scholarly journals Objective Ventricle Segmentation in Brain CT with Ischemic Stroke Based on Anatomical Knowledge

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaohua Qian ◽  
Yuan Lin ◽  
Yue Zhao ◽  
Xinyan Yue ◽  
Bingheng Lu ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Domain Knowledge ◽  
Mean Squared Error ◽  
Detection System ◽  
Three Dimensional ◽  
Segmentation Strategy ◽  
Initial Segmentation ◽  
Brain Ventricle ◽  
Sensitivity Specificity ◽  
Ventricle Segmentation

Ventricle segmentation is a challenging technique for the development of detection system of ischemic stroke in computed tomography (CT), as ischemic stroke regions are adjacent to the brain ventricle with similar intensity. To address this problem, we developed an objective segmentation system of brain ventricle in CT. The intensity distribution of the ventricle was estimated based on clustering technique, connectivity, and domain knowledge, and the initial ventricle segmentation results were then obtained. To exclude the stroke regions from initial segmentation, a combined segmentation strategy was proposed, which is composed of three different schemes: (1) the largest three-dimensional (3D) connected component was considered as the ventricular region; (2) the big stroke areas were removed by the image difference methods based on searching optimal threshold values; (3) the small stroke regions were excluded by the adaptive template algorithm. The proposed method was evaluated on 50 cases of patients with ischemic stroke. The mean Dice, sensitivity, specificity, and root mean squared error were 0.9447, 0.969, 0.998, and 0.219 mm, respectively. This system can offer a desirable performance. Therefore, the proposed system is expected to bring insights into clinic research and the development of detection system of ischemic stroke in CT.

scholarly journals An Improved Fuzzy Connectedness Method for Automatic Three-Dimensional Liver Vessel Segmentation in CT Images

2018 ◽  
Vol 2018 ◽  
pp. 1-18 ◽  
Author(s):  
Rui Zhang ◽  
Zhuhuang Zhou ◽  
Weiwei Wu ◽  
Chung-Chih Lin ◽  
Po-Hsiang Tsui ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Region Growing ◽  
Threshold Level ◽  
Ct Images ◽  
Vessel Segmentation ◽  
Fuzzy Connectedness ◽  
Segmentation Strategy ◽  
Volumetric Images ◽  
Vesselness Filter ◽  
Sensitivity Specificity

In this paper, an improved fuzzy connectedness (FC) method was proposed for automatic three-dimensional (3D) liver vessel segmentation in computed tomography (CT) images. The vessel-enhanced image (i.e., vesselness image) was incorporated into the fuzzy affinity function of FC, rather than the intensity image used by traditional FC. An improved vesselness filter was proposed by incorporating adaptive sigmoid filtering and a background-suppressing item. The fuzzy scene of FC was automatically initialized by using the Otsu segmentation algorithm and one single seed generated adaptively, while traditional FC required multiple seeds. The improved FC method was evaluated on 40 cases of clinical CT volumetric images from the 3Dircadb (n=20) and Sliver07 (n=20) datasets. Experimental results showed that the proposed liver vessel segmentation strategy could achieve better segmentation performance than traditional FC, region growing, and threshold level set. Average accuracy, sensitivity, specificity, and Dice coefficient of the improved FC method were, respectively, (96.4 ± 1.1)%, (73.7 ± 7.6)%, (97.4 ± 1.3)%, and (67.3 ± 5.7)% for the 3Dircadb dataset and (96.8 ± 0.6)%, (89.1 ± 6.8)%, (97.6 ± 1.1)%, and (71.4 ± 7.6)% for the Sliver07 dataset. It was concluded that the improved FC may be used as a new method for automatic 3D segmentation of liver vessel from CT images.

Three-dimensional active shape model matching for left ventricle segmentation in cardiac CT

2003 ◽  
Author(s):  
Hans C. van Assen ◽  
Rob J. van der Geest ◽  
Mikhail G. Danilouchkine ◽  
Hildo J. Lamb ◽  
Johan H. C. Reiber ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Cardiac Ct ◽  
Three Dimensional ◽  
Active Shape Model ◽  
Model Matching ◽  
Shape Model ◽  
Active Shape ◽  
Ventricle Segmentation

Fabrication of Three-Dimensional Micro-Structures with Two-Photon Absorption by Femtosecond Laser

2006 ◽  
Vol 532-533 ◽  
pp. 568-571
Author(s):  
Ming Zhou ◽  
Hai Feng Yang ◽  
Li Peng Liu ◽  
Lan Cai
Keyword(s):  
Photonic Crystal ◽  
Femtosecond Laser ◽  
Detection System ◽  
Three Dimensional ◽  
Photon Absorption ◽  
Micro Fabrication ◽  
Two Photon Absorption ◽  
Two Photon ◽  
Photo Polymerization ◽  
System A

