Conferences related to Corpus Callosum

Back to Top

2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE


2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)

The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging.ISBI 2019 will be the 16th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2019 meeting will continue this tradition of fostering cross fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2018 will be the 15th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2018 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2017 will be the 14th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2017 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI 2016)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forumfor the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2016 willbe the thirteenth meeting in this series. The previous meetings have played a leading role in facilitatinginteraction between researchers in medical and biological imaging. The 2016 meeting will continue thistradition of fostering crossfertilization among different imaging communities and contributing to an integrativeapproach to biomedical imaging across all scales of observation.

  • 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI 2015)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2015 will be the 12th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI 2014)

    The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2014 will be the eleventh meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2014 meeting will continue this tradition of fostering crossfertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.

  • 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013)

    To serve the biological, biomedical, bioengineering, bioimaging and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2011 IEEE 8th International Symposium on Biomedical Imaging (ISBI 2011)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2010 IEEE 7th International Symposium on Biomedical Imaging (ISBI 2010)

    To serve the biological, biomedical, bioengineering, bioimaging, and other technical communities through a quality program of presentations and papers on the foundation, application, development, and use of biomedical imaging.

  • 2009 IEEE 6th International Symposium on Biomedical Imaging (ISBI 2009)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2008 IEEE 5th International Symposium on Biomedical Imaging (ISBI 2008)

    Algorithmic, mathematical and computational aspects of biomedical imaging, from nano- to macroscale. Topics of interest include image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological and statistical modeling. Molecular, cellular, anatomical and functional imaging modalities and applications.

  • 2007 IEEE 4th International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2007)

  • 2006 IEEE 3rd International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2006)

  • 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2004)

  • 2002 1st IEEE International Symposium on Biomedical Imaging: Macro to Nano (ISBI 2002)


2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and severalco-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students, academics and industry researchers.

  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premier annual computer vision event comprising the main conference and several co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry researchers.

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conferenceand 27co-located workshops and short courses. With its high quality and low cost, it provides anexceptional value for students,academics and industry.

  • 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    computer, vision, pattern, cvpr, machine, learning

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. Main conference plus 50 workshop only attendees and approximately 50 exhibitors and volunteers.

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    CVPR is the premiere annual Computer Vision event comprising the main CVPR conference and 27 co-located workshops and short courses. With its high quality and low cost, it provides an exceptional value for students, academics and industry.

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Topics of interest include all aspects of computer vision and pattern recognition including motion and tracking,stereo, object recognition, object detection, color detection plus many more

  • 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Sensors Early and Biologically-Biologically-inspired Vision, Color and Texture, Segmentation and Grouping, Computational Photography and Video

  • 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics, motion analysis and physics-based vision.

  • 2009 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

    Concerned with all aspects of computer vision and pattern recognition. Issues of interest include pattern, analysis, image, and video libraries, vision and graphics,motion analysis and physics-based vision.

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2007 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

  • 2005 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


2019 IEEE 13th International Conference on Semantic Computing (ICSC)

Content Analysis (from contents to semantics)Structured dataimage and videoaudio and speechbig datanatural languagedeep learningDescription and Integration (of data and services)Semantics description languagesontology integrationinteroperabilityUse of Semantics in IT ApplicationsMultimediaIoTcloud computingSDNwearable computingmobile computingsearch enginesquestion answeringroboticsweb servicesecurity and privacyUse of Semantics in Interdisciplinary Applicationsbiomedicinehealthcaremanufacturingengineeringeducationfinanceentertainmentbusinesssciencehumanity¿InterfaceNatural languagemulti-modal

  • 2018 IEEE 12th International Conference on Semantic Computing (ICSC)

    Topics for submission include but are not limited to:Analytics (from contents to semantics) Structured data image and video audio and speech big data natural language deep learningDescription and Integration Semantics description languages ontology integration interoperabilityUse of Semantics in IT Applications Multimedia IoT cloud computing SDN wearable computing mobile computing search engines question answering robotics web service security and privacyUse of Semantics in Interdisciplinary Applications biomedicine healthcare manufacturing engineering education finance entertainment business science humanityInterface Natural language multi-modal

  • 2017 IEEE 11th International Conference on Semantic Computing (ICSC)

    Topics of interest include, but are not limited to:• Analytics (from contents to semantics): Structured data, image and video, audio and speech, big data, natural language, deep learning• Description and Integration: Semantics description languages, ontology integration, interoperability• Use of Semantics in IT Applications: Multimedia, IoT, cloud computing, SDN, wearable computing, mobile computing, search engines, question answering, web services, security and privacy• Use of Semantics in Interdisciplinary Applications such as biomedicine, healthcare, manufacturing, engineering, education, finance, entertainment, business, science, humanity• Interfaces: Natural language, multi-modal

