cross sectional images. We propose an automatic method to segment lymphatic vessel lumen from OCT structural cross sections using eigenvalues of Hessian filters. Compared to the existing method based on intensity threshold, Hessian filters are more selective on vessel shape and less sensitive to intensity variations and noise. Using this segmentation technique along with optical micro-angiography allows label-free noninvasive simultaneous visualization of blood and lymphatic vessels in vivo. Lymphatic vessels play an important role in cancer, immune system response, inflammatory disease, wound healing and tissue regeneration. Development of imaging techniques and visualization tools for lymphatic vessels is valuable in understanding the mechanisms and studying therapeutic methods in related disease and tissue response.

  14. Investigation of source-detector separation optimization for an implantable perfusion and oxygenation sensor for liver blood vessels

    NASA Astrophysics Data System (ADS)

    Baba, J. S.; Akl, T. J.; Coté, G. L.; Wilson, M. A.; Ericson, M. N.

    2011-03-01

    An implanted system is being developed to monitor transplanted liver health during the critical 7-10 day period posttransplantation. The unit will monitor organ perfusion and oxygen consumption using optically-based probes placed on both the inflow and outflow blood vessels, and on the liver parenchymal surface. Sensing probes are based on a 3- wavelength LED source and a photodiode detector. Sample diffuse reflectance is measured at 735, 805, and 940 nm. To ascertain optimal source-to-photodetector spacing for perfusion measurement in blood vessels, an ex vivo study was conducted. In this work, a dye mixture simulating 80% blood oxygen saturation was developed and perfused through excised porcine arteries while collecting data for various preset probe source-to-photodetector spacings. The results from this study demonstrate a decrease in the optical signal with decreasing LED drive current and a reduction in perfusion index signal with increasing probe spacing. They also reveal a 2- to 4-mm optimal range for blood vessel perfusion probe source-to-photodetector spacing that allows for sufficient perfusion signal modulation depth with maximized signal to noise ratio (SNR). These findings are currently being applied to guide electronic configuration and probe placement for in vivo liver perfusion porcine model studies.

  15. Segments.

    ERIC Educational Resources Information Center

    Zemsky, Robert; Shaman, Susan; Shapiro, Daniel B.

    2001-01-01

    Presents a market taxonomy for higher education, including what it reveals about the structure of the market, the model's technical attributes, and its capacity to explain pricing behavior. Details the identification of the principle seams separating one market segment from another and how student aspirations help to organize the market, making…

  16. A modified Seeded Region Growing algorithm for vessel segmentation in breast MRI images for investigating the nature of potential lesions

    NASA Astrophysics Data System (ADS)

    Glotsos, D.; Vassiou, K.; Kostopoulos, S.; Lavdas, El; Kalatzis, I.; Asvestas, P.; Arvanitis, D. L.; Fezoulidis, I. V.; Cavouras, D.

    2014-03-01

    The role of Magnetic Resonance Imaging (MRI) as an alternative protocol for screening of breast cancer has been intensively investigated during the past decade. Preliminary research results have indicated that gadolinium-agent administrative MRI scans may reveal the nature of breast lesions by analyzing the contrast-agent's uptake time. In this study, we attempt to deduce the same conclusion, however, from a different perspective by investigating, using image processing, the vascular network of the breast at two different time intervals following the administration of gadolinium. Twenty cases obtained from a 3.0-T MRI system (SIGNA HDx; GE Healthcare) were included in the study. A new modification of the Seeded Region Growing (SRG) algorithm was used to segment vessels from surrounding background. Delineated vessels were investigated by means of their topology, morphology and texture. Results have shown that it is possible to estimate the nature of the lesions with approximately 94.4% accuracy, thus, it may be claimed that the breast vascular network does encodes useful, patterned, information, which can be used for characterizing breast lesions.

  17. Active shape models for a fully automated 3D segmentation of the liver--an evaluation on clinical data.

    PubMed

    Heimann, Tobias; Wolf, Ivo; Meinzer, Hans-Peter

    2006-01-01

    This paper presents an evaluation of the performance of a three-dimensional Active Shape Model (ASM) to segment the liver in 48 clinical CT scans. The employed shape model is built from 32 samples using an optimization approach based on the minimum description length (MDL). Three different gray-value appearance models (plain intensity, gradient and normalized gradient profiles) are created to guide the search. The employed segmentation techniques are ASM search with 10 and 30 modes of variation and a deformable model coupled to a shape model with 10 modes of variation. To assess the segmentation performance, the obtained results are compared to manual segmentations with four different measures (overlap, average distance, RMS distance and ratio of deviations larger 5mm). The only appearance model delivering usable results is the normalized gradient profile. The deformable model search achieves the best results, followed by the ASM search with 30 modes. Overall, statistical shape modeling delivers very promising results for a fully automated segmentation of the liver. PMID:17354754

  18. Automatic detection and segmentation of vascular structures in dermoscopy images using a novel vesselness measure based on pixel redness and tubularness

    NASA Astrophysics Data System (ADS)

    Kharazmi, Pegah; Lui, Harvey; Stoecker, William V.; Lee, Tim

    2015-03-01

    Vascular structures are one of the most important features in the diagnosis and assessment of skin disorders. The presence and clinical appearance of vascular structures in skin lesions is a discriminating factor among different skin diseases. In this paper, we address the problem of segmentation of vascular patterns in dermoscopy images. Our proposed method is composed of three parts. First, based on biological properties of human skin, we decompose the skin to melanin and hemoglobin component using independent component analysis of skin color images. The relative quantities and pure color densities of each component were then estimated. Subsequently, we obtain three reference vectors of the mean RGB values for normal skin, pigmented skin and blood vessels from the hemoglobin component by averaging over 100000 pixels of each group outlined by an expert. Based on the Euclidean distance thresholding, we generate a mask image that extracts the red regions of the skin. Finally, Frangi measure was applied to the extracted red areas to segment the tubular structures. Finally, Otsu's thresholding was applied to segment the vascular structures and get a binary vessel mask image. The algorithm was implemented on a set of 50 dermoscopy images. In order to evaluate the performance of our method, we have artificially extended some of the existing vessels in our dermoscopy data set and evaluated the performance of the algorithm to segment the newly added vessel pixels. A sensitivity of 95% and specificity of 87% were achieved.

  19. Negative space filling and 3D reconstruction of histological sections demonstrates differences in volumes of vessels and ducts within portal tracts of canine livers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Visualizing areas of tissue that are occupied by air or liquid can provide a unique perspective on the relationships between various spaces within the tissue. The portal tracts of liver tissue are an example of such a space since the liver contains several vessels and ducts in various patterns of i...

  20. Real-time segmentation of multiple implanted cylindrical liver markers in kilovoltage and megavoltage x-ray images

    NASA Astrophysics Data System (ADS)

    Fledelius, W.; Worm, E.; Høyer, M.; Grau, C.; Poulsen, P. R.

    2014-06-01

    Gold markers implanted in or near a tumor can be used as x-ray visible landmarks for image based tumor localization. The aim of this study was to develop and demonstrate fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in cone-beam CT (CBCT) projections, for real-time motion management. Thirteen patients treated with conformal stereotactic body radiation therapy in three fractions had 2-3 cylindrical gold markers implanted in the liver prior to treatment. At each fraction, the projection images of a pre-treatment CBCT scan were used for automatic generation of a 3D marker model that consisted of the size, orientation, and estimated 3D trajectory of each marker during the CBCT scan. The 3D marker model was used for real-time template based segmentation in subsequent x-ray images by projecting each marker's 3D shape and likely 3D motion range onto the imager plane. The segmentation was performed in intra-treatment kV images (526 marker traces, 92 097 marker projections) and MV images (88 marker traces, 22 382 marker projections), and in post-treatment CBCT projections (42 CBCT scans, 71 381 marker projections). 227 kV marker traces with low mean contrast-to-noise ratio were excluded as markers were not visible due to MV scatter. Online segmentation times measured for a limited dataset were used for estimating real-time segmentation times for all images. The percentage of detected markers was 94.8% (kV), 96.1% (MV), and 98.6% (CBCT). For the detected markers, the real-time segmentation was erroneous in 0.2-0.31% of the cases. The mean segmentation time per marker was 5.6 ms [2.1-12 ms] (kV), 5.5 ms [1.6-13 ms] (MV), and 6.5 ms [1.8-15 ms] (CBCT). Fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in CBCT projections was demonstrated for a large dataset.

  1. Real-time segmentation of multiple implanted cylindrical liver markers in kilovoltage and megavoltage x-ray images.

    PubMed

    Fledelius, W; Worm, E; Høyer, M; Grau, C; Poulsen, P R

    2014-06-01

    Gold markers implanted in or near a tumor can be used as x-ray visible landmarks for image based tumor localization. The aim of this study was to develop and demonstrate fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in cone-beam CT (CBCT) projections, for real-time motion management. Thirteen patients treated with conformal stereotactic body radiation therapy in three fractions had 2-3 cylindrical gold markers implanted in the liver prior to treatment. At each fraction, the projection images of a pre-treatment CBCT scan were used for automatic generation of a 3D marker model that consisted of the size, orientation, and estimated 3D trajectory of each marker during the CBCT scan. The 3D marker model was used for real-time template based segmentation in subsequent x-ray images by projecting each marker's 3D shape and likely 3D motion range onto the imager plane. The segmentation was performed in intra-treatment kV images (526 marker traces, 92,097 marker projections) and MV images (88 marker traces, 22,382 marker projections), and in post-treatment CBCT projections (42 CBCT scans, 71,381 marker projections). 227 kV marker traces with low mean contrast-to-noise ratio were excluded as markers were not visible due to MV scatter. Online segmentation times measured for a limited dataset were used for estimating real-time segmentation times for all images. The percentage of detected markers was 94.8% (kV), 96.1% (MV), and 98.6% (CBCT). For the detected markers, the real-time segmentation was erroneous in 0.2-0.31% of the cases. The mean segmentation time per marker was 5.6 ms [2.1-12 ms] (kV), 5.5 ms [1.6-13 ms] (MV), and 6.5 ms [1.8-15 ms] (CBCT). Fast and reliable real-time segmentation of multiple liver tumor markers in intra-treatment kV and MV images and in CBCT projections was demonstrated for a large dataset. PMID:24801205

  2. Automatic segmentation of the liver using multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images

    NASA Astrophysics Data System (ADS)

    Jang, Yujin; Hong, Helen; Chung, Jin Wook; Yoon, Young Ho

    2012-02-01

    We propose an effective technique for the extraction of liver boundary based on multi-planar anatomy and deformable surface model in abdominal contrast-enhanced CT images. Our method is composed of four main steps. First, for extracting an optimal volume circumscribing a liver, lower and side boundaries are defined by positional information of pelvis and rib. An upper boundary is defined by separating the lungs and heart from CT images. Second, for extracting an initial liver volume, optimal liver volume is smoothed by anisotropic diffusion filtering and is segmented using adaptively selected threshold value. Third, for removing neighbor organs from initial liver volume, morphological opening and connected component labeling are applied to multiple planes. Finally, for refining the liver boundaries, deformable surface model is applied to a posterior liver surface and missing left robe in previous step. Then, probability summation map is generated by calculating regional information of the segmented liver in coronal plane, which is used for restoring the inaccurate liver boundaries. Experimental results show that our segmentation method can accurately extract liver boundaries without leakage to neighbor organs in spite of various liver shape and ambiguous boundary.

  3. Robust Adaptive 3-D Segmentation of Vessel Laminae From Fluorescence Confocal Microscope Images and Parallel GPU Implementation

    PubMed Central

    Narayanaswamy, Arunachalam; Dwarakapuram, Saritha; Bjornsson, Christopher S.; Cutler, Barbara M.; Shain, William

    2010-01-01

    This paper presents robust 3-D algorithms to segment vasculature that is imaged by labeling laminae, rather than the lumenal volume. The signal is weak, sparse, noisy, nonuniform, low-contrast, and exhibits gaps and spectral artifacts, so adaptive thresholding and Hessian filtering based methods are not effective. The structure deviates from a tubular geometry, so tracing algorithms are not effective. We propose a four step approach. The first step detects candidate voxels using a robust hypothesis test based on a model that assumes Poisson noise and locally planar geometry. The second step performs an adaptive region growth to extract weakly labeled and fine vessels while rejecting spectral artifacts. To enable interactive visualization and estimation of features such as statistical confidence, local curvature, local thickness, and local normal, we perform the third step. In the third step, we construct an accurate mesh representation using marching tetrahedra, volume-preserving smoothing, and adaptive decimation algorithms. To enable topological analysis and efficient validation, we describe a method to estimate vessel centerlines using a ray casting and vote accumulation algorithm which forms the final step of our algorithm. Our algorithm lends itself to parallel processing, and yielded an 8× speedup on a graphics processor (GPU). On synthetic data, our meshes had average error per face (EPF) values of (0.1–1.6) voxels per mesh face for peak signal-to-noise ratios from (110–28 dB). Separately, the error from decimating the mesh to less than 1% of its original size, the EPF was less than 1 voxel/face. When validated on real datasets, the average recall and precision values were found to be 94.66% and 94.84%, respectively. PMID:20199906

  4. Pre-Operative Image-based Segmentation of the Cranial Nerves and Blood Vessels in Microvascular Decompression: Can we Prevent Unnecessary Explorations?