The photo-polymerization induced by Two-Photon Absorption (TPA) is tightly confined in the focus because the efficiency of TPA is proportional to the square of intensity. Three-dimensional (3D) micro-fabrication can be achieved by controlling the movement of the focus. Based on this theory, a system for 3D-micro-fabrication with femtosecond laser is proposed. The system consists of a laser system, a microscope system, a real-time detection system and a 3D-movement system, etc. The precision of micro-machining reaches a level down to 700nm linewidth. The line width was inversely proportional to the fabrication speed, but proportional to laser power and NA. The experiment results were simulated, beam waist of 0.413μm and TPA cross section of 2×10-54cm4s was obtained. While we tried to optimize parameters, we also did some research about its applications. With TPA photo-polymerization by means of our experimental system, 3D photonic crystal of wood-pile structure twelve layers and photonic crystal fiber are manufactured. These results proved that the micro-fabrication system of TPA can not only obtain the resolution down to sub-micron level, but also realize real 3D micro-fabrication.

T1595: Three Dimensional Image Overlay Navigation Using Magnetic Endoscope Detection System for NOTES® and SILS

2010 ◽  
Vol 71 (5) ◽  
pp. AB318 ◽  
Author(s):  
Maki Sugimoto ◽  
Yoshinori Morita ◽  
Tsuyoshi Sanuki ◽  
Hiromu Kutsumi ◽  
Takeshi Azuma
Keyword(s):  
Detection System ◽  
Three Dimensional ◽  
Dimensional Image ◽  
Image Overlay

scholarly journals Three-dimensional cultured mesenchymal stem cells enhance repair of ischemic stroke through inhibition of microglia

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yuejiao Li ◽  
Yankai Dong ◽  
Ye Ran ◽  
Yanan Zhang ◽  
Boyao Wu ◽  
...  
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Ischemic Stroke ◽  
Proinflammatory Cytokines ◽  
Infarct Volume ◽  
Brain Lesion ◽  
Three Dimensional ◽  
Artery Occlusion ◽  
Rna Seq ◽  
The Brain

Abstract Background We show previously that three-dimensional (3D) spheroid cultured mesenchymal stem cells (MSCs) exhibit reduced cell size thus devoid of lung entrapment following intravenous (IV) infusion. In this study, we determined the therapeutic effect of 3D-cultured MSCs on ischemic stroke and investigated the mechanisms involved. Methods Rats underwent middle cerebral artery occlusion (MCAO) and reperfusion. 1 × 106 of 3D- or 2D-cultured MSCs, which were pre-labeled with GFP, were injected through the tail vain three and seven days after MCAO. Two days after infusion, MSC engraftment into the ischemic brain tissues was assessed by histological analysis for GFP-expressing cells, and infarct volume was determined by MRI. Microglia in the lesion were sorted and subjected to gene expressional analysis by RNA-seq. Results We found that infusion of 3D-cultured MSCs significantly reduced the infarct volume of the brain with increased engraftment of the cells into the ischemic tissue, compared to 2D-cultured MSCs. Accordingly, in the brain lesion of 3D MSC-treated animals, there were significantly reduced numbers of amoeboid microglia and decreased levels of proinflammatory cytokines, indicating attenuated activation of the microglia. RNA-seq of microglia derived from the lesions suggested that 3D-cultured MSCs decreased the response of microglia to the ischemic insult. Interestingly, we observed a decreased expression of mincle, a damage-associated molecular patterns (DAMPs) receptor, which induces the production of proinflammatory cytokines, suggestive of a potential mechanism in 3D MSC-mediated enhanced repair to ischemic stroke. Conclusions Our data indicate that 3D-cultured MSCs exhibit enhanced repair to ischemic stroke, probably through a suppression to ischemia-induced microglial activation.

Abstract 61: MR Perfusion to Determine the Status of Collaterals in Patients With Acute Ischemic Stroke: Look Beyond Perfusion Time-maps

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Kambiz Nael ◽  
James Knitter ◽  
Amish Doshi ◽  
J Mocco ◽  
Thomas Naidich
Keyword(s):  
Ischemic Stroke ◽  
Diagnostic Accuracy ◽  
Cerebral Angiography ◽  
Independent Predictor ◽  
Collateral Flow ◽  
Mr Perfusion ◽  
The Status ◽  
Perfusion Time ◽  
Sensitivity Specificity ◽  
Angiographic Findings

