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Left Atrial Segmentation Challenge: A Unified Benchmarking Framework [chapter]

Catalina Tobon-Gomez, Jochen Peters, Juergen Weese, Karen Pinto, Rashed Karim, Tobias Schaeffter, Reza Razavi, Kawal S. Rhode
2014 Lecture Notes in Computer Science  
Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem.  ...  We aimed at evaluating current algorithms that address this problem by creating a unified benchmarking framework through the mechanism of a challenge, the Left Atrial Segmentation Challenge 2013 (LASC'  ...  Geers for their very useful suggestions for the automatisation of the evaluation framework.  ... 
doi:10.1007/978-3-642-54268-8_1 fatcat:ejttwrw4yvd2jknagtlydalrre

Statistical Classifiers in Computer Vision [chapter]

J. Hornegger, D. Paulus, H. Niemann
1998 Studies in Classification, Data Analysis, and Knowledge Organization  
This paper introduces a unified Bayesian approach to 3-D computer vision using segmented image features.  ...  Normally distributed features are used for automatic learning, localization, and classification. The contribution concludes with the experimental evaluation of the presented theoretical approach.  ...  The correct pose is computed for 45 images using the statistical approach (see Figure 2 ). The alignment method failed for 11 images.  ... 
doi:10.1007/978-3-642-72087-1_33 fatcat:kteobfdnprdbxkys4twepyc7lu

Comparison of statistical shape models built on correspondence probabilities and one-to-one correspondences

Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Nicholas Ayache, Heinz Handels, Joseph M. Reinhardt, Josien P. W. Pluim
2008 Medical Imaging 2008: Image Processing  
These are the basis for a novel algorithm that computes a generative statistical shape model.  ...  A comparison with a statistical shape model which is built using the Iterative Closest Point (ICP) registration algorithm and a Principal Component Analysis (PCA) shows that our approach leads to better  ...  Acknowledgments The MR images as well as the segmentations of the putamen data were kindly provided by the Hôpital La Pitié-Salpêtrière, Paris, France.  ... 
doi:10.1117/12.771136 dblp:conf/miip/HufnagelPEAH08 fatcat:dsbvrhxl65axtgyqrv3qkq2lqa

Unsupervised image segmentation by Global and local Criteria Optimization Based on Bayesian Networks [article]

Mohamed Ali Mahjoub, Mohamed Mhiri
2015 arXiv   pre-print
Today Bayesian networks are more used in many areas of decision support and image processing. In this way, our proposed approach uses Bayesian Network to modelize the segmented image quality.  ...  To find the segmented image with the best overall quality we used two approximate inference methods, the first using ICM algorithm which is widely used in Markov Models and a second is a recursive method  ...  by a) Otsu b) Proposed approach multi layers Although the predicates used are not specified for this field segmentation of documents to judge the quality of the segmented image, results of our approach  ... 
arXiv:1501.05617v1 fatcat:hgcddlgaxjfyjhjlpglojjlcsi

CerebroMatic: A Versatile Toolbox for Spline-Based MRI Template Creation

Marko Wilke, Mekibib Altaye, Scott K. Holland
2017 Frontiers in Computational Neuroscience  
Brain image spatial normalization and tissue segmentation rely on prior tissue probability maps.  ...  Using statistically-described parameters, high-quality tissue probability maps could be generated for the whole age range; they are consistently closer to a gold standard than conventionally-generated  ...  round of unified segmentation (Ashburner and Friston, 2005) , to create a bias-corrected image in native space, which was then used for further processing.  ... 
doi:10.3389/fncom.2017.00005 pmid:28275348 pmcid:PMC5321046 fatcat:v5ozjexjinecfifu2osoflssqy

Image Segmentation with a Unified Graphical Model

Lei Zhang, Qiang Ji
2010 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Using the unified graphical model, image segmentation can be performed through a principled probabilistic inference.  ...  We propose a unified graphical model that can represent both the causal and noncausal relationships among random variables and apply it to the image segmentation problem.  ...  ACKNOWLEDGMENTS This project is supported in part by a grant from the US National Science Foundation under award number 0241182.  ... 
doi:10.1109/tpami.2009.145 pmid:20558874 fatcat:d3v5j5h3zzbk7eusno2xpa4gri

3D cardiac segmentation with pose-invariant higher-order MRFs

Bo Xiang, Chaohui Wang, Jean-Francois Deux, Alain Rahmouni, Nikos Paragios
2012 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)  
This paper proposes a novel pose-invariant segmentation approach for left ventricle in 3D CT images.  ...  image or a derived feature space.  ...  Early approaches have considered slice-by-slice segmentation [1] using active contours.The use of active shape models [2] as well as active appearance models was a step forward where geometric and  ... 
doi:10.1109/isbi.2012.6235836 dblp:conf/isbi/XiangWDRP12 fatcat:7jvx5bumhbbv7mfhtmugdndofy

Heterogeneous Computing for Vertebra Detection and Segmentation in X-Ray Images

Fabian Lecron, Sidi Ahmed Mahmoudi, Mohammed Benjelloun, Saïd Mahmoudi, Pierre Manneback
2011 International Journal of Biomedical Imaging  
An original approach taking advantage of the edge polygonal approximation was developed to locate the vertebra positions in a X-ray image.  ...  Experimentations have been conducted using a set of high-resolution X-ray medical images, showing a global speedup ranging from 3 to 22, by comparison with the CPU implementation.  ...  They aknowledge also the support of the European COST action IC0805 "Open European Network for High Performance Computing on Complex Environment".  ... 
doi:10.1155/2011/640208 pmid:21860613 pmcid:PMC3154518 fatcat:ex7lf5hsufg47giu3i6vsrpnvm