    PubMed Central

    Dolati, P; Golby, A; Eichberg, D; Abolfotoh, M; Dunn, IF; Mukundan, S; Hulou, MM; Al-Mefty, O

    2016-01-01

    Objectives This study was conducted to validate the accuracy of image-based pre-operative segmentation using the gold standard endoscopic and microscopic findings for localization and pre-operative diagnosis of the offensive vessel. Patients and Methods Fourteen TN and 6 HS cases were randomly selected. All patients had 3T MRI, which included thin-sectioned 3D space T2, 3D Time of Flight and MPRAGE Sequences. Imaging sequences were loaded in BrainLab iPlanNet and fused. Individual segmentation of the affected cranial nerves and the compressing vascular structure was performed by a neurosurgeon, and the results were compared with the microscopic and endoscopic findings by two blinded neurosurgeons. For each case, at least three neurovascular landmarks were targeted. Each segmented neurovascular element was validated by manual placement of the navigation probe over each target, and errors of localization were measured in mm. Results All patients underwent retro-sigmoid craniotomy and MVD using both microscope and endoscope. Based on image segmentation, the compressing vessel was identified in all cases except one, which was also negative intraoperatively. Perfect correspondence was found between image-based segmentation and endoscopic and microscopic images and videos (Dice coefficient of 1). Measurement accuracy was 0.45+/-0.21 mm (mean +/-SD). Conclusion Image-based segmentation is a promising method for pre-operative identification and localization of offending blood vessels causing HFS and TN. Using this method may prevent some unnecessary explorations on especially atypical cases with no vascular contacts. However, negative pre-operative image segmentation may not preclude one from exploration in classic cases of TN or HFS. A multicenter study with larger number of cases is recommended. PMID:26476700

  5. 3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

    NASA Astrophysics Data System (ADS)

    Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

    2015-03-01

    During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

  6. Framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms in conjunction with 3D landmark localization and registration

    NASA Astrophysics Data System (ADS)

    Wörz, Stefan; Hoegen, Philipp; Liao, Wei; Müller-Eschner, Matthias; Kauczor, Hans-Ulrich; von Tengg-Kobligk, Hendrik; Rohr, Karl

    2016-03-01

    We introduce a framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms. Phantoms are designed using a CAD system and created with a 3D printer, and comprise realistic shapes including branches and pathologies such as abdominal aortic aneurysms (AAA). To transfer ground truth information to the 3D image coordinate system, we use a landmark-based registration scheme utilizing fiducial markers integrated in the phantom design. For accurate 3D localization of the markers we developed a novel 3D parametric intensity model that is directly fitted to the markers in the images. We also performed a quantitative evaluation of different vessel segmentation approaches for a phantom of an AAA.

  7. Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network

    PubMed Central

    2016-01-01

    Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN), which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the “ground truth.” Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively. PMID:27597960

  8. Liver Tumor Segmentation from MR Images Using 3D Fast Marching Algorithm and Single Hidden Layer Feedforward Neural Network.

    PubMed

    Le, Trong-Ngoc; Bao, Pham The; Huynh, Hieu Trung

    2016-01-01

    Objective. Our objective is to develop a computerized scheme for liver tumor segmentation in MR images. Materials and Methods. Our proposed scheme consists of four main stages. Firstly, the region of interest (ROI) image which contains the liver tumor region in the T1-weighted MR image series was extracted by using seed points. The noise in this ROI image was reduced and the boundaries were enhanced. A 3D fast marching algorithm was applied to generate the initial labeled regions which are considered as teacher regions. A single hidden layer feedforward neural network (SLFN), which was trained by a noniterative algorithm, was employed to classify the unlabeled voxels. Finally, the postprocessing stage was applied to extract and refine the liver tumor boundaries. The liver tumors determined by our scheme were compared with those manually traced by a radiologist, used as the "ground truth." Results. The study was evaluated on two datasets of 25 tumors from 16 patients. The proposed scheme obtained the mean volumetric overlap error of 27.43% and the mean percentage volume error of 15.73%. The mean of the average surface distance, the root mean square surface distance, and the maximal surface distance were 0.58 mm, 1.20 mm, and 6.29 mm, respectively. PMID:27597960

  9. Computer-aided measurement of liver volumes in CT by means of geodesic active contour segmentation coupled with level-set algorithms

    SciTech Connect

    Suzuki, Kenji; Kohlbrenner, Ryan; Epstein, Mark L.; Obajuluwa, Ademola M.; Xu Jianwu; Hori, Masatoshi

    2010-05-15

    Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic active contour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic active contour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time

  10. A simple technique for hemostasis control after enucleation of deep located liver tumors or after liver trauma.

    PubMed

    Machado, Marcel A; Surjan, Rodrigo C; Basseres, Tiago; Makdissi, Fábio F

    2016-01-01

    Modern liver techniques allowed the development of segment-based anatomical liver resections. Nevertheless, there is still a place for nonanatomical liver resections. However, in some cases, there is a need for enucleation of deep located liver tumors. The main problem with enucleation of a liver tumor deeply located in the middle of the liver is the control of bleeding resulting from the rupture of small or medium vessels. The authors describe a simple way to control the bleeding without the use of any special instrument or material. This technique can also be used to control bleeding from penetrating liver injury. PMID:26846270

  11. Semi-automated segmentation of solid and GGO nodules in lung CT images using vessel-likelihood derived from local foreground structure

    NASA Astrophysics Data System (ADS)

    Yaguchi, Atsushi; Okazaki, Tomoya; Takeguchi, Tomoyuki; Matsumoto, Sumiaki; Ohno, Yoshiharu; Aoyagi, Kota; Yamagata, Hitoshi

    2015-03-01

    Reflecting global interest in lung cancer screening, considerable attention has been paid to automatic segmentation and volumetric measurement of lung nodules on CT. Ground glass opacity (GGO) nodules deserve special consideration in this context, since it has been reported that they are more likely to be malignant than solid nodules. However, due to relatively low contrast and indistinct boundaries of GGO nodules, segmentation is more difficult for GGO nodules compared with solid nodules. To overcome this difficulty, we propose a method for accurately segmenting not only solid nodules but also GGO nodules without prior information about nodule types. First, the histogram of CT values in pre-extracted lung regions is modeled by a Gaussian mixture model and a threshold value for including high-attenuation regions is computed. Second, after setting up a region of interest around the nodule seed point, foreground regions are extracted by using the threshold and quick-shift-based mode seeking. Finally, for separating vessels from the nodule, a vessel-likelihood map derived from elongatedness of foreground regions is computed, and a region growing scheme starting from the seed point is applied to the map with the aid of fast marching method. Experimental results using an anthropomorphic chest phantom showed that our method yielded generally lower volumetric measurement errors for both solid and GGO nodules compared with other methods reported in preceding studies conducted using similar technical settings. Also, our method allowed reasonable segmentation of GGO nodules in low-dose images and could be applied to clinical CT images including part-solid nodules.

  12. Preferential orientation of centrioles toward the heart in endothelial cells of major blood vessels is reestablished after reversal of a segment.

    PubMed Central

    Rogers, K A; McKee, N H; Kalnins, V I

    1985-01-01

    The distribution of centrioles was examined in porcine and rabbit vascular endothelial cells fixed in situ and prepared en face for immunofluorescent staining with rabbit sera that specifically stain these organelles. In endothelial cells lining the major blood vessels of the pig, the centrioles are preferentially located on the heart side of the nucleus regardless of the direction of blood flow. A similar distribution is seen in the inferior vena cava of the rabbit but not in the rabbit aorta. In the major vessels of the pig and in the rabbit inferior vena cava, 60%-80% of the endothelial cells have their centrioles located on the side of the nucleus toward the heart, 10%-20% have them on the side away from the heart, and 7%-15% have them in a central position along the side of the nucleus. To determine whether this preferential orientation is reestablished, microvascular surgical techniques were used to reverse a 3-cm segment of the inferior vena cava between the left renal vein and the common iliac veins of the rabbit. Within 1 week of the reversal, some of the centrioles had migrated from the end away from the heart to a more central position. During the following weeks, an increasing number of endothelial cells had their centrioles located on the heart side of the nucleus; after 12 weeks, values similar to those in the nonreversed inferior vena cava were reached in the reversed segment. The demonstration that the preferential orientation of centrioles on the heart side of the nucleus is reestablished after reversal of a segment suggests that the observed polarity is important for normal functioning of vascular endothelium. Images PMID:3889904

  13. Automatic Registration between Real-Time Ultrasonography and Pre-Procedural Magnetic Resonance Images: A Prospective Comparison between Two Registration Methods by Liver Surface and Vessel and by Liver Surface Only.

    PubMed

    Kim, Ah Yeong; Lee, Min Woo; Cha, Dong Ik; Lim, Hyo Keun; Oh, Young-Taek; Jeong, Ja-Yeon; Chang, Jung-Woo; Ryu, Jiwon; Lee, Kyong Joon; Kim, Jaeil; Bang, Won-Chul; Shin, Dong Kuk; Choi, Sung Jin; Koh, Dalkwon; Seo, Bong Koo; Kim, Kyunga

    2016-07-01

    The aim of this study was to compare the accuracy of and the time required for image fusion between real-time ultrasonography (US) and pre-procedural magnetic resonance (MR) images using automatic registration by a liver surface only method and automatic registration by a liver surface and vessel method. This study consisted of 20 patients referred for planning US to assess the feasibility of percutaneous radiofrequency ablation or biopsy for focal hepatic lesions. The first 10 consecutive patients were evaluated by an experienced radiologist using the automatic registration by liver surface and vessel method, whereas the remaining 10 patients were evaluated using the automatic registration by liver surface only method. For all 20 patients, image fusion was automatically executed after following the protocols and fused real-time US and MR images moved synchronously. The accuracy of each method was evaluated by measuring the registration error, and the time required for image fusion was assessed by evaluating the recorded data using in-house software. The results obtained using the two automatic registration methods were compared using the Mann-Whitney U-test. Image fusion was successful in all 20 patients, and the time required for image fusion was significantly shorter with the automatic registration by liver surface only method than with the automatic registration by liver surface and vessel method (median: 43.0 s, range: 29-74 s vs. median: 83.0 s, range: 46-101 s; p = 0.002). The registration error did not significantly differ between the two methods (median: 4.0 mm, range: 2.1-9.9 mm vs. median: 3.7 mm, range: 1.8-5.2 mm; p = 0.496). The automatic registration by liver surface only method offers faster image fusion between real-time US and pre-procedural MR images than does the automatic registration by liver surface and vessel method. However, the degree of accuracy was similar for the two methods. PMID:27085384

  14. Crystal structure of cod liver class I alcohol dehydrogenase: substrate pocket and structurally variable segments.

    PubMed Central

    Ramaswamy, S.; el Ahmad, M.; Danielsson, O.; Jörnvall, H.; Eklund, H.

    1996-01-01

    The structural framework of cod liver alcohol dehydrogenase is similar to that of horse and human alcohol dehydrogenases. In contrast, the substrate pocket differs significantly, and main differences are located in three loops. Nevertheless, the substrate pocket is hydrophobic like that of the mammalian class I enzymes and has a similar topography in spite of many main-chain and side-chain differences. The structural framework of alcohol dehydrogenase is also present in a number of related enzymes like glucose dehydrogenase and quinone oxidoreductase. These enzymes have completely different substrate specificity, but also for these enzymes, the corresponding loops of the substrate pocket have significantly different structures. The domains of the two subunits in the crystals of the cod enzyme further differ by a rotation of the catalytic domains by about 6 degrees. In one subunit, they close around the coenzyme similarly as in coenzyme complexes of the horse enzyme, but form a more open cleft in the other subunit, similar to the situation in coenzyme-free structures of the horse enzyme. The proton relay system differs from the mammalian class I alcohol dehydrogenases. His 51, which has been implicated in mammalian enzymes to be important for proton transfer from the buried active site to the surface is not present in the cod enzyme. A tyrosine in the corresponding position is turned into the substrate pocket and a water molecule occupies the same position in space as the His side chain, forming a shorter proton relay system. PMID:8845755

  15. Computer-aided classification of liver tumors in 3D ultrasound images with combined deformable model segmentation and support vector machine

    NASA Astrophysics Data System (ADS)

    Lee, Myungeun; Kim, Jong Hyo; Park, Moon Ho; Kim, Ye-Hoon; Seong, Yeong Kyeong; Cho, Baek Hwan; Woo, Kyoung-Gu

    2014-03-01

    In this study, we propose a computer-aided classification scheme of liver tumor in 3D ultrasound by using a combination of deformable model segmentation and support vector machine. For segmentation of tumors in 3D ultrasound images, a novel segmentation model was used which combined edge, region, and contour smoothness energies. Then four features were extracted from the segmented tumor including tumor edge, roundness, contrast, and internal texture. We used a support vector machine for the classification of features. The performance of the developed method was evaluated with a dataset of 79 cases including 20 cysts, 20 hemangiomas, and 39 hepatocellular carcinomas, as determined by the radiologist's visual scoring. Evaluation of the results showed that our proposed method produced tumor boundaries that were equal to or better than acceptable in 89.8% of cases, and achieved 93.7% accuracy in classification of cyst and hemangioma.

  16. Reconstruction of a rare variant of the left hepatic vein in a left lateral segment liver graft from a living donor: Technical notes

    PubMed Central

    Veerankutty, Fadl H.; Ali, T.U. Shabeer; Manoj, Krishnan Sarojam; Venugopal, B.