  • 2016 IEEE Tenth International Conference on Semantic Computing (ICSC)

    Semantic Computing (SC) is Computing based on Semantics (“meaning”, "context", “intention”). It addresses all types of resource including data, document, tool, device, process and people. The scope of SC includes analytics, semantics description languages and integration, interfaces, and applications including biomed, IoT, cloud computing, SDN,wearable computing, context awareness, mobile computing, search engines, question answering, big data, multimedia, and services.

  • 2015 IEEE International Conference on Semantic Computing (ICSC)

    Semantics based AnalysisNatural language processingImage and video analysisAudio, music and speech analysisData and web miningBehavior of software, systems, and networksServices and networksSecurityPrivacyAnalysis of social networksSemantic IntegrationMetadata and other description languagesDatabase schema integrationOntology integrationInteroperability and service integrationSemantic programming languages and software engineeringSemantic system design and synthesisApplications using SemanticsBig DataSearch engines and question answeringSemantic web servicesContent-based multimedia retrieval and editingContext-aware networks of sensors, devices and applicationsDevices and applicationsDigital library applicationsMachine translationMusic description and meta-creationMedicine and BiologyGIS systems and architectureSemantic InterfacesNatural language interfacesMultimodal interfaces and mediation technologyHuman centered computing

  • 2014 IEEE International Conference on Semantic Computing (ICSC)

    Semantics based Analysis:Natural language processing,Image and video analysis, Audio, music and speech analysis, Data and web mining,Behavior of software, services and networks, Services and networks,Security,Privacy,Analysis of social networksSemantic Integration,Metadata and other description languages,Database schema integration,Ontology integration,Interoperability and service integration,Semantic programming languages and software engineering,Semantic system design and synthesisApplications using Semantics,Search engines and question answering,Semantic web services,Content-based multimedia retrieval and editing,Context-aware networks of sensors, devices and applications,Digital library applications,Machine translation,Music description and meta-creation,Medicine and Biology,GIS systems and architectureSemantic Interfaces,Natural language interfaces,Multimodal interfaces and mediation technology,Human centered computing

  • 2013 IEEE Seventh International Conference on Semantic Computing (ICSC)

    Semantics based Analysis

  • 2012 IEEE Sixth International Conference on Semantic Computing (ICSC)

    Natural language processing Image and video analysis Audio and speech analysis Data and web mining Behavior of software, services and networks Security Metadata and other description languages Ontology integration Interoperability and service integration Search engines and question answering Semantic web services Content-based multimedia retrieval and editing Context-aware networks of sensors, devices and applications Machine translation Creative art description Medicine and biology Semantic programming languages and software engineering System design and synthesis GIS

  • 2011 IEEE Fifth International Conference on Semantic Computing (ICSC)

    Semantics based Analysis Natural language processing Image and video analysis Audio and speech analysis Data and web mining Behavior of software, services and networks Security Semantic Integration Metadata and other description languages Ontology integration Interoperability and service integration Applications using Semantics Search engines and question answering Semantic web services Content-based multimedia retrieval and editing Context-aware networks of sensors, devices and applications Machine translation Creative art description Medicine and biology Semantic programming languages and software engineering System design and synthesis GIS Semantic Interfaces Natural language interfaces Multimodal interfaces Human centered computing

  • 2010 IEEE Fourth International Conference on Semantic Computing (ICSC)

    The field of Semantic Computing addresses the derivation and matching of the semantics of computational content to that of naturally expressed user intentions in order to retrieve, manage, manipulate or even create content, where "content" maybe anything including video, audio, text, processes, services, hardware, networks, etc.

  • 2009 IEEE Third International Conference on Semantic Computing (ICSC)

    ANALYSIS AND UNDERSTANDING OF CONTENT Natural-language processing Image and video analysis Audio and speech analysis Analysis of structured and semi-structured data Analysis of behavior of software, services, and networks INTEGRATION OF MULTIPLE SEMANTIC REPRESENTATIONS Database schema integration Ontology integration Interoperability and Service Integration SEMANTIC INTERFACES Natural-Language Interface Multimodal Interfaces APPLICATIONS Semantic Web and other search technologies Quest

  • 2008 Second IEEE International Conference on Semantic Computing (ICSC)

    The field of Semantic Computing (SC) brings together those disciplines concerned with connecting the (often vaguely-formulated) intentions of humans with computational content. This connection can go both ways: retrieving, using and manipulating existing content according to user's goals ("do what the user means"); and creating, rearranging, and managing content that matches the author's intentions ("do what the author means").