Purpose: Collateral flow is an independent predictor of reperfusion and infarct size in patients with acute ischemic stroke (AIS). MR perfusion time-maps show delayed perfusion but unable to differentiate antegrade from collateral flow if used alone. Using a multiparametric approach, we aimed to identify a perfusion biomarker that can represent the extent of collaterals in comparison to angiographic findings. Methods: AIS patients with MCA proximal occlusion who had baseline MRI and cerebral angiography included. MR perfusion data were processed by Bayesian method to generate arterial tissue delay (ATD) maps at thresholds of 2 & 6 seconds. The volume of delayed perfusion (Vol-ATD 2sec ), critical hypoperfusion (Vol-ATD 6sec ), and hypoperfusion (Vol-ATD 2sec-6sec ) in addition to corresponding rCBV and rCBF were calculated. Baseline angiography collaterals were dichotomized to poor (TICI ≤2a) or good collaterals (TICI≥ 2b). The association of perfusion biomarkers and status of collaterals was assessed by repeated measure of analyses and receiver operating characteristic (ROC) to determine the optimal parameters for predicting the status of collaterals. Results: In 37 patients included, 20 had good collaterals on cerebral angiography. After controlling for age, baseline NIHSS and infarct volume, multivariate logistic regression analysis identified rCBV (p=0.001) and hypoperfused volume (Vol-ATD 2sec-6sec ), but not rCBF, Vol-ATD 2sec or Vol-ATD 6sec , as independent predictors of good collaterals. ROC analysis showed AUC of 0.89 (sensitivity/specificity: 85%90%) for rCBV and AUC of 0.78 (sensitivity/specificity: 70%82%) for Vol-ATD 2sec-6sec . Hypoperfused tissue volume (Vol-ATD 2sec-6sec ) x its rCBV, termed hypoperfused tissue collateral index , remained an independent predictor of good collaterals with improved diagnostic accuracy over each measure alone (AUC: 0.96, sensitivity/specificity: 91%100%). Conclusions: Multiparametric MR perfusion can be used to assess the status of collaterals in patients with AIS. Hypoperfused tissue collateral index defined as hypoperfused volume (Vol-ATD 2sec-6sec ) x rCBV is a new perfusion index with diagnostic accuracy of 96% compared to angiographic findings to predict status of collaterals.

scholarly journals Operational ocean models in the Adriatic Sea: a skill assessment

Ocean Science ◽  
2008 ◽  
Vol 4 (1) ◽  
pp. 61-71 ◽  
Author(s):  
J. Chiggiato ◽  
P. Oddo
Keyword(s):  
General Circulation ◽  
Mean Squared Error ◽  
Three Dimensional ◽  
Circulation Model ◽  
Remote Sensing Data ◽  
Skill Assessment ◽  
Regional Models ◽  
Operational Systems ◽  
Forecasting System ◽  
The Mediterranean

Abstract. In the framework of the Mediterranean Forecasting System (MFS) project, the performance of regional numerical ocean forecasting systems is assessed by means of model-model and model-data comparison. Three different operational systems considered in this study are: the Adriatic REGional Model (AREG); the Adriatic Regional Ocean Modelling System (AdriaROMS) and the Mediterranean Forecasting System General Circulation Model (MFS-GCM). AREG and AdriaROMS are regional implementations (with some dedicated variations) of POM and ROMS, respectively, while MFS-GCM is an OPA based system. The assessment is done through standard scores. In situ and remote sensing data are used to evaluate the system performance. In particular, a set of CTD measurements collected in the whole western Adriatic during January 2006 and one year of satellite derived sea surface temperature measurements (SST) allow to asses a full three-dimensional picture of the operational forecasting systems quality during January 2006 and to draw some preliminary considerations on the temporal fluctuation of scores estimated on surface quantities between summer 2005 and summer 2006. The regional systems share a negative bias in simulated temperature and salinity. Nonetheless, they outperform the MFS-GCM in the shallowest locations. Results on amplitude and phase errors are improved in areas shallower than 50 m, while degraded in deeper locations, where major models deficiencies are related to vertical mixing overestimation. In a basin-wide overview, the two regional models show differences in the local displacement of errors. In addition, in locations where the regional models are mutually correlated, the aggregated mean squared error was found to be smaller, that is a useful outcome of having several operational systems in the same region.

scholarly journals Weighted area constraints-based breast lesion segmentation in ultrasound image analysis

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Qianting Ma ◽  
Tieyong Zeng ◽  
Dexing Kong ◽  
Jianwei Zhang
Keyword(s):  
Level Set ◽  
Domain Knowledge ◽  
Ultrasound Image ◽  
Speckle Noise ◽  
Breast Ultrasound ◽  
Nonlinear Constraint ◽  
Low Contrast ◽  
Anisotropic Diffusion Filter ◽  
Initial Segmentation ◽  
Speed Up

<p style='text-indent:20px;'>Breast ultrasound segmentation is a challenging task in practice due to speckle noise, low contrast and blurry boundaries. Although numerous methods have been developed to solve this problem, most of them can not produce a satisfying result due to uncertainty of the segmented region without specialized domain knowledge. In this paper, we propose a novel breast ultrasound image segmentation method that incorporates weighted area constraints using level set representations. Specifically, we first use speckle reducing anisotropic diffusion filter to suppress speckle noise, and apply the Grabcut on them to provide an initial segmentation result. In order to refine the resulting image mask, we propose a weighted area constraints-based level set formulation (WACLSF) to extract a more accurate tumor boundary. The major contribution of this paper is the introduction of a simple nonlinear constraint for the regularization of probability scores from a classifier, which can speed up the motion of zero level set to move to a desired boundary. Comparisons with other state-of-the-art methods, such as FCN-AlexNet and U-Net, show the advantages of our proposed WACLSF-based strategy in terms of visual view and accuracy.</p>

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