    2016-01-01

    Reconstruction of hepatic veins in living donor liver transplantation (LDLT) is often technically challenging and a good venous outflow is essential for survival of the graft and patient. We describe a quadrangular patch venoplasty technique used for the reconstruction of a rare variant of the left hepatic vein (LHV) in a pediatric LDLT with left lateral segment (LLS) graft. Segment II vein in the graft was draining directly into the inferior vena cava (IVC) and segment III vein was draining into the middle hepatic vein (MHV) after receiving a tributary from segment IV so that there were two widely separated ostia at the cut surface. This is one of the rarest variations of the LHV and is so called type 3 variant; it is usually reconstructed using interposition tubular conduits necessitating two separate anastomoses at the IVC. PMID:26862296

  17. Reconstruction of a rare variant of the left hepatic vein in a left lateral segment liver graft from a living donor: Technical notes.

    PubMed

    Veerankutty, Fadl H; Ali, T U Shabeer; Manoj, Krishnan Sarojam; Venugopal, B

    2016-01-01

    Reconstruction of hepatic veins in living donor liver transplantation (LDLT) is often technically challenging and a good venous outflow is essential for survival of the graft and patient. We describe a quadrangular patch venoplasty technique used for the reconstruction of a rare variant of the left hepatic vein (LHV) in a pediatric LDLT with left lateral segment (LLS) graft. Segment II vein in the graft was draining directly into the inferior vena cava (IVC) and segment III vein was draining into the middle hepatic vein (MHV) after receiving a tributary from segment IV so that there were two widely separated ostia at the cut surface. This is one of the rarest variations of the LHV and is so called type 3 variant; it is usually reconstructed using interposition tubular conduits necessitating two separate anastomoses at the IVC. PMID:26862296

  18. Vasculature segmentation for radio frequency ablation of non-resectable hepatic tumors

    NASA Astrophysics Data System (ADS)

    Hemler, Paul F.; McCreedy, Evan S.; Cheng, Ruida; Wood, Brad; McAuliffe, Matthew J.

    2006-03-01

    In Radio Frequency Ablation (RFA) procedures, hepatic tumor tissue is heated to a temperature where necrosis is insured. Unfortunately, recent results suggest that heating tumor tissue to necrosis is complicated because nearby major blood vessels provide a cooling effect. Therefore, it is fundamentally important for physicians to perform a careful analysis of the spatial relationship of diseased tissue to larger liver blood vessels. The liver contains many of these large vessels, which affect the RFA ablation shape and size. There are many sophisticated vasculature detection and segmentation techniques reported in the literature that identify continuous vessels as the diameter changes size and it transgresses through many bifurcation levels. However, the larger blood vessels near the treatment area are the only vessels required for proper RFA treatment plan formulation and analysis. With physician guidance and interaction, our system can segment those vessels which are most likely to affect the RFA ablations. We have found that our system provides the physician with therapeutic, geometric and spatial information necessary to accurately plan treatment of tumors near large blood vessels. The segmented liver vessels near the treatment region are also necessary for computing isolevel heating profiles used to evaluate different proposed treatment configurations.

  19. Reconstitution of hepatic tissue architectures from fetal liver cells obtained from a three-dimensional culture with a rotating wall vessel bioreactor.

    PubMed

    Ishikawa, Momotaro; Sekine, Keisuke; Okamura, Ai; Zheng, Yun-wen; Ueno, Yasuharu; Koike, Naoto; Tanaka, Junzo; Taniguchi, Hideki

    2011-06-01

    Reconstitution of tissue architecture in vitro is important because it enables researchers to investigate the interactions and mutual relationships between cells and cellular signals involved in the three-dimensional (3D) construction of tissues. To date, in vitro methods for producing tissues with highly ordered structure and high levels of function have met with limited success although a variety of 3D culture systems have been investigated. In this study, we reconstituted functional hepatic tissue including mature hepatocyte and blood vessel-like structures accompanied with bile duct-like structures from E15.5 fetal liver cells, which contained more hepatic stem/progenitor cells comparing with neonatal liver cells. The culture was performed in a simulated microgravity environment produced by a rotating wall vessel (RWV) bioreactor. The hepatocytes in the reconstituted 3D tissue were found to be capable of producing albumin and storing glycogen. Additionally, bile canaliculi between hepatocytes, characteristics of adult hepatocyte in vivo were also formed. Apart from this, bile duct structure secreting mucin was shown to form complicated tubular branches. Furthermore, gene expression analysis by semi-quantitative RT-PCR revealed the elevated levels of mature hepatocyte markers as well as genes with the hepatic function. With RWV culture system, we could produce functionally reconstituted liver tissue and this might be useful in pharmaceutical industry including drug screening and testing and other applications such as an alternative approach to experimental animals. PMID:21402492

  20. Liver.

    PubMed

    Kim, W R; Lake, J R; Smith, J M; Skeans, M A; Schladt, D P; Edwards, E B; Harper, A M; Wainright, J L; Snyder, J J; Israni, A K; Kasiske, B L

    2016-01-01

    The median waiting time for patients with MELD ≥ 35 decreased from 18 days in 2012 to 9 days in 2014, after implementation of the Share 35 policy in June 2013. Similarly, mortality among candidates listed with MELD ≥ 35 decreased from 366 per 100 waitlist years in 2012 to 315 in 2014. The number of new active candidates added to the pediatric liver transplant waiting list in 2014 was 655, down from a peak of 826 in 2005. The number of prevalent candidates (on the list on December 31 of the given year) continued to decline, 401 active and 173 inactive. The number of deceased donor pediatric liver transplants peaked at 542 in 2008 and was 478 in 2014. The number of living donor liver pediatric transplants was 52 in 2014; most were from donors closely related to the recipients. Graft survival continued to improve among pediatric recipients of deceased donor and living donor livers. PMID:26755264

  1. Implementation of an interactive liver surgery planning system

    NASA Astrophysics Data System (ADS)

    Wang, Luyao; Liu, Jingjing; Yuan, Rong; Gu, Shuguo; Yu, Long; Li, Zhitao; Li, Yanzhao; Li, Zhen; Xie, Qingguo; Hu, Daoyu

    2011-03-01

    Liver tumor, one of the most wide-spread diseases, has a very high mortality in China. To improve success rates of liver surgeries and life qualities of such patients, we implement an interactive liver surgery planning system based on contrastenhanced liver CT images. The system consists of five modules: pre-processing, segmentation, modeling, quantitative analysis and surgery simulation. The Graph Cuts method is utilized to automatically segment the liver based on an anatomical prior knowledge that liver is the biggest organ and has almost homogeneous gray value. The system supports users to build patient-specific liver segment and sub-segment models using interactive portal vein branch labeling, and to perform anatomical resection simulation. It also provides several tools to simulate atypical resection, including resection plane, sphere and curved surface. To match actual surgery resections well and simulate the process flexibly, we extend our work to develop a virtual scalpel model and simulate the scalpel movement in the hepatic tissue using multi-plane continuous resection. In addition, the quantitative analysis module makes it possible to assess the risk of a liver surgery. The preliminary results show that the system has the potential to offer an accurate 3D delineation of the liver anatomy, as well as the tumors' location in relation to vessels, and to facilitate liver resection surgeries. Furthermore, we are testing the system in a full-scale clinical trial.

  2. SU-E-I-87: Automated Liver Segmentation Method for CBCT Dataset by Combining Sparse Shape Composition and Probabilistic Atlas Construction

    SciTech Connect

    Li, Dengwang; Liu, Li; Chen, Jinhu; Li, Hongsheng

    2014-06-01

    Purpose: The aiming of this study was to extract liver structures for daily Cone beam CT (CBCT) images automatically. Methods: Datasets were collected from 50 intravenous contrast planning CT images, which were regarded as training dataset for probabilistic atlas and shape prior model construction. Firstly, probabilistic atlas and shape prior model based on sparse shape composition (SSC) were constructed by iterative deformable registration. Secondly, the artifacts and noise were removed from the daily CBCT image by an edge-preserving filtering using total variation with L1 norm (TV-L1). Furthermore, the initial liver region was obtained by registering the incoming CBCT image with the atlas utilizing edge-preserving deformable registration with multi-scale strategy, and then the initial liver region was converted to surface meshing which was registered with the shape model where the major variation of specific patient was modeled by sparse vectors. At the last stage, the shape and intensity information were incorporated into joint probabilistic model, and finally the liver structure was extracted by maximum a posteriori segmentation.Regarding the construction process, firstly the manually segmented contours were converted into meshes, and then arbitrary patient data was chosen as reference image to register with the rest of training datasets by deformable registration algorithm for constructing probabilistic atlas and prior shape model. To improve the efficiency of proposed method, the initial probabilistic atlas was used as reference image to register with other patient data for iterative construction for removing bias caused by arbitrary selection. Results: The experiment validated the accuracy of the segmentation results quantitatively by comparing with the manually ones. The volumetric overlap percentage between the automatically generated liver contours and the ground truth were on an average 88%–95% for CBCT images. Conclusion: The experiment demonstrated

  3. Graph representation of hepatic vessel based on centerline extraction and junction detection

    NASA Astrophysics Data System (ADS)

    Zhang, Xing; Tian, Jie; Deng, Kexin; Li, Xiuli; Yang, Fei

    2012-02-01

    In the area of computer-aided diagnosis (CAD), segmentation and analysis of hepatic vessel is a prerequisite for hepatic diseases diagnosis and surgery planning. For liver surgery planning, it is crucial to provide the surgeon with a patient-individual three-dimensional representation of the liver along with its vasculature and lesions. The representation allows an exploration of the vascular anatomy and the measurement of vessel diameters, following by intra-patient registration, as well as the analysis of the shape and volume of vascular territories. In this paper, we present an approach for generation of hepatic vessel graph based on centerline extraction and junction detection. The proposed approach involves the following concepts and methods: 1) Flux driven automatic centerline extraction; 2) Junction detection on the centerline using hollow sphere filtering; 3) Graph representation of hepatic vessel based on the centerline and junction. The approach is evaluated on contrast-enhanced liver CT datasets to demonstrate its availability and effectiveness.

  4. NCSX Vacuum Vessel Fabrication

    SciTech Connect

    Viola, M. E.; Brown, T.; Heitzenroeder, P.; Malinowski, F.; Reiersen, W.; Sutton, L.; Goranson, P.; Nelson, B.; Cole, M.; Manuel, M.; McCorkle, D.

    2005-10-07

    The National Compact Stellarator Experiment (NCSX) is being constructed at the Princeton Plasma Physics Laboratory (PPPL) in conjunction with the Oak Ridge National Laboratory (ORNL). The goal of this experiment is to develop a device which has the steady state properties of a traditional stellarator along with the high performance characteristics of a tokamak. A key element of this device is its highly shaped Inconel 625 vacuum vessel. This paper describes the manufacturing of the vessel. The vessel is being fabricated by Major Tool and Machine, Inc. (MTM) in three identical 120º vessel segments, corresponding to the three NCSX field periods, in order to accommodate assembly of the device. The port extensions are welded on, leak checked, cut off within 1" of the vessel surface at MTM and then reattached at PPPL, to accommodate assembly of the close-fitting modular coils that surround the vessel. The 120º vessel segments are formed by welding two 60º segments together. Each 60º segment is fabricated by welding ten press-formed panels together over a collapsible welding fixture which is needed to precisely position the panels. The vessel is joined at assembly by welding via custom machined 8" (20.3 cm) wide spacer "spool pieces." The vessel must have a total leak rate less than 5 X 10-6 t-l/s, magnetic permeability less than 1.02μ, and its contours must be within 0.188" (4.76 mm). It is scheduled for completion in January 2006.

  5. Optimal Elasticity cut-off value for discriminating Healthy to Pathological Fibrotic patients employing Fuzzy C-Means automatic segmentation in Liver Shear Wave Elastography images

    NASA Astrophysics Data System (ADS)

    Gatos, Ilias; Tsantis, Stavros; Skouroliakou, Aikaterini; Theotokas, Ioannis; Zoumpoulis, Pavlos S.; Kagadis, George C.

    2015-09-01

    The aim of the present study is to determine an optimal elasticity cut-off value for discriminating Healthy from Pathological fibrotic patients by means of Fuzzy C-Means automatic segmentation and maximum participation cluster mean value employment in Shear Wave Elastography (SWE) images. The clinical dataset comprised 32 subjects (16 Healthy and 16 histological or Fibroscan verified Chronic Liver Disease). An experienced Radiologist performed SWE measurement placing a region of interest (ROI) on each subject's right liver lobe providing a SWE image for each patient. Subsequently Fuzzy C-Means clustering was performed on every SWE image utilizing 5 clusters. Mean Stiffness value and pixels number of each cluster were calculated. The mean stiffness value feature of the cluster with maximum pixels number was then fed as input for ROC analysis. The selected Mean Stiffness value feature an Area Under the Curve (AUC) of 0.8633 with Optimum Cut-off value of 7.5 kPa with sensitivity and specificity values of 0.8438 and 0.875 and balanced accuracy of 0.8594. Examiner's classification measurements exhibited sensitivity, specificity and balanced accuracy value of 0.8125 with 7.1 kPa cutoff value. A new promising automatic algorithm was implemented with more objective criteria of defining optimum elasticity cut-off values for discriminating fibrosis stages for SWE. More subjects are needed in order to define if this algorithm is an objective tool to outperform manual ROI selection.

