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A variational method for vessels segmentation: algorithm and application to liver vessels visualization

M. Freiman, L. Joskowicz, J. Sosna, Michael I. Miga, Kenneth H. Wong
2009 Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling  
We present a new variational-based method for automatic liver vessels segmentation from abdominal CTA images.  ...  These results indicate that our method is suitable for the automatic segmentation and visualization of the liver vessels.  ...  Ten main liver vessels were examined in each dataset: CONCLUSION We have presented a new variational method for vessels segmentation and showed its application to liver vessels segmentation.  ... 
doi:10.1117/12.810611 dblp:conf/miigp/FreimanJS09 fatcat:klzr3bpqgzdvvgyol3u45dbivi

Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review

Marcin Ciecholewski, Michał Kassjański
2021 Sensors  
Based on the literature, this review paper presents the most advanced and effective methods of liver vessel segmentation, as well as their performance according to the metrics used.  ...  The segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures  ...  The reason for using CIL for liver vessel segmentation is that it is difficult to provide a sufficient number of features to cover all variations in the liver vessel structure.  ... 
doi:10.3390/s21062027 pmid:33809361 fatcat:dowsqsuwlrgyjic7ozoa7mr23q

Hepatic vascular network segmentation for liver surgery planning

Olivér Benis, Benedek Csaba
2021 Zenodo  
During my work I have developed a new method for automatic liver vessel network segmentation that is based on a marked point process (MPP) model and region growing algorithm.  ...  The adaptivity and robustness of the proposed 3D vessel network extraction algorithm was also demonstrated with testing its applicability for vessel segmentation in the lungs.  ...  During my work I have developed a new method for fully automatic liver vessel network segmentation that is based on a three dimensional marked point process (MPP) model and region growing algorithm.  ... 
doi:10.5281/zenodo.5779145 fatcat:hjkwmjsv55egrnmgeh62ysssna

A new segmentation framework based on sparse shape composition in liver surgery planning system

Guotai Wang, Shaoting Zhang, Feng Li, Lixu Gu
2013 Medical Physics (Lancaster)  
deal with the complex variations of liver shapes and obtain patient-specific liver shape priors. (2) The integration of the liver shape prior with a minimally supervised segmentation algorithm to achieve  ...  Methods: The segmentation framework proposed in this paper includes two important modules: (1) The robust shape prior modeling for liver, in which the sparse shape composition (SSC) model is employed to  ...  ACKNOWLEDGMENTS This research is partially supported by the Chinese NSFC research fund (61190120, 61190124 and 61271318) and biomedical engineering fund of Shanghai Jiao Tong University (YG2012ZD06).  ... 
doi:10.1118/1.4802215 pmid:23635283 pmcid:PMC3651215 fatcat:cl5ye6uj7jecrkz6tzcflixmgi

Multi-Scale Blood Vessel Detection and Segmentation in Breast MRIs

Gilad Kahala, Miri Sklair, Hedva Spitzer
2017 Journal of Biomedical Engineering and Medical Devices  
It appears that with the application of mass detection as the last step, our algorithm provides a helpful tool for tumour enhancement and automated detection of breast cancer.  ...  An algorithm is proposed to perform segmentation of blood vessels in 3D breast MRIs. The blood vessels play an essential role as an additional tool to detect tumors.  ...  The suggested method can be applied to additional medical applications, and other types of tissues such as: segmentation of vessels in the liver or airways in the lungs.  ... 
doi:10.4172/2475-7586.1000122 fatcat:5adm3m26njdslcd7pdy7ecpmbm

Multi-scale Blood Vessel Detection and Segmentation in Breast MRIs

Gilad Kahala, Miri Sklair, Hedva Spitzer
2018 Journal of Medical and Biological Engineering  
It appears that with the application of mass detection as the last step, our algorithm provides a helpful tool for tumour enhancement and automated detection of breast cancer.  ...  An algorithm is proposed to perform segmentation of blood vessels in 3D breast MRIs. The blood vessels play an essential role as an additional tool to detect tumors.  ...  The suggested method can be applied to additional medical applications, and other types of tissues such as: segmentation of vessels in the liver or airways in the lungs.  ... 
doi:10.1007/s40846-018-0418-6 fatcat:6ezqtpwf5re7jirs2yrvmvngqa

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

Jens N. Kaftan, Hüseyin Tek, Til Aach, Josien P. W. Pluim, Benoit M. Dawant
2009 Medical Imaging 2009: Image Processing  
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.  ...  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.  ...  A review on vessel segmentation methods with application to hepatic vessel segmentation can be also found in [8] . Soler et al .  ... 
doi:10.1117/12.812407 dblp:conf/miip/KaftanTA09 fatcat:ajc5epa6yvaozciybfoxuinfvu

Implicit medial representation for vessel segmentation

Guillaume Pizaine, Elsa Angelini, Isabelle Bloch, Sherif Makram-Ebeid, Benoit M. Dawant, David R. Haynor
2011 Medical Imaging 2011: Image Processing  
The centerline itself is derived as the characteristic function of an underlying signed medialness function, to enforce a tubular shape for the segmented object, and evolves under shape and medialness  ...  In the context of mathematical modeling of complex vessel tree structures with deformable models, we present a novel level set formulation to evolve both the vessel surface and its centerline.  ...  A mask of the liver was first computed during an additional pre-processing step to restrain the propagation to the liver. The segmentation is then performed according to the methods in Sect. 2.  ... 
doi:10.1117/12.878048 dblp:conf/miip/PizaineABM11 fatcat:exfkerlgsve6rbyfegtbkcgjry