  • 2007 First IEEE International Conference on Semantic Computing (ICSC)


More Conferences

Periodicals related to Corpus Callosum

Back to Top

Engineering in Medicine and Biology Magazine, IEEE

Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.


Image Processing, IEEE Transactions on

Signal-processing aspects of image processing, imaging systems, and image scanning, display, and printing. Includes theory, algorithms, and architectures for image coding, filtering, enhancement, restoration, segmentation, and motion estimation; image formation in tomography, radar, sonar, geophysics, astronomy, microscopy, and crystallography; image scanning, digital half-toning and display, andcolor reproduction.


Information Technology in Biomedicine, IEEE Transactions on

Telemedicine, teleradiology, telepathology, telemonitoring, telediagnostics, 3D animations in health care, health information networks, clinical information systems, virtual reality applications in medicine, broadband technologies, and global information infrastructure design for health care.


Magnetics, IEEE Transactions on

Science and technology related to the basic physics and engineering of magnetism, magnetic materials, applied magnetics, magnetic devices, and magnetic data storage. The Transactions publishes scholarly articles of archival value as well as tutorial expositions and critical reviews of classical subjects and topics of current interest.


Medical Imaging, IEEE Transactions on

Imaging methods applied to living organisms with emphasis on innovative approaches that use emerging technologies supported by rigorous physical and mathematical analysis and quantitative evaluation of performance.


More Periodicals

Most published Xplore authors for Corpus Callosum

Back to Top

Xplore Articles related to Corpus Callosum

Back to Top

K-means clustering approach for segmentation of corpus callosum from brain magnetic resonance images

International Conference on Circuits, Communication, Control and Computing, 2014

The corpus callosum is one of the most important structures in human brain. Most of the neurological disorders reflect directly or indirectly on the morphological features of Corpus Callosum. The mid-sagittal brain Magnetic Resonance images fully describe the anatomical structure of corpus callosum. Often considered challenging task of segmenting Corpus Callosum from Magnetic Resonance images has proved the importance of ...


Shape-Based Normalization of the Corpus Callosum for DTI Connectivity Analysis

IEEE Transactions on Medical Imaging, 2007

The continuous medial representation (cm-rep) is an approach that makes it possible to model, normalize, and analyze anatomical structures on the basis of medial geometry. Having recently presented a partial differential equation (PDE)-based approach for 3-D cm-rep modeling [1], here we present an equivalent 2-D approach that involves solving an ordinary differential equation. This paper derives a closed form solution ...


An automatic segmentation approach for boundary delineation of corpus callosum based on cell competition

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008

The size and shape of corpus callosum are important indicators for assisting diagnosis of many neurological diseases involving morphological changes of corpus callosum. A new automatic segmentation approach was proposed in this paper for boundary delineation of corpus callosum. The basic idea of the proposed approach was to perform segmentation on the red component of color- coded map of diffusion ...


Corpus callosum thickness estimation using elastic shape matching

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 2015

We present a shape-based approach for calculating the thickness of the corpus callosum. The corpus callosum is delineated from the MRI midsagittal white matter boundary and represented as a parameterized curve consisting of the top and bottom boundaries by a trained expert. The top and bottom boundaries are first represented in a quotient space of open curves, and then elastically ...


Tractography of corpus callosum connections to other brain structures

4th IET International Conference on Advances in Medical, Signal and Information Processing - MEDSIP 2008, 2008

A microstructural damage of corpus callosum (cc) is demonstrated by histological post-mortem study in many neurodegenerative diseases, while at present the only in-vivo investigation is provided by DTI and tractography. However, the lesional load which often accompanies these pathologies can severely limit the image registration steps necessary for reliable DTI computation. A technical study for specific cc investigation and for ...


More Xplore Articles

Educational Resources on Corpus Callosum

Back to Top

IEEE.tv Videos

No IEEE.tv Videos are currently tagged "Corpus Callosum"

IEEE-USA E-Books

  • K-means clustering approach for segmentation of corpus callosum from brain magnetic resonance images

    The corpus callosum is one of the most important structures in human brain. Most of the neurological disorders reflect directly or indirectly on the morphological features of Corpus Callosum. The mid-sagittal brain Magnetic Resonance images fully describe the anatomical structure of corpus callosum. Often considered challenging task of segmenting Corpus Callosum from Magnetic Resonance images has proved the importance of studies on Corpus Callosum segmentation. In this paper, a K-means clustering algorithm is proposed for segmentation of the region of Corpus Callosum. The results of segmentation can be used further for feature extraction and classification for medical diagnosis.