  6. Hepatic lesions segmentation in ultrasound nonlinear imaging

    NASA Astrophysics Data System (ADS)

    Kissi, Adelaide A.; Cormier, Stephane; Pourcelot, Leandre; Tranquart, Francois

    2005-04-01

    Doppler has been used for many years for cardiovascular exploration in order to visualize the vessels walls and anatomical or functional diseases. The use of ultrasound contrast agents makes it possible to improve ultrasonic information. Nonlinear ultrasound imaging highlights the detection of these agents within an organ and hence is a powerful technique to image perfusion of an organ in real-time. The visualization of flow and perfusion provides important information for the diagnosis of various diseases as well as for the detection of tumors. However, the images are buried in noise, the speckle, inherent in the image formation. Furthermore at portal phase, there is often an absence of clear contrast between lesions and surrounding tissues because the organ is filled with agents. In this context, we propose a new method of automatic liver lesions segmentation in nonlinear imaging sequences for the quantification of perfusion. Our method of segmentation is divided into two stages. Initially, we developed an anisotropic diffusion step which raised the structural characteristics to eliminate the speckle. Then, a fuzzy competitive clustering process allowed us to delineate liver lesions. This method has been used to detect focal hepatic lesions (metastasis, nodular hyperplasia, adenoma). Compared to medical expert"s report obtained on 15 varied lesions, the automatic segmentation allows us to identify and delineate focal liver lesions during the portal phase which high accuracy. Our results show that this method improves markedly the recognition of focal hepatic lesions and opens the way for future precise quantification of contrast enhancement.

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

    PubMed

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

    2010-07-01

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

  8. Automated 3D vascular segmentation in CT hepatic venography

    NASA Astrophysics Data System (ADS)

    Fetita, Catalin; Lucidarme, Olivier; Preteux, Francoise

    2005-08-01

    In the framework of preoperative evaluation of the hepatic venous anatomy in living-donor liver transplantation or oncologic rejections, this paper proposes an automated approach for the 3D segmentation of the liver vascular structure from 3D CT hepatic venography data. The developed segmentation approach takes into account the specificities of anatomical structures in terms of spatial location, connectivity and morphometric properties. It implements basic and advanced morphological operators (closing, geodesic dilation, gray-level reconstruction, sup-constrained connection cost) in mono- and multi-resolution filtering schemes in order to achieve an automated 3D reconstruction of the opacified hepatic vessels. A thorough investigation of the venous anatomy including morphometric parameter estimation is then possible via computer-vision 3D rendering, interaction and navigation capabilities.

  9. Image processing of liver computed tomography angiographic (CTA) images for laser induced thermotherapy (LITT) planning

    NASA Astrophysics Data System (ADS)

    Li, Yue; Gao, Xiang; Tang, Qingyu; Gao, Shangkai

    2012-02-01

    Analysis of patient images is highly desired for simulating and planning the laser-induced thermotherapy (LITT) to study the cooling effect of big vessels around tumors during the procedure. In this paper, we present an image processing solution for simulating and planning LITT on liver cancer using computed tomography angiography (CTA) images. This includes first performing a 3D anisotropic filtering on the data to remove noise. The liver region is then segmented with a level sets based contour tracking method. A 3D level sets based surface evolution driven by boundary statistics is then used to segment the surfaces of vessels and tumors. Then the medial lines of vessels were extracted by a thinning algorithm. Finally the vessel tree is found on the thinning result, by first constructing a shortest path spanning tree by Dijkstra algorithm and then pruning the unnecessary branches. From the segmentation and vessel skeletonization results, important geometric parameters of the vessels and tumors are calculated for simulation and surgery planning. The proposed methods was applied to a patient's image and the result is shown.

  10. Pressure vessel flex joint

    NASA Technical Reports Server (NTRS)

    Kahn, Jon B. (Inventor)

    1992-01-01

    An airtight, flexible joint is disclosed for the interfacing of two pressure vessels such as between the Space Station docking tunnel and the Space Shuttle Orbiter bulkhead adapter. The joint provides for flexibility while still retaining a structural link between the two vessels required due to the loading created by the internal/external pressure differential. The joint design provides for limiting the axial load carried across the joint to a specific value, a function returned in the Orbiter/Station tunnel interface. The flex joint comprises a floating structural segment which is permanently attached to one of the pressure vessels through the use of an inflatable seal. The geometric configuration of the joint causes the tension between the vessels created by the internal gas pressure to compress the inflatable seal. The inflation pressure of the seal is kept at a value above the internal/external pressure differential of the vessels in order to maintain a controlled distance between the floating segment and pressure vessel. The inflatable seal consists of either a hollow torus-shaped flexible bladder or two rolling convoluted diaphragm seals which may be reinforced by a system of straps or fabric anchored to the hard structures. The joint acts as a flexible link to allow both angular motion and lateral displacement while it still contains the internal pressure and holds the axial tension between the vessels.

  11. Vessel enhancing diffusion: a scale space representation of vessel structures.

    PubMed

    Manniesing, Rashindra; Viergever, Max A; Niessen, Wiro J

    2006-12-01

    A method is proposed to enhance vascular structures within the framework of scale space theory. We combine a smooth vessel filter which is based on a geometrical analysis of the Hessian's eigensystem, with a non-linear anisotropic diffusion scheme. The amount and orientation of diffusion depend on the local vessel likeliness. Vessel enhancing diffusion (VED) is applied to patient and phantom data and compared to linear, regularized Perona-Malik, edge and coherence enhancing diffusion. The method performs better than most of the existing techniques in visualizing vessels with varying radii and in enhancing vessel appearance. A diameter study on phantom data shows that VED least affects the accuracy of diameter measurements. It is shown that using VED as a preprocessing step improves level set based segmentation of the cerebral vasculature, in particular segmentation of the smaller vessels of the vasculature. PMID:16876462

  12. Timing of Staged Percutaneous Coronary Intervention for a Non-Culprit Lesion in Patients With Anterior Wall ST Segment Elevation Myocardial Infarction With Multiple Vessel Disease.

    PubMed

    Lee, Wei-Chieh; Wu, Bo-Jui; Fang, Chih-Yuan; Chen, Chien-Jen; Yang, Cheng-Hsu; Yip, Hon-Kan; Hang, Chi-Ling; Wu, Chiung-Jen; Fang, Hsiu-Yu

    2016-07-27

    The optimal timing of a staged percutaneous coronary intervention (PCI) for non-culprit lesions in patients with STsegment elevation myocardial infarction (STEMI) patients with multi-vessel disease (MVD) remains controversial. We focused on patients with anterior wall STEMI with MVD and determined the clinical effects for timing of staged PCI.From November 2005 to December 2014, 258 patients were diagnosed with anterior wall STEMI with MVD in our hospital. Among them, 37 patients received staged PCI within 3 weeks, 50 patients received staged PCI during 3 weeks to one year, and 167 patients received only primary PCI for culprit lesions. Clinical outcomes such as admission for angina or heart failure, target vessel revascularization, myocardial infarction, stroke, cardiovascular mortality, and allcause mortality were compared among the 3 groups.Acute kidney injury (AKI) after PCI occurred in 18.9% of the 3-week group, 0% of the one-year group, and 7.6% of the control group (P = 0.005). Of the one-year and 3-year clinical outcomes, the one-year group had better results, such as fewer major adverse cardiac cerebral events (P = 0.028, P = 0.023), and lower recurrent MI (P = 0.065; P = 0.018), cardiovascular mortality (P = 0.043; P = 0.020), and all-cause mortality (P = 0.047; P = 0.005).In patients with anterior wall STEMI with MVD, staged PCI for a non-culprit lesion over 3 weeks to one year had a better clinical outcome. Staged PCI for a non-culprit lesion within 3 weeks may be related to the occurrence of AKI, may lead to worse clinical outcomes, and did not decrease the occurrence of angina or post-MI heart failure. PMID:27357434

  13. A Geophysical Investigation of the Offshore Portion of the Northern Segment of the San Andreas Fault on a "green research vessel"

    NASA Astrophysics Data System (ADS)

    Beeson, J. W.; Goldfinger, C.; Johnson, S. Y.; Wakefield, W. W.; Clarke, M. E.

    2011-12-01

    faults is yet unclear. The principle stress axis of the folding/faulting west of the NSAF is consistent with deformation and uplift observed southwest of the Mendocino triple junction Geophysical data collection, 20 days of multibeam and seismic survey, were conducted using the R/V Baylis, a 65' sailing research vessel owned by Sealife Conservation Society, Santa Cruz, CA. In addition, the R/V Pacific Storm, an 86' converted fishing vessel, was used for Autonomous Underwater Vehicle (AUV) dives to gather video imagery of the NSAF. It was not only our goal to study the offshore portion of the NSAF but it was an opportunity to conduct research in an efficient manner. During the entire cruise, mobilization, data collection and demobilization, fuel consumption was recorded. The Baylis averaged 1.6 gallons of fuel per hour (g/hr) while the Pacific Storm consumed 12.9 g/hr. Total fuel consumption for the entire cruise was ~4900 gallons (Baylis, 681 gal, Pacific Storm, 3096 gal). For comparison, a similar cruise conducted on an intermediate class ship, i.e. OSU's Wecoma, would consume 30,000-40,000 gallons of fuel.

  14. Effects of AMI-25 on liver vessels and tumors on T1-weighted turbo-field-echo images: implications for tumor characterization.

    PubMed

    van Gansbeke, D; Metens, T M; Matos, C; Nicaise, N; Gay, F; Raeymaekers, H; Struyven, J

    1997-01-01

    This study was devoted to tumor differentiation in liver MR T1-weighted imaging with superparamagnetic iron oxide (SPIO). Twenty-one patients with 40 liver lesions were studied at 1.5 T. Before and at least 45 minutes after SPIO administration, turbo-field-echo (TFE) T1-weighted, TFE T1 x T2*-weighted (MXT), and fat-suppressed turbo-spin-echo T2-weighted images were acquired. A quantitative analysis was performed blindly. On TFE T1-weighted images, the signal enhancement was -33% +/- 12 for the liver, -24% +/- 2 for adenomas and focal nodular hyperplasia, +60% +/- 33 for the hemangiomas; metastases and cyst enhancement were not significant. After SPIO on TFE T1-weighted images, the hemangioma-to-liver signal ratio (149% +/- 18) was definitely higher than the mean metastasis-to-liver signal ratio (90% +/- 16). This T1-related differentiation ability lacked dramatically on TFE MXT images and, in one case, was reduced on post-SPIO TFE T1-weighted images by a long imaging delay after SPIO administration (2 hours). PMID:9170031

  15. Liver metastases

    MedlinePlus

    Metastases to the liver; Metastatic liver cancer; Liver cancer - metastatic; Colorectal cancer - liver metastases; Colon cancer - liver metastases; Esophageal cancer - liver metastases; Lung cancer - liver metastases; Melanoma - liver metastases

  16. Blood Vessel Tension Tester

    NASA Technical Reports Server (NTRS)

    1978-01-01

    In the photo, a medical researcher is using a specially designed laboratory apparatus for measuring blood vessel tension. It was designed by Langley Research Center as a service to researchers of Norfolk General Hospital and Eastern Virginia Medical School, Norfolk, Virginia. The investigators are studying how vascular smooth muscle-muscle in the walls of blood vessels-reacts to various stimulants, such as coffee, tea, alcohol or drugs. They sought help from Langley Research Center in devising a method of measuring the tension in blood vessel segments subjected to various stimuli. The task was complicated by the extremely small size of the specimens to be tested, blood vessel "loops" resembling small rubber bands, some only half a millimeter in diameter. Langley's Instrumentation Development Section responded with a miniaturized system whose key components are a "micropositioner" for stretching a length of blood vessel and a strain gage for measuring the smooth muscle tension developed. The micropositioner is a two-pronged holder. The loop of Mood vessel is hooked over the prongs and it is stretched by increasing the distance between the prongs in minute increments, fractions of a millimeter. At each increase, the tension developed is carefully measured. In some experiments, the holder and specimen are lowered into the test tubes shown, which contain a saline solution simulating body fluid; the effect of the compound on developed tension is then measured. The device has functioned well and the investigators say it has saved several months research time.

  17. [Liver intervention].