Automatic Volumetric Liver Segmentation from MRI Data

Haidi Ibrahim, Maria Petrou, Kevin Wells, Simon Doran, Øystein Olsen
2010 Journal of clean energy technologies  
From the initial slice, the contour propagates inside the volume and segments the liver in every slice using a dynamic programming algorithm.  ...  In this paper, we automate a segmentation technique known as intelligent scissors to segment the liver from volumetric MRI data.  ...  There are many possible advantages of segmenting the liver surface, such as to create 3D liver model, to separate the liver region from the surrounding organs (for better visual inspection), and to calculate  ... 
doi:10.7763/ijcte.2010.v2.136 fatcat:wb5us6gtgnbfvfj3ryx7vwuasy

Direction-dependent level set segmentation of cerebrovascular structures

Nils Daniel Forkert, Dennis Säring, Till Illies, Jens Fiehler, Jan Ehrhardt, Heinz Handels, Alexander Schmidt-Richberg, Benoit M. Dawant, David R. Haynor
2011 Medical Imaging 2011: Image Processing  
A general problem of most vessel segmentation methods is the insufficient delineation of small vessels, which are often represented by rather low intensities and high surface curvatures.  ...  Exact cerebrovascular segmentations based on high resolution 3D anatomical datasets are required for many clinical applications.  ...  In a following evaluation, the proposed method could be applied for other vessel segmentation problems, such as lung or liver vessels.  ... 
doi:10.1117/12.877942 dblp:conf/miip/ForkertSIFEHS11 fatcat:nbjmz6si3rhtnlklv4nlj2q5py

Segmentation of Liver Anatomy by Combining 3D U-Net Approaches

Abir Affane, Adrian Kucharski, Paul Chapuis, Samuel Freydier, Marie-Ange Lebre, Antoine Vacavant, Anna Fabijańska
2021 Applied Sciences  
Recent state-of-the-art methods for liver vessel reconstruction mostly utilize deep learning methods, namely, the U-Net model and its variants.  ...  Moreover, most research works do not consider the liver volume segmentation as a preprocessing step, in order to keep only inner hepatic vessels, for Couinaud representation for instance.  ...  for Academic Exchange (NAWA) with the Campus France Code 44833NE and NAWA code PPN/BFR/2019/1/00006/U/00001.  ... 
doi:10.3390/app11114895 fatcat:qkmwouribbbopavnqckxahast4

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

Reinhard Beichel, Alexander Bornik, Christian Bauer, Erich Sorantin
2012 Medical Physics (Lancaster)  
The purpose of this work was to evaluate a new approach for liver segmentation.  ...  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.  ...  Building a liver model is challenging because of the large variation in liver shapes, and several alternatives to model-based methods were developed.  ... 
doi:10.1118/1.3682171 pmid:22380370 pmcid:PMC4109564 fatcat:wni4xf355nhdxd2rkpqtlkfzl4

Vessel Segmentation for Ablation Treatment Planning and Simulation [chapter]

Tuomas Alhonnoro, Mika Pollari, Mikko Lilja, Ronan Flanagan, Bernhard Kainz, Judith Muehl, Ursula Mayrhauser, Horst Portugaller, Philipp Stiegler, Karlheinz Tscheliessnigg
2010 Lecture Notes in Computer Science  
In this paper, a novel segmentation method for liver vasculature is presented, intended for numerical simulation of radio frequency ablation (RFA).  ...  The developed method is a semiautomatic hybrid based on multi-scale vessel enhancement combined with ridge-oriented region growing and skeleton-based postprocessing.  ...  Conclusion We have demonstrated a new, efficient and robust hybrid vessel segmentation for RFA ablation simulation.  ... 
doi:10.1007/978-3-642-15705-9_6 fatcat:l7delph6n5agfmpu3w4xunysce

Automatic Inferior Vena Cava segmentation in contrast-enhanced CT volumes

Thierry Lefevre, Benoit Mory, Roberto Ardon, Javier Sanchez-Castro, Anthony Yezzi
2010 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
This paper presents a novel robust automatic method for the segmentation of the Inferior Vena Cava (IVC) in the proximity of the liver.  ...  In clinical diagnosis and surgery planning, IVC segmentation is essential since it strongly impacts both liver volumetry accuracy and vascularity analysis.  ...  In particular, scale-space theory, medial representations [5] , and propagation methods have helped the development of now well-established algorithms for vessel enhancement [6] and centerline extraction  ... 
doi:10.1109/isbi.2010.5490321 dblp:conf/isbi/LefevreMASY10 fatcat:andsr3tzx5dk7g67wpcljycx4q

Integrating Segmentation Methods From Different Tools Into a Visualization Program Using an Object-Based Plug-In Interface

Felix Fischer, M Alper Selver, Walter Hillen, Cüneyt Guzelis
2010 IEEE Transactions on Information Technology in Biomedicine  
For an informative rendering, these necessitate the usage of different segmentation methods in a single application, and combining/representing the results together in a proper way.  ...  This paper describes the implementation of an interface, which can be used to plug-in and then apply a segmentation method to a medical image series.  ...  The internal analysis of the segmented liver show that FM method does not include contrast-enhanced liver vessels and some parts of the parenchyma, where contrast media leaks from the vessels, in segmentation  ... 
doi:10.1109/titb.2010.2044243 pmid:20403791 fatcat:esl5nqq3zzgevjc4yiyi2wjjay
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