2014 Index IEEE Transactions on Medical Imaging Vol. 33

2014 IEEE Transactions on Medical Imaging  
Y., +, TMI Nov. 2014 2107-2117 Image recognition A Generic Approach to Pathological Lung Segmentation.  ...  Mamonov, A. V., +, TMI July 2014 1488-1502 Automatic Segmentation of Breast MR Images Through a Markov Random Field Statistical Model.  ...  MRI Upsampling Using Feature-Based Nonlocal Means Approach. Jafari-Khouzani, K., 1969 -1985 Numerical Surrogates for Human Observers in Myocardial Motion Evaluation From SPECT Images.  ... 
doi:10.1109/tmi.2014.2386278 fatcat:poarfhfto5bm5mhfl7ugwtw4xy

A Bayesian Network Model for Automatic and Interactive Image Segmentation

Lei Zhang, Qiang Ji
2011 IEEE Transactions on Image Processing  
While existing interactive segmentation (IS) approaches often passively depend on the user to provide exact intervention, we propose a new active input selection approach to provide suggestions for the  ...  Besides the automatic image segmentation, the proposed model can also be used for interactive image segmentation.  ...  Compared with the BN model proposed in this paper, the unified graphical model is more expressive and more powerful. But the unified model was only used for automatic segmentation.  ... 
doi:10.1109/tip.2011.2121080 pmid:21356618 fatcat:l45ltz2ktrfubodwjpp2j2ofpa

Multi-Faceted Hierarchical Image Segmentation Taxonomy ( MFHIST)

Tilottama Goswami, Arun Agarwal, C Raghavendra Rao
2021 IEEE Access  
The paper proposes a unified way of systematic categorization of the research work on image segmentation called Multi-Faceted Hierarchical Image Segmentation Taxonomy (MFHIST), which consist of six facets  ...  presented in a hierarchical manner -scope, requirement, control, feature, image representation and approach specifications.  ...  A great deal of activity on recent statistical approaches to level set segmentation is referred in survey paper [21] .  ... 
doi:10.1109/access.2021.3055678 fatcat:r3aaee4vrbgqhdzlb6qc5vkefy

Page 7748 of Mathematical Reviews Vol. , Issue 2002J [page]

2002 Mathematical Reviews  
Here, the authors establish the solvability of the indefinite LQ problem using the classical frequency domain approach and unify different approaches dealing with the LQ problem.  ...  Another advantage of the given method is that it can segment wavelet- compressed images without decompression. Henk J. A. M.  ... 

A Variational Framework for Joint Detection and Segmentation of Ovarian Cancer Metastases [chapter]

Jianfei Liu, Shijun Wang, Marius George Linguraru, Jianhua Yao, Ronald M. Summers
2013 Lecture Notes in Computer Science  
Validation on 50 patient datasets demonstrated that our joint approach was superior to a sequential method with sensitivity 89.2% vs. 81.4% (Fisher exact test p = 0.046) and false positive per patient  ...  This paper presents a variational framework that combines region competition based level set propagation and image matching flow computation to jointly detect and segment metastases.  ...  (a) (b) (c) (d) (e) (f ) (g) (h) (i) (j) (k) (l) Conclusion and Future Work In this paper, we developed a variational framework to jointly detect and segment ovarian cancer metastases by unifying image  ... 
doi:10.1007/978-3-642-40763-5_11 fatcat:rbkwtvturnfyrk66igrpk3vd6y

Subdural and depth electrode placement in the brain for validation of MEG in partial epilepsy

Mohammad-Reza Siadat, Kost Elisevich, Hamid Soltanian-Zadeh, Kourosh Jafari-Khouzani, Susan Bowyer, Kevin R. Cleary, Robert L. Galloway, Jr.
2006 Medical Imaging 2006: Visualization, Image-Guided Procedures, and Display  
It also provides a ground for validation of less expensive and noninvasive procedures, e.g., scalp EEG, MEG.  ...  This approach offers a means by which an accurate appreciation of the zone of epileptogenicity may be established through optimal visualization and further quantitative analyses of the fused data.  ...  Segmentation Segmentation is always a challenging part of medical image processing.  ... 
doi:10.1117/12.657012 dblp:conf/miigp/SiadatESJB06 fatcat:ph5zumftczfa3i3tpzqtaca7wy

A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images

Zhou Zheng, Xuechang Zhang, Huafei Xu, Wang Liang, Siming Zheng, Yueding Shi
2018 BioMed Research International  
Specifically, for liver segmentation, a hybrid image preprocessing scheme is used first to convert an input CT image into a binary image.  ...  In this paper, we present a method for liver segmentation and a method for liver tumor segmentation.  ...  LY17E050011 and the research project on key technologies of complex surgery for liver resection based on 3D printing that was funded by Ningbo, China, under Grant no. 2015C50025.  ... 
doi:10.1155/2018/3815346 pmid:30159326 fatcat:l6sfgh6fmzczlmtm4hmvmudpli
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