    PubMed

    Oi, H

    2000-12-01

    Interventional radiology is now widely performed for the treatment of liver tumors, because surgery is sometimes limited by poor liver function. Transcatheter arterial chemoembolization(TACE) is an effective therapy for hepatocellular carcinoma. Lipiodol TACE shows a strong antitumor effect because of the overflow of excess iodized oil into the portal veins, and segmental TACE is recommended to avoid deteriorating liver function. Selective CT arteriography is performed in order to decide on the treatment area, and TACE under CT guidance leads to effective results in terms of dense accumulation of the chemotherapeutic drug in the individual tumors that are affected by the ischemic state and anticancer drugs. Percutaneous microwave or radiofrequency coagulation therapy is adequate for a few of the hypovascular tumors. Excessive coagulation through the needle tract is indispensable in these therapies, and precisely designed puncture is necessary to minimize damage to the liver parenchyma. Selective chemotherapy to the tumor-bearing organ is the first step in a number of liver tumors. Continuous intra-arterial infusion chemotherapy is performed for multiple liver metastases. The reservoir implantation technique is percutaneously achieved via the left subclavian artery under ultrasound guidance, without the exposure of an artery in the incision method, which can induce thrombus formation. PMID:11197832

  18. Hepatic Arterial Configuration in Relation to the Segmental Anatomy of the Liver; Observations on MDCT and DSA Relevant to Radioembolization Treatment

    SciTech Connect

    Hoven, Andor F. van den Leeuwen, Maarten S. van Lam, Marnix G. E. H. Bosch, Maurice A. A. J. van den

    2015-02-15

    PurposeCurrent anatomical classifications do not include all variants relevant for radioembolization (RE). The purpose of this study was to assess the individual hepatic arterial configuration and segmental vascularization pattern and to develop an individualized RE treatment strategy based on an extended classification.MethodsThe hepatic vascular anatomy was assessed on MDCT and DSA in patients who received a workup for RE between February 2009 and November 2012. Reconstructed MDCT studies were assessed to determine the hepatic arterial configuration (origin of every hepatic arterial branch, branching pattern and anatomical course) and the hepatic segmental vascularization territory of all branches. Aberrant hepatic arteries were defined as hepatic arterial branches that did not originate from the celiac axis/CHA/PHA. Early branching patterns were defined as hepatic arterial branches originating from the celiac axis/CHA.ResultsThe hepatic arterial configuration and segmental vascularization pattern could be assessed in 110 of 133 patients. In 59 patients (54 %), no aberrant hepatic arteries or early branching was observed. Fourteen patients without aberrant hepatic arteries (13 %) had an early branching pattern. In the 37 patients (34 %) with aberrant hepatic arteries, five also had an early branching pattern. Sixteen different hepatic arterial segmental vascularization patterns were identified and described, differing by the presence of aberrant hepatic arteries, their respective vascular territory, and origin of the artery vascularizing segment four.ConclusionsThe hepatic arterial configuration and segmental vascularization pattern show marked individual variability beyond well-known classifications of anatomical variants. We developed an individualized RE treatment strategy based on an extended anatomical classification.

  19. [Pulmonary blood vessels in goats].

    PubMed

    Roos, H; Hegner, K; Vollmerhaus, B

    1999-05-01

    The blood vessels in the lung of the goat, which until now have received little attention, are described in detail for the first time. With regard to the segments of the lung, blood vessels are bronchovascular units in the lobi craniales, lobus medius and lobus accessorius, but bronchoartery units in the lobi caudales. We investigated the types of branches of the Aa. pulmonales dextra et sinistra, the inter- and intraspecific principles of the outlet of the pulmonary veins and the importance of bronchopulmonary segmentation of the lungs. PMID:10386009

  20. Salvage living-donor liver transplantation for liver failure following definitive radiation therapy for recurrent hepatocellular carcinoma: a case report.

    PubMed

    Kitajima, T; Fujimoto, Y; Hatano, E; Nishida, H; Ogawa, K; Mori, A; Okajima, H; Kaido, T; Nakamura, A; Nagamatsu, H; Uemoto, S

    2015-04-01

    A 57-year-old man with a history of hepatitis B virus infection was referred to our hospital for living-donor liver transplantation (LDLT). Five years earlier, right lobectomy had been performed for solitary hepatocellular carcinoma (HCC) with bile duct tumor thrombus in segments 5 and 6 in the liver. Two years later, transarterial chemoembolization and radiofrequency ablation were performed for recurrent HCC. Two years after those local therapies, another recurrent HCC was treated with transhepatic arterial infusion chemotherapy with cisplatin and conventional radiation therapy (RT) with 60 Gy in 20 fractions, because the tumor was contiguous to the trunk of the portal vein. After the completion of RT, symptoms due to liver failure and severe infection caused by multiple liver abscesses developed despite the administration of antibiotics and percutaneous transhepatic cholangiodrainage. Therefore, LDLT was performed with the use of a right lobe graft donated by his wife. Vascular anastomosis was successfully performed with the use of normal procedures. The patient recovered uneventfully, and has since been doing well for 34 months, with no evidence of vascular complications. However, the degree of injury to the anastomotic vessels caused by definitive RT before LDLT remains unclear, whereas the safety and efficacy of some forms of RT as a bridge to deceased-donor LT have been reported. Salvage LDLT is effective for patients with liver failure after multidisciplinary treatment including radiation, while carefully taking radiation-induced vessel injury as a potential late complication into consideration, especially in LDLT cases. PMID:25891735

  1. Hepatectomy After Yttrium-90 (Y90) Radioembolization-Induced Liver Fibrosis.

    PubMed

    Maker, Ajay V; August, Carey; Maker, Vijay K; Weisenberg, Elliot

    2016-04-01

    An obese 55-year-old woman with nonalcoholic fatty liver disease presented 7 years after resection of a T3N1 ileal carcinoid tumor with an elevated chromogranin A, multifocal metastatic disease to the liver, and carcinoid syndrome. She underwent right hepatic artery yttrium-90 (Y90) radioembolization, followed a month later by selective Y90 treatment to segment IV. She then presented to our clinic 10 months later, remaining symptomatic with flushing, diarrhea, anxiety, myalgia, pain, and persistent night sweats despite Sandostatin administration. At least 11 tumors were identified in the right lobe of the liver and three in segment IV on liver-specific imaging. These lesions were stable over a year with no new lesions. At exploration, there was marked hypertrophy of the left lateral segment due to the yttrium-90 treatment of segments IV-VIII, corresponding with preoperative volumetrics predicting a functional liver remnant (FLR) of 40% after extended right hepatectomy. The right lobe and segment IV were fibrotic, hard, and visibly damaged. The gland had a thick, fibrotic capsule, and the parenchyma was dense, inflexible, and difficult to dissect, consistent with the previously reported morbidity of these operations. Extended right hepatectomy was performed. Final pathology demonstrated 15 foci of metastatic well-differentiated neuroendocrine carcinoma that were negative for necrosis, as was expected given her continued symptoms despite radioembolization. Numerous amorphous spheres, frequently in clusters, were present in segments IV-VIII in vessels and approximating tumors consistent with prior Y90 radioembolization. The patient had an uneventful post-operative recovery and remains symptom free on follow-up. Treatment options for metastatic tumors to the liver have increased in recent years and currently include radioembolization in selected patients. Surgical cytoreduction and complete metastasectomy continue to offer improvement in symptoms, quality of life, and

  2. Apoptosis regulates endothelial cell number and capillary vessel diameter but not vessel regression during retinal angiogenesis.

    PubMed

    Watson, Emma C; Koenig, Monica N; Grant, Zoe L; Whitehead, Lachlan; Trounson, Evelyn; Dewson, Grant; Coultas, Leigh

    2016-08-15

    The growth of hierarchical blood vessel networks occurs by angiogenesis. During this process, new vessel growth is accompanied by the removal of redundant vessel segments by selective vessel regression ('pruning') and a reduction in endothelial cell (EC) density in order to establish an efficient, hierarchical network. EC apoptosis has long been recognised for its association with angiogenesis, but its contribution to this process has remained unclear. We generated mice in which EC apoptosis was blocked by tissue-specific deletion of the apoptosis effector proteins BAK and BAX. Using the retina as a model, we found that apoptosis made a minor contribution to the efficiency of capillary regression around arteries where apoptosis was most concentrated, but was otherwise dispensable for vessel pruning. Instead, apoptosis was necessary for the removal of non-perfused vessel segments and the reduction in EC density that occurs during vessel maturation. In the absence of apoptosis, increased EC density resulted in an increase in the diameter of capillaries, but not arteries or veins. Our findings show that apoptosis does not influence the number of vessels generated during angiogenesis. Rather it removes non-perfused vessel segments and regulates EC number during vessel maturation, which has vessel-specific consequences for vessel diameter. PMID:27471260

  3. Construction of realistic liver phantoms from patient images using 3D printer and its application in CT image quality assessment

    NASA Astrophysics Data System (ADS)

    Leng, Shuai; Yu, Lifeng; Vrieze, Thomas; Kuhlmann, Joel; Chen, Baiyu; McCollough, Cynthia H.

    2015-03-01

    The purpose of this study is to use 3D printing techniques to construct a realistic liver phantom with heterogeneous background and anatomic structures from patient CT images, and to use the phantom to assess image quality with filtered back-projection and iterative reconstruction algorithms. Patient CT images were segmented into liver tissues, contrast-enhanced vessels, and liver lesions using commercial software, based on which stereolithography (STL) files were created and sent to a commercial 3D printer. A 3D liver phantom was printed after assigning different printing materials to each object to simulate appropriate attenuation of each segmented object. As high opacity materials are not available for the printer, we printed hollow vessels and filled them with iodine solutions of adjusted concentration to represent enhance levels in contrast-enhanced liver scans. The printed phantom was then placed in a 35×26 cm oblong-shaped water phantom and scanned repeatedly at 4 dose levels. Images were reconstructed using standard filtered back-projection and an iterative reconstruction algorithm with 3 different strength settings. Heterogeneous liver background were observed from the CT images and the difference in CT numbers between lesions and background were representative for low contrast lesions in liver CT studies. CT numbers in vessels filled with iodine solutions represented the enhancement of liver arteries and veins. Images were run through a Channelized Hotelling model observer with Garbor channels and ROC analysis was performed. The AUC values showed performance improvement using the iterative reconstruction algorithm and the amount of improvement increased with strength setting.

  4. Robotic suture of a large caval injury caused by endo-GIA stapler malfunction during laparoscopic wedge resection of liver segments VII and VIII en-bloc with the right hepatic vein.

    PubMed

    Boggi, Ugo; Moretto, Carlo; Vistoli, Fabio; D'Imporzano, Simone; Mosca, Franco

    2009-01-01

    Primary endo-GIA stapler malfunction occurred during robotic wedge resection of liver segments VII and VIII en-bloc with the right hepatic vein, in an obese woman diagnosed with single liver metastasis from a previous carcinoid tumour. Haemorrhage was soon controlled by clamping the vena cava below the injury using two wristed forceps angled at 90 degrees . With the two instruments locked in the holding position the ensuing operative strategy was discussed between surgeon and anaesthesia teams. Using the third robotic arm the caval injury was repaired laparoscopically with interrupted polypropylene sutures. The patient was transfused with two units of packed red blood cells, recovered uneventfully, and was discharged on post-operative day five. We conclude that even the most advanced technologies can fail and that surgeons should be fully aware of the consequences of these malfunctions and be prepared for repair. From this point of view, the da Vinci surgical system seems to have some advantages over classical laparoscopic methods including the ability to lock the wristed instruments in the holding position, the use of three arms by the same operating surgeon, and the extreme facilitation of intracorporeal suturing and knot-tying in deep and narrow spaces, extremely difficult if not impossible with conventional laparoscopic instruments. PMID:19707931

  5. Probabilistic atlas based labeling of the cerebral vessel tree

    NASA Astrophysics Data System (ADS)

    Van de Giessen, Martijn; Janssen, Jasper P.; Brouwer, Patrick A.; Reiber, Johan H. C.; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

    2015-03-01

    Preoperative imaging of the cerebral vessel tree is essential for planning therapy on intracranial stenoses and aneurysms. Usually, a magnetic resonance angiography (MRA) or computed tomography angiography (CTA) is acquired from which the cerebral vessel tree is segmented. Accurate analysis is helped by the labeling of the cerebral vessels, but labeling is non-trivial due to anatomical topological variability and missing branches due to acquisition issues. In recent literature, labeling the cerebral vasculature around the Circle of Willis has mainly been approached as a graph-based problem. The most successful method, however, requires the definition of all possible permutations of missing vessels, which limits application to subsets of the tree and ignores spatial information about the vessel locations. This research aims to perform labeling using probabilistic atlases that model spatial vessel and label likelihoods. A cerebral vessel tree is aligned to a probabilistic atlas and subsequently each vessel is labeled by computing the maximum label likelihood per segment from label-specific atlases. The proposed method was validated on 25 segmented cerebral vessel trees. Labeling accuracies were close to 100% for large vessels, but dropped to 50-60% for small vessels that were only present in less than 50% of the set. With this work we showed that using solely spatial information of the vessel labels, vessel segments from stable vessels (>50% presence) were reliably classified. This spatial information will form the basis for a future labeling strategy with a very loose topological model.

  6. Robotic liver surgery: preliminary experience in a tertiary hepato-biliary unit.

    PubMed

    Felli, Emanuele; Santoro, Roberto; Colasanti, Marco; Vennarecci, Giovanni; Lepiane, Pasquale; Ettorre, Giuseppe M

    2015-03-01

    Minimally invasive liver surgery is performed with increasing frequency by hepatic surgeons. Laparoscopy was the first approach to be used and it is currently safely feasible in selected patients by experienced surgeons. Minor and major laparoscopic hepatectomies are now performed as a routine procedure in tertiary referral centers, with increasing evidence of long-term results comparable to traditional surgery together with the advantages of a minimally invasive approach. Robotic surgery, first developed for military purposes, showed to overcome some of the limits of laparoscopy, with an improved visual magnification, a 3-dimensional view and enhanced dexterity with better movement control. This allows an easier approach for resections in the posterior segments and for lesions close to major vessels. We present our preliminary experience of 20 consecutive robotic liver resection. Indications were colo-rectal liver metastasis (n = 7), hepatocellular carcinoma (n = 6), liver hemangioma (n = 2), biliary cystoadenoma (n = 2), breast cancer liver metastasis (n = 1), lung cancer liver metastasis (n = 1), symptomatic left liver lithiasis (n = 1). No conversion to laparotomy have been made and no hepatic pedicle clamping has been performed. The median duration of surgery was 141 min. There was no mortality, global morbidity was 10%. Median tumor size was 36 mm. Median post-operative length of stay was 5.7 days. Robotic surgery can be safely performed by experienced hepatic surgeons, resections of lesions in the posterior segments and close to the major vessels seem to be the best indication. Further studies are needed to clarify the exact role of robotics in liver surgery. PMID:25750057

  7. Blood vessel uptake and metabolism of organic nitrates in the rat.

    PubMed

    Fung, H L; Sutton, S C; Kamiya, A

    1984-02-01

    Recent reports have suggested that the unusual pharmacokinetics observed for nitroglycerin (NTG) and isosorbide dinitrate (ISDN) may be partially explained by extensive uptake and/or metabolism of these drugs by vascular and other extrahepatic tissues. Using the rat as an animal model, this hypothesis was examined by in vivo intravessel NTG and [14C]ISDN infusion and injection into various vessel segments, viz. the femoral vein, inferior vena cava [IVC: lower, middle and upper) and the aorta. NTG and [14C]ISDN concentrations were determined in these blood vessels and in plasma. Blood vessel segments nearest the input site had the greatest amounts of nitrate, whereas segments further away from the input site had progressively less nitrate, with the exception of aorta, which appeared to take up NTG less extensively, on a per weight of vessel basis, than the IVC. Blood vessel NTG concentrations (nanogram per gram) were generally higher (10-fold) and declined about twice as slowly as NTG plasma concentrations (nanograms per milliliter). [14C]NTG and [14C]ISDN were also incubated with cofactors in IVC, aorta, abdominal muscle, lung and liver. The amounts of nitrate metabolites formed from parent drug were larger in each extrahepatic tissue incubation than in the controls (P less than .05). The results are consistent with the hypothesis that vascular and other extrahepatic tissues can take up and/or metabolize organic nitrates. The data appear to provide a partial explanation for the large systemic clearance seen with nitrates and appear consistent with existing mechanistic hypotheses for the vascular action of these compounds. PMID:6420543

  8. Segmental neurofibromatosis.

    PubMed

    Galhotra, Virat; Sheikh, Soheyl; Jindal, Sanjeev; Singla, Anshu

    2014-07-01

    Segmental neurofibromatosis is a rare disorder, characterized by neurofibromas or cafι-au-lait macules limited to one region of the body. Its occurrence on the face is extremely rare and only few cases of segmental neurofibromatosis over the face have been described so far. We present a case of segmental neurofibromatosis involving the buccal mucosa, tongue, cheek, ear, and neck on the right side of the face. PMID:25565748

  9. Segmental neurofibromatosis.

    PubMed

    Toy, Brian

    2003-10-01

    Segmental neurofibromatosis is a rare variant of neurofibromatosis in which skin lesions are confined to a circumscribed body segment. A case of a 72-year-old woman with this condition is presented. Clinical features and genetic evidence are reviewed. PMID:14594599

  10. Active Segmentation

    PubMed Central

    Mishra, Ajay; Aloimonos, Yiannis

    2009-01-01

    The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary. We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach. PMID:20686671

  11. Liver Cancer

    MedlinePlus

    ... body digest food, store energy, and remove poisons. Primary liver cancer starts in the liver. Metastatic liver ... and spreads to your liver. Risk factors for primary liver cancer include Having hepatitis B or C ...

  12. Liver scan

    MedlinePlus

    ... hyperplasia or adenoma of the liver Abscess Budd-Chiari syndrome Infection Liver disease (such as cirrhosis or ... Amebic liver abscess Cirrhosis Hepatic vein obstruction (Budd-Chiari) Hepatitis Liver cancer - hepatocellular carcinoma Liver disease Splenic ...

  13. WE-D-18A-05: Construction of Realistic Liver Phantoms From Patient Images and a Commercial 3D Printer

    SciTech Connect

    Leng, S; Vrieze, T; Kuhlmann, J; Yu, L; Matsumoto, J; Morris, J; McCollough, C

    2014-06-15

    Purpose: To assess image quality and radiation dose reduction in abdominal CT imaging, physical phantoms having realistic background textures and lesions are highly desirable. The purpose of this work was to construct a liver phantom with realistic background and lesions using patient CT images and a 3D printer. Methods: Patient CT images containing liver lesions were segmented into liver tissue, contrast-enhanced vessels, and liver lesions using commercial software (Mimics, Materialise, Belgium). Stereolithography (STL) files of each segmented object were created and imported to a 3D printer (Object350 Connex, Stratasys, MN). After test scans were performed to map the eight available printing materials into CT numbers, printing materials were assigned to each object and a physical liver phantom printed. The printed phantom was scanned on a clinical CT scanner and resulting images were compared with the original patient CT images. Results: The eight available materials used to print the liver phantom had CT number ranging from 62 to 117 HU. In scans of the liver phantom, the liver lesions and veins represented in the STL files were all visible. Although the absolute value of the CT number in the background liver material (approx. 85 HU) was higher than in patients (approx. 40 HU), the difference in CT numbers between lesions and background were representative of the low contrast values needed for optimization tasks. Future work will investigate materials with contrast sufficient to emulate contrast-enhanced arteries. Conclusion: Realistic liver phantoms can be constructed from patient CT images using a commercial 3D printer. This technique may provide phantoms able to determine the effect of radiation dose reduction and noise reduction techniques on the ability to detect subtle liver lesions in the context of realistic background textures.

  14. [Liver and artificial liver].

    PubMed

    Chamuleau, R A

    1998-06-01

    Despite good results of orthotopic liver transplantation in patients with fulminant hepatic failure the need still exists for an effective and safe artificial liver, able to temporarily take over the complex liver function so as to bridge the gap with transplantation or regeneration. Attempts to develop non-biological artificial livers have failed, mostly when controlled clinical trials were performed. In the last decade several different types of bioartificial livers have been devised, in which the biocomponent consists of freshly isolated porcine hepatocytes or a human hepatoblastoma cell line. The majority use semipermeable hollow fibers known from artificial kidney devices. The liver cells may lie either inside or outside the lumen of these fibers. In vitro analysis of liver function and animal experimental work showing that the bioartificial liver increases survival justify clinical application. Bioartificial livers are connected to patients extracorporeally by means of plasmapheresis circuit for periods of about 6 hours. In different trials about 40 patients with severe liver failure have been treated. No important adverse effects have not been reported in these phase I trials. Results of controlled studies are urgently needed. As long as no satisfactory immortalised human liver cell line with good function is available, porcine hepatocytes will remain the first choice, provided transmission of porcine pathogens to man is prevented. PMID:9752034

  15. Monitoring of Total and Regional Liver Function after SIRT

    PubMed Central

    Bennink, Roelof J.; Cieslak, Kasia P.; van Delden, Otto M.; van Lienden, Krijn P.; Klümpen, Heinz-Josef; Jansen, Peter L.; van Gulik, Thomas M.

    2014-01-01

    Selective internal radiation therapy (SIRT) is a promising treatment modality for advanced hepatocellular carcinoma or metastatic liver cancer. SIRT is usually well tolerated. However, in most patients, SIRT will result in a (temporary) decreased liver function. Occasionally patients develop radioembolization-induced liver disease (REILD). In case of a high tumor burden of the liver, it could be beneficial to perform SIRT in two sessions enabling the primary untreated liver segments to guarantee liver function until function in the treated segments has recovered or functional hypertrophy has occurred. Clinically used liver function tests provide evidence of only one of the many liver functions, though all of them lack the possibility of assessment of segmental (regional) liver function. Hepatobiliary scintigraphy (HBS) has been validated as a tool to assess total and regional liver function in liver surgery. It is also used to assess segmental liver function before and after portal vein embolization. HBS is considered as a valuable quantitative liver function test enabling assessment of segmental liver function recovery after regional intervention and determination of future remnant liver function. We present two cases in which HBS was used to monitor total and regional liver function in a patient after repeated whole liver SIRT complicated with REILD and a patient treated unilaterally without complications. PMID:24982851

  16. The inhomogeneous distribution of liver function: possible impact on the prediction of post-operative remnant liver function

    PubMed Central

    Nilsson, Henrik; Karlgren, Silja; Blomqvist, Lennart; Jonas, Eduard

    2015-01-01

    Background Previous studies have shown that liver function is inhomogeneously distributed in diseased livers, and this uneven distribution cannot be compensated for if a global liver function test is used for the prediction of post-operative remnant liver function. Dynamic Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) can assess segmental liver function, thus offering the possibility to overcome this problem. Methods In 10 patients with liver cirrhosis and 10 normal volunteers, the contribution of individual liver segments to total liver function and volume was calculated using dynamic Gd-EOB-DTPA-enhanced MRI. Remnant liver function predictions using a segmental method and global assessment were compared for a simulated left hemihepatectomy. For the prediction based on segmental functional MRI assessment, the estimated function of the remnant liver segments was added. Results Global liver function assessment overestimated the remnant liver function in 9 out of 10 patients by as much as 9.3% [median −3.5% (−9.3–3.5%)]. In the normal volunteers there was a slight underestimation of remnant function in 9 out of 10 cases [median 1.07% (−0.7–2.5%)]. Discussion The present study underlines the necessity of a segmental liver function test able to compensate for the non-homogeneous nature of liver function, if the prediction of post-operative remnant liver function is to be improved. PMID:25297934

  17. Segmented combustor

    NASA Technical Reports Server (NTRS)

    Halila, Ely E. (Inventor)

    1994-01-01

    A combustor liner segment includes a panel having four sidewalls forming a rectangular outer perimeter. A plurality of integral supporting lugs are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls. A plurality of integral bosses are disposed substantially perpendicularly to the panel and extend from respective ones of the four sidewalls, with the bosses being shorter than the lugs. In one embodiment, the lugs extend through supporting holes in an annular frame for mounting the liner segments thereto, with the bosses abutting the frame for maintaining a predetermined spacing therefrom.

  18. Liver Facts

    MedlinePlus

    ... Home / Before The Transplant / Organ Facts / Liver Organ Facts Heart Lung Heart/Lung Kidney Pancreas Kidney/Pancreas Liver ... Receiving "the call" About the Operation Heart Lung Heart/Lung Kidney Pancreas Kidney/Pancreas Liver Intestine Liver Facts How the Liver Works The liver is one ...

  19. Preparing the anatomical model for ablation of unresectable liver tumor

    PubMed Central

    2014-01-01

    Introduction Nowadays the best treatment of the primary and secondary hepatic tumor is surgical resection, but only 5–15% of all patient with hepatocellular carcinoma and 20–25% of all patients with liver metastases are indicated for resection. In these cases some kind of ablation and other technique could be used. Aim To present the methodology of preparing the anatomical model for ablation of unresectable liver tumor. Material and methods The presented method is based on abdomen computed tomography (CT) dynamic examination. Three methods of segmentation are used: rolling vector for liver volume, modified Frangi filter for liver vessels, and fuzzy expert system with initial region-of-interest anisotropic filtration for liver metastases. Segmentation results are the input data for creating 3D anatomical models in the form of B-spline curves and surfaces performing the surface global interpolation algorithm. A graphical user interface for presentation and evaluation of models, presented in color against DICOM images in grayscale, is designed and implemented. Results The proposed approach was tested on 20 abdominal CT obtained from the Department of Clinical Radiology of Silesian Medical University. The lack of a “gold standard” provides for the correction of the results. Conclusions Preparation of the anatomical model is one of the important early stages of the use of image-based navigation systems. This process could not take place in a fully automatic manner and verification of the results obtained is performed by the radiologist. Using the above anatomical model in surgical workflow is presented. PMID:25097694

  20. Surface-based registration of liver in ultrasound and CT

    NASA Astrophysics Data System (ADS)

    Dehghan, Ehsan; Lu, Kongkuo; Yan, Pingkun; Tahmasebi, Amir; Xu, Sheng; Wood, Bradford J.; Abi-Jaoudeh, Nadine; Venkatesan, Aradhana; Kruecker, Jochen

    2015-03-01

    Ultrasound imaging is an attractive modality for real-time image-guided interventions. Fusion of US imaging with a diagnostic imaging modality such as CT shows great potential in minimally invasive applications such as liver biopsy and ablation. However, significantly different representation of liver in US and CT turns this image fusion into a challenging task, in particular if some of the CT scans may be obtained without contrast agents. The liver surface, including the diaphragm immediately adjacent to it, typically appears as a hyper-echoic region in the ultrasound image if the proper imaging window and depth setting are used. The liver surface is also well visualized in both contrast and non-contrast CT scans, thus making the diaphragm or liver surface one of the few attractive common features for registration of US and non-contrast CT. We propose a fusion method based on point-to-volume registration of liver surface segmented in CT to a processed electromagnetically (EM) tracked US volume. In this approach, first, the US image is pre-processed in order to enhance the liver surface features. In addition, non-imaging information from the EM-tracking system is used to initialize and constrain the registration process. We tested our algorithm in comparison with a manually corrected vessel-based registration method using 8 pairs of tracked US and contrast CT volumes. The registration method was able to achieve an average deviation of 12.8mm from the ground truth measured as the root mean square Euclidean distance for control points distributed throughout the US volume. Our results show that if the US image acquisition is optimized for imaging of the diaphragm, high registration success rates are achievable.

  1. Optimized Performance of FlightPlan during Chemoembolization for Hepatocellular Carcinoma: Importance of the Proportion of Segmented Tumor Area

    PubMed Central

    Joo, Seung-Moon; Kim, Yong Pyo; Yum, Tae Jun; Eun, Na Lae; Lee, Dahye

    2016-01-01

    Objective To evaluate retrospectively the clinical effectiveness of FlightPlan for Liver (FPFL), an automated tumor-feeding artery detection software in cone-beam CT angiography (CBCTA), in identifying tumor-feeding arteries for the treatment of hepatocellular carcinoma (HCC) using three different segmentation sensitivities. Materials and Methods The study included 50 patients with 80 HCC nodules who received transarterial chemoembolization. Standard digital subtracted angiography (DSA) and CBCTA were systematically performed and analyzed. Three settings of the FPFL software for vascular tree segmentation were tested for each tumor: the default, Group D; adjusting the proportion of segmented tumor area between 30 to 50%, Group L; and between 50 to 80%, Group H. Results In total, 109 feeder vessels supplying 80 HCC nodules were identified. The negative predictive value of DSA, FPFL in groups D, L, and H was 56.8%, 87.7%, 94.2%, 98.5%, respectively. The accuracy of DSA, FPFL in groups D, L, and H was 62.6%, 86.8%, 93.4%, 95.6%, respectively. The sensitivity, negative predictive value (NPV), and accuracy of FPFL were higher in Group H than in Group D (p = 0.041, 0.034, 0.005). All three segmentation sensitivity groups showed higher specificity, positive predictive value, NPV, and accuracy of FPFL, as compared to DSA. Conclusion FlightPlan for Liver is a valuable tool for increasing detection of HCC tumor feeding vessels, as compared to standard DSA analysis, particularly in small HCC. Manual adjustment of segmentation sensitivity improves the accuracy of FPFL. PMID:27587967

  2. Fusobacterium Liver Abscess

    PubMed Central

    Buelow, Ben D.; Lambert, Joelle M.; Gill, Ryan M.

    2013-01-01

    Fusobacterium is well characterized as an oropharyngeal pathogen that may induce a septic thrombophlebitis by direct extension of abscess into an adjacent neck vessel (Lemierre's syndrome); its potential for visceral abscess formation, however, remains under-recognized. A 65-year-old man with a recent history of multiple rim-enhancing liver lesions presented to the emergency room with fever and abdominal pain. Based on interval increase in the size of the lesions, abscess was suspected. A liver biopsy was performed, and although no organism could be identified on routine microscopy, Warthin-Starry stain revealed Gram-negative bacilli consistent with an anaerobic Fusobacterium species as the underlying etiology of liver abscess formation. Subsequent anaerobic culture results confirmed the diagnosis. This case highlights the importance of consideration for Fusobacterium infection in the setting of liver abscess if anaerobic organisms have not yet been excluded on initial culture evaluation. PMID:24348321

  3. Fusobacterium liver abscess.

    PubMed

    Buelow, Ben D; Lambert, Joelle M; Gill, Ryan M

    2013-01-01

    Fusobacterium is well characterized as an oropharyngeal pathogen that may induce a septic thrombophlebitis by direct extension of abscess into an adjacent neck vessel (Lemierre's syndrome); its potential for visceral abscess formation, however, remains under-recognized. A 65-year-old man with a recent history of multiple rim-enhancing liver lesions presented to the emergency room with fever and abdominal pain. Based on interval increase in the size of the lesions, abscess was suspected. A liver biopsy was performed, and although no organism could be identified on routine microscopy, Warthin-Starry stain revealed Gram-negative bacilli consistent with an anaerobic Fusobacterium species as the underlying etiology of liver abscess formation. Subsequent anaerobic culture results confirmed the diagnosis. This case highlights the importance of consideration for Fusobacterium infection in the setting of liver abscess if anaerobic organisms have not yet been excluded on initial culture evaluation. PMID:24348321

  4. Managing synchronous liver metastases from colorectal cancer: a multidisciplinary international consensus.

    PubMed

    Adam, René; de Gramont, Aimery; Figueras, Joan; Kokudo, Norihiro; Kunstlinger, Francis; Loyer, Evelyne; Poston, Graeme; Rougier, Philippe; Rubbia-Brandt, Laura; Sobrero, Alberto; Teh, Catherine; Tejpar, Sabine; Van Cutsem, Eric; Vauthey, Jean-Nicolas; Påhlman, Lars

    2015-11-01

    An international panel of multidisciplinary experts convened to develop recommendations for managing patients with colorectal cancer (CRC) and synchronous liver metastases (CRCLM). A modified Delphi method was used. CRCLM is defined as liver metastases detected at or before diagnosis of the primary CRC. Early and late metachronous metastases are defined as those detected ⩽12months and >12months after surgery, respectively. To provide information on potential curability, use of high-quality contrast-enhanced computed tomography (CT) before chemotherapy is recommended. Magnetic resonance imaging is increasingly being used preoperatively to aid detection of subcentimetric metastases, and alongside CT in difficult situations. To evaluate operability, radiology should provide information on: nodule size and number, segmental localization and relationship with major vessels, response after neoadjuvant chemotherapy, non-tumoral liver condition and anticipated remnant liver volume. Pathological evaluation should assess response to preoperative chemotherapy for both the primary tumour and metastases, and provide information on the tumour, margin size and micrometastases. Although the treatment strategy depends on the clinical scenario, the consensus was for chemotherapy before surgery in most cases. When the primary CRC is asymptomatic, liver surgery may be performed first (reverse approach). When CRCLM are unresectable, the goal of preoperative chemotherapy is to downsize tumours to allow resection. Hepatic resection should not be denied to patients with stable disease after optimal chemotherapy, provided an adequate liver remnant with inflow and outflow preservation remains. All patients with synchronous CRCLM should be evaluated by a hepatobiliary multidisciplinary team. PMID:26417845

  5. [Segmental neurofibromatosis].

    PubMed

    Zulaica, A; Peteiro, C; Pereiro, M; Pereiro Ferreiros, M; Quintas, C; Toribio, J

    1989-01-01

    Four cases of segmental neurofibromatosis (SNF) are reported. It is a rare entity considered to be a localized variant of neurofibromatosis (NF)-Riccardi's type V. Two cases are male and two female. The lesions are located to the head in a patient and the other three cases in the trunk. No family history nor transmission to progeny were manifested. The rest of the organs are undamaged. PMID:2502696

  6. Registration-free laparoscope augmentation for intra-operative liver resection planning

    NASA Astrophysics Data System (ADS)

    Feuerstein, Marco; Mussack, Thomas; Heining, Sandro M.; Navab, Nassir

    2007-03-01

    In recent years, an increasing number of liver tumor indications were treated by minimally invasive laparoscopic resection. Besides the restricted view, a major issue in laparoscopic liver resection is the enhanced visualization of (hidden) vessels, which supply the tumorous liver segment and thus need to be divided prior to the resection. To navigate the surgeon to these vessels, pre-operative abdominal imaging data can hardly be used due to intraoperative organ deformations mainly caused by appliance of carbon dioxide pneumoperitoneum and respiratory motion. While regular respiratory motion can be gated and synchronized intra-operatively, motion caused by pneumoperitoneum is individual for every patient and difficult to estimate. Therefore, we propose to use an optically tracked mobile C-arm providing cone-beam CT imaging capability intraoperatively. The C-arm is able to visualize soft tissue by means of its new flat panel detector and is calibrated offline to relate its current position and orientation to the coordinate system of a reconstructed volume. Also the laparoscope is optically tracked and calibrated offline, so both laparoscope and C-arm are registered in the same tracking coordinate system. Intra-operatively, after patient positioning, port placement, and carbon dioxide insufflation, the liver vessels are contrasted and scanned during patient exhalation. Immediately, a three-dimensional volume is reconstructed. Without any further need for patient registration, the volume can be directly augmented on the live laparoscope video, visualizing the contrasted vessels. This augmentation provides the surgeon with advanced visual aid for the localization of veins, arteries, and bile ducts to be divided or sealed.

  7. Liver Wellness

    MedlinePlus

    ... to liver wellness. • There are more than 100 liver diseases. • Liver disease is one of the top 10 causes of ... out of every 10 Americans is affected by liver disease. • Some liver diseases such as hepatitis A, hepatitis ...

  8. SU-E-J-168: Automated Pancreas Segmentation Based On Dynamic MRI

    SciTech Connect

    Gou, S; Rapacchi, S; Hu, P; Sheng, K

    2014-06-01

    Purpose: MRI guided radiotherapy is particularly attractive for abdominal targets with low CT contrast. To fully utilize this modality for pancreas tracking, automated segmentation tools are needed. A hybrid gradient, region growth and shape constraint (hGReS) method to segment 2D upper abdominal dynamic MRI is developed for this purpose. Methods: 2D coronal dynamic MR images of 2 healthy volunteers were acquired with a frame rate of 5 f/second. The regions of interest (ROIs) included the liver, pancreas and stomach. The first frame was used as the source where the centers of the ROIs were annotated. These center locations were propagated to the next dynamic MRI frame. 4-neighborhood region transfer growth was performed from these initial seeds for rough segmentation. To improve the results, gradient, edge and shape constraints were applied to the ROIs before final refinement using morphological operations. Results from hGReS and 3 other automated segmentation methods using edge detection, region growth and level set were compared to manual contouring. Results: For the first patient, hGReS resulted in the organ segmentation accuracy as measure by the Dices index (0.77) for the pancreas. The accuracy was slightly superior to the level set method (0.72), and both are significantly more accurate than the edge detection (0.53) and region growth methods (0.42). For the second healthy volunteer, hGReS reliably segmented the pancreatic region, achieving a Dices index of 0.82, 0.92 and 0.93 for the pancreas, stomach and liver, respectively, comparing to manual segmentation. Motion trajectories derived from the hGReS, level set and manual segmentation methods showed high correlation to respiratory motion calculated using a lung blood vessel as the reference while the other two methods showed substantial motion tracking errors. hGReS was 10 times faster than level set. Conclusion: We have shown the feasibility of automated segmentation of the pancreas anatomy based on

  9. Liver Diseases

    MedlinePlus

    ... remove poisons. There are many kinds of liver diseases. Viruses cause some of them, like hepatitis A, ... the skin, can be one sign of liver disease. Cancer can affect the liver. You could also ...

  10. Liver Transplant

    MedlinePlus

    ... You Can Use April May Calendar Liver Lowdown Mar 2014 Calendar of Events In The News Academic ... 2016 Calendar Jan Feb 2016 recipe Liver Lowdown Mar/Apr 2016 Liver Lowdown August 2016 Know Your ...

  11. Liver biopsy

    MedlinePlus

    Biopsy - liver; Percutaneous biopsy ... the biopsy needle to be inserted into the liver. This is often done by using ultrasound. The ... the chance of damage to the lung or liver. The needle is removed quickly. Pressure will be ...

  12. Liver disease

    MedlinePlus

    ... this page: //medlineplus.gov/ency/article/000205.htm Liver disease To use the sharing features on this page, please enable JavaScript. The term "liver disease" applies to many conditions that stop the liver ...

  13. Segmental neurofibromatosis.

    PubMed

    Sobjanek, Michał; Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-12-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed. PMID:25610358

  14. Segmental neurofibromatosis.

    PubMed

    Adigun, Chris G; Stein, Jennifer

    2011-01-01

    A 59-year-old man presented for evaluation and excision of non-tender, fleshy nodules that were arranged in a dermatomal distribution from the left side of the chest to the left axilla. A biopsy specimen of a nodule was consistent with a neurofibroma. Owing to the lack of other cutaneous findings, the lack of a family history of neurofibromatosis, and the dermatomal distribution of the neurofibromas, this patient met the criteria for a diagnosis of segmental neurofibromatosis (SNF) according to Riccardi's definition of SNF and classification of neurofibromatosis. Because the patient has no complications of neurofibromatosis 1 no medical treatment is required. PMID:22031651

  15. Segmental neurofibromatosis

    PubMed Central

    Dobosz-Kawałko, Magdalena; Michajłowski, Igor; Pęksa, Rafał; Nowicki, Roman

    2014-01-01

    Segmental neurofibromatosis or type V neurofibromatosis is a rare genodermatosis characterized by neurofibromas, café-au-lait spots and neurofibromas limited to a circumscribed body region. The disease may be associated with systemic involvement and malignancies. The disorder has not been reported yet in the Polish medical literature. A 63-year-old Caucasian woman presented with a 20-year history of multiple, flesh colored, dome-shaped, soft to firm nodules situated in the right lumbar region. A histopathologic evaluation of three excised tumors revealed neurofibromas. No neurological and ophthalmologic symptoms of neurofibromatosis were diagnosed. PMID:25610358

  16. Heat-Irrigate Effect' of Radiofrequency Ablation on Relevant Regional Hepatocyte in Living Swine Liver-Initial Study on Pathology.

    PubMed

    Jiang, Kai; Chen, Jiye; Liu, Yang; Liu, Jiang; Liu, Aijun; Dong, Jiahong; Huang, Zhiqiang

    2015-05-01

    Radiofrequency ablation (RFA) is one of the effective methods for HCC treatment. However, because of the "heat-sink effect" (HSE), it is very difficult to achieve a complete ablation in intrahepatic tumors. This study establishes the animal model of RFA on living swine liver and observes the 'heat-irrigate effect' on relevant regional hepatocytes. Three liver segments of 6 Guangxi Bama mini-pigs were selected to be ablated closed to segmental outflow vessel under surveillance of sonography for 6 min, and pathological changes of relevant downstream region were observed. We observed an elliptic shape of ablated area with diameter of 2.2 ± 1.1 cm on gross liver. Thermal damage was seen in downstream regional of relevant portal vein under microscope. However, adjacent area around the vessel was remained intact. In conclusion, the 'heat-irrigate effect' in RFA could cause thermal damage along the downstream region of relevant portal vein and this influence decreased gradually toward the surface. PMID:25416583

  17. Lymph circulation in the liver.

    PubMed

    Ohtani, Osamu; Ohtani, Yuko

    2008-06-01

    The liver produces a large amount of lymph, which is estimated to be 25 to 50 % of lymph flowing through the thoracic duct. The hepatic lymphatic system falls into three categories depending on their locations: portal, sublobular, and superficial lymphatic vessels. It is suggested that 80 % or more of hepatic lymph drains into portal lymphatic vessels, while the remainder drains through sublobular and capsular lymphatic vessels. The hepatic lymph primarily comes from the hepatic sinusoids. Our tracer studies, together with electron microscopy, show many channels with collagen fibers traversing through the limiting plate and connecting the space of Disse with the interstitial space either in the portal tracts, or around the sublobular veins. Fluid filtered out of the sinusoids into the space of Disse flows through the channels traversing the limiting plate either independently of blood vessels or along blood vessels and enters the interstitial space of either portal tract or sublobular veins. Fluid in the space of Disse also flows through similar channels traversing the hepatocytes intervening between the space of Disse and the hepatic capsule and drains into the interstitial space of the capsule. Fluid and migrating cells in the interstitial space pass through prelymphatic vessels to finally enter the lymphatic vessels. The area of the portal lymphatic vessels increases in liver fibrosis and cirrhosis and in idiopathic portal hypertension. Lymphatic vessels are abundant in the immediate vicinity of the hepatocellular carcinoma (HCC) and liver metastasis. HCCs expressing vascular endothelial growth factor-C are more liable to metastasize, indicating that lymphangiogenesis is associated with their enhanced metastasis. PMID:18484610

  18. Precise renal artery segmentation for estimation of renal vascular dominant regions

    NASA Astrophysics Data System (ADS)

    Wang, Chenglong; Kagajo, Mitsuru; Nakamura, Yoshihiko; Oda, Masahiro; Yoshino, Yasushi; Yamamoto, Tokunori; Mori, Kensaku

    2016-03-01

    This paper presents a novel renal artery segmentation method combining graph-cut and template-based tracking methods and its application to estimation of renal vascular dominant region. For the purpose of giving a computer assisted diagnose for kidney surgery planning, it is important to obtain the correct topological structures of renal artery for estimation of renal vascular dominant regions. Renal artery has a low contrast, and its precise extraction is a difficult task. Previous method utilizing vesselness measure based on Hessian analysis, still cannot extract the tiny blood vessels in low-contrast area. Although model-based methods including superellipsoid model or cylindrical intensity model are low-contrast sensitive to the tiny blood vessels, problems including over-segmentation and poor bifurcations detection still remain. In this paper, we propose a novel blood vessel segmentation method combining a new Hessian-based graph-cut and template modeling tracking method. Firstly, graph-cut algorithm is utilized to obtain the rough segmentation result. Then template model tracking method is utilized to improve the accuracy of tiny blood vessel segmentation result. Rough segmentation utilizing graph-cut solves the bifurcations detection problem effectively. Precise segmentation utilizing template model tracking focuses on the segmentation of tiny blood vessels. By combining these two approaches, our proposed method segmented 70% of the renal artery of 1mm in diameter or larger. In addition, we demonstrate such precise segmentation can contribute to divide renal regions into a set of blood vessel dominant regions utilizing Voronoi diagram method.

  19. A web-based computer aided system for liver surgery planning: initial implementation on RayPlus

    NASA Astrophysics Data System (ADS)

    Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo

    2016-03-01

    At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.

  20. Automatic registration between 3D intra-operative ultrasound and pre-operative CT images of the liver based on robust edge matching

    NASA Astrophysics Data System (ADS)

    Nam, Woo Hyun; Kang, Dong-Goo; Lee, Duhgoon; Lee, Jae Young; Ra, Jong Beom

    2012-01-01

    The registration of a three-dimensional (3D) ultrasound (US) image with a computed tomography (CT) or magnetic resonance image is beneficial in various clinical applications such as diagnosis and image-guided intervention of the liver. However, conventional methods usually require a time-consuming and inconvenient manual process for pre-alignment, and the success of this process strongly depends on the proper selection of initial transformation parameters. In this paper, we present an automatic feature-based affine registration procedure of 3D intra-operative US and pre-operative CT images of the liver. In the registration procedure, we first segment vessel lumens and the liver surface from a 3D B-mode US image. We then automatically estimate an initial registration transformation by using the proposed edge matching algorithm. The algorithm finds the most likely correspondences between the vessel centerlines of both images in a non-iterative manner based on a modified Viterbi algorithm. Finally, the registration is iteratively refined on the basis of the global affine transformation by jointly using the vessel and liver surface information. The proposed registration algorithm is validated on synthesized datasets and 20 clinical datasets, through both qualitative and quantitative evaluations. Experimental results show that automatic registration can be successfully achieved between 3D B-mode US and CT images even with a large initial misalignment.

  1. Method of fabricating a prestressed cast iron vessel

    DOEpatents

    Lampe, Robert F.

    1982-01-01

    A method of fabricating a prestressed cast iron vessel wherein double wall cast iron body segments each have an arcuate inner wall and a spaced apart substantially parallel outer wall with a plurality of radially extending webs interconnecting the inner wall and the outer wall, the bottom surface and the two exposed radial side surfaces of each body segment are machined and eight body segments are formed into a ring. The top surfaces and outer surfaces of the outer walls are machined and keyways are provided across the juncture of adjacent end walls of the body segments. A liner segment complementary in shape to a selected inner wall of one of the body segments is mounted to each of the body segments and again formed into a ring. The liner segments of each ring are welded to form unitary liner rings and thereafter the cast iron body segments are prestressed to complete the ring assembly. Ring assemblies are stacked to form the vessel and adjacent unitary liner rings are welded. A top head covers the top ring assembly to close the vessel and axially extending tendons retain the top and bottom heads in place under pressure.

  2. Liver surgery perspective: from pre-operative surgery planning to intra-operative image guided operation

    NASA Astrophysics Data System (ADS)

    Li, Senhu; Lennon, Brian T.; Waite, Jon M.; Clements, Logan W.; Scherer, Mike A.; Stefansic, Jim D.

    2009-10-01

    Liver cancer represents a major health care problem in the world, especially in China and several countries in Southeast Asia. The most effective treatment is through tumor resection. To improve the outcome of surgery, a combination of preoperative planning and intra operative image guided liver surgery (IGLS) system has been developed at Pathfinder Therapeutics, Inc. The preoperative planning subsystem (Linasys® PlaniSight®) is user-oriented and applies several novel algorithms on image segmentation and modeling, which allows the user to build various organ and tumor models with anticipated resection planes in less than 30 minutes. The surgeons can analyze the patient-specific case and set up surgical protocols. This information in image space can then be transferred into physical space through our intra operative image guided liver surgery system (Linasys® SurgSight®) based on modifications of existing surface registration algorithms, allowing surgeons to perform more accurate resections after preoperative planning. This tool gives surgeons a better understanding of vessel structure and tumor locations within the liver parenchyma during the surgery. Our ongoing clinical trial shows that it greatly facilitates liver resection operation and it is expected to improve the surgery outcome and create more candidates for surgery.

  3. Gd-EOB-DTPA-enhanced MRI for the assessment of liver function and volume in liver cirrhosis

    PubMed Central

    Blomqvist, L; Douglas, L; Nordell, A; Janczewska, I; Näslund, E; Jonas, E

    2013-01-01

    Objective: The aims of this study were to use dynamic hepatocyte-specific contrast-enhanced MRI to evaluate liver volume and function in liver cirrhosis, correlate the results with standard scoring models and explore the inhomogeneous distribution of liver function in cirrhotic livers. Methods: 10 patients with liver cirrhosis and 20 healthy volunteers, serving as controls, were included. Hepatic extraction fraction (HEF), input relative blood flow and mean transit time were calculated on a voxel-by-voxel basis using deconvolutional analysis. Segmental and total liver volumes as well as segmental and total hepatic extraction capacity, expressed in HEFml, were calculated. An incongruence score (IS) was constructed to reflect the uneven distribution of liver function. The Mann–Whitney U-test was used for group comparison of the quantitative liver function parameters, liver volumes and ISs. Correlations between liver function parameters and clinical scores were assessed using Spearman rank correlation. Results: Patients had larger parenchymal liver volume, lower hepatocyte function and more inhomogeneous distribution of function compared with healthy controls. Conclusion: The study demonstrates the non-homogeneous nature of liver cirrhosis and underlines the necessity of a liver function test able to compensate for the heterogeneous distribution of liver function in patients with diseased liver parenchyma. Advances in knowledge: The study describes a new way to quantitatively assess the hepatic uptake of gadoxetate or gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid in the liver as a whole as well as on a segmental level. PMID:23403453

  4. BIOASSAY VESSEL FAILURE ANALYSIS

    SciTech Connect

    Vormelker, P

    2008-09-22

    Two high-pressure bioassay vessels failed at the Savannah River Site during a microwave heating process for biosample testing. Improper installation of the thermal shield in the first failure caused the vessel to burst during microwave heating. The second vessel failure is attributed to overpressurization during a test run. Vessel failure appeared to initiate in the mold parting line, the thinnest cross-section of the octagonal vessel. No material flaws were found in the vessel that would impair its structural performance. Content weight should be minimized to reduce operating temperature and pressure. Outer vessel life is dependent on actual temperature exposure. Since thermal aging of the vessels can be detrimental to their performance, it was recommended that the vessels be used for a limited number of cycles to be determined by additional testing.

  5. Reductions in post-hepatectomy liver failure and related mortality after implementation of the LiMAx algorithm in preoperative work-up: a single-centre analysis of 1170 hepatectomies of one or more segments

    PubMed Central

    Jara, Maximilian; Reese, Tim; Malinowski, Maciej; Valle, Erika; Seehofer, Daniel; Puhl, Gero; Neuhaus, Peter; Pratschke, Johann; Stockmann, Martin

    2015-01-01

    Objectives Post-hepatectomy liver failure has a major impact on patient outcome. This study aims to explore the impact of the integration of a novel patient-centred evaluation, the LiMAx algorithm, on perioperative patient outcome after hepatectomy. Methods Trends in perioperative variables and morbidity and mortality rates in 1170 consecutive patients undergoing elective hepatectomy between January 2006 and December 2011 were analysed retrospectively. Propensity score matching was used to compare the effects on morbidity and mortality of the integration of the LiMAx algorithm into clinical practice. Results Over the study period, the proportion of complex hepatectomies increased from 29.1% in 2006 to 37.7% in 2011 (P = 0.034). Similarly, the proportion of patients with liver cirrhosis selected for hepatic surgery rose from 6.9% in 2006 to 11.3% in 2011 (P = 0.039). Despite these increases, rates of post-hepatectomy liver failure fell from 24.7% in 2006 to 9.0% in 2011 (P < 0.001) and liver failure-related postoperative mortality decreased from 4.0% in 2006 to 0.9% in 2011 (P = 0.014). Propensity score matching was associated with reduced rates of post-hepatectomy liver failure [24.7% (n = 77) versus 11.2% (n = 35); P < 0.001] and related mortality [3.8% (n = 12) versus 1.0% (n = 3); P = 0.035]. Conclusions Postoperative liver failure and postoperative liver failure-related mortality decreased in patients undergoing hepatectomy following the implementation of the LiMAx algorithm. PMID:26058324

  6. Polyp Segmentation in NBI Colonoscopy

    NASA Astrophysics Data System (ADS)

    Gross, Sebastian; Kennel, Manuel; Stehle, Thomas; Wulff, Jonas; Tischendorf, Jens; Trautwein, Christian; Aach, Til

    Endoscopic screening of the colon (colonoscopy) is performed to prevent cancer and to support therapy. During intervention colon polyps are located, inspected and, if need be, removed by the investigator. We propose a segmentation algorithm as a part of an automatic polyp classification system for colonoscopic Narrow-Band images. Our approach includes multi-scale filtering for noise reduction, suppression of small blood vessels, and enhancement of major edges. Results of the subsequent edge detection are compared to a set of elliptic templates and evaluated. We validated our algorithm on our polyp database with images acquired during routine colonoscopic examinations. The presented results show the reliable segmentation performance of our method and its robustness to image variations.

  7. Liver transplant

    MedlinePlus

    ... series References Keefe EB. Hepatic failure and liver transplantation. In: Goldman L, Schafer AI, eds. Goldman's Cecil ... 2011:chap 157. Martin P, Rosen HR. Liver transplantation. In: Feldman M, Friedman LS, Brandt LJ, eds. ...

  8. Liver spots

    MedlinePlus

    Sun-induced skin changes - liver spots; Senile or solar lentigines; Skin spots - aging; Age spots ... Liver spots are changes in skin color that occur in older skin. The coloring may be due to aging, exposure to the sun ...

  9. Liver Diseases

    MedlinePlus

    Your liver is the largest organ inside your body. It helps your body digest food, store energy, and remove poisons. There are many kinds of liver diseases. Viruses cause some of them, like hepatitis ...

  10. Liver biopsy

    MedlinePlus

    ... Test is Performed The biopsy helps diagnose many liver diseases . The procedure also helps assess the stage (early, advanced) of liver disease. This is especially important in hepatitis C infection. ...