  • Shape-Based Normalization of the Corpus Callosum for DTI Connectivity Analysis

    The continuous medial representation (cm-rep) is an approach that makes it possible to model, normalize, and analyze anatomical structures on the basis of medial geometry. Having recently presented a partial differential equation (PDE)-based approach for 3-D cm-rep modeling [1], here we present an equivalent 2-D approach that involves solving an ordinary differential equation. This paper derives a closed form solution of this equation and shows how Pythagorean hodograph curves can be used to express the solution as a piecewise polynomial function, allowing efficient and robust medial modeling. The utility of the approach in medical image analysis is demonstrated by applying it to the problem of shape-based normalization of the midsagittal section of the corpus callosum. Using diffusion tensor tractography, we show that shape- based normalization aligns subregions of the corpus callosum, defined by connectivity, more accurately than normalization based on volumetric registration. Furthermore, shape-based normalization helps increase the statistical power of group analysis in an experiment where features derived from diffusion tensor tractography are compared between two cohorts. These results suggest that cm-rep is an appropriate tool for normalizing the corpus callosum in white matter studies.

  • An automatic segmentation approach for boundary delineation of corpus callosum based on cell competition

    The size and shape of corpus callosum are important indicators for assisting diagnosis of many neurological diseases involving morphological changes of corpus callosum. A new automatic segmentation approach was proposed in this paper for boundary delineation of corpus callosum. The basic idea of the proposed approach was to perform segmentation on the red component of color- coded map of diffusion tensor magnetic resonance image (MR-DTI). The boundary of corpus callosum was delineated in two phases. Firstly, a rough boundary surrounding corpus callosum was derived by using a built-in contour function in Matlab. Then, this cell competition algorithm was applied to the area inside the rough boundary derived in the first phase. The proposed segmentation approach has been evaluated and compared to the Chan and Vese level set method by using the MR-DTI images of a healthy volunteer and a systemic lupus erythematorsus (SLE) patient. The implementation results showed that the proposed approach could delineate the boundaries of corpus callosum reasonably well for both cases, whereas the Chan and Vese level set method failed to catch the weak edge for the SLE patient.

  • Corpus callosum thickness estimation using elastic shape matching

    We present a shape-based approach for calculating the thickness of the corpus callosum. The corpus callosum is delineated from the MRI midsagittal white matter boundary and represented as a parameterized curve consisting of the top and bottom boundaries by a trained expert. The top and bottom boundaries are first represented in a quotient space of open curves, and then elastically matched under a geometric framework that generates an optimal correspondence between their “shapes”. This matching is computed using a geodesic between shape representations that are invariant to reparameterizations of the curves. Callosal thickness is given by the distance between matched points on the top and bottom boundaries. Our results within a healthy population of N = 96 subjects show significant differences in callosal thickness computed using elastic matching compared to the direct Euclidean approach.

  • Tractography of corpus callosum connections to other brain structures

    A microstructural damage of corpus callosum (cc) is demonstrated by histological post-mortem study in many neurodegenerative diseases, while at present the only in-vivo investigation is provided by DTI and tractography. However, the lesional load which often accompanies these pathologies can severely limit the image registration steps necessary for reliable DTI computation. A technical study for specific cc investigation and for the enhancement of main tracts connecting cc and other brain structures is presented, analyzing 5 subjects with different lesional loads. Atlas of 116 brain structures and segmented cc, derived from high-resolution-Tl images, are coregistered onto DTI directly or by 2 passages. For 2 patients with high lesional load, the 2- steps coregistration gives best results, indeed mutual information between Tl and DTI is higher for Tl coregistered with 2 steps than directly. Volumes of entire cc, portions of cc, brain structures connected to cc are computed. Also DTI-derived indices (MD, FA) are computed for the same structures. For all the subjects, the volume of cc anterior portion was less than posterior one; for 4 subjects FA of anterior bundles were less then FA of posteriors. The parameters of fiber tracking allowed to extract bundles connecting cc to other brain structures and to compute indices of their microstructural integrity, within the limits, in terms of acquisition time, of a clinically feasible protocol.

  • Statistical Shape Analysis of the Corpus Callosum in Subtypes of Autism

    Brain imaging studies of the corpus callosum (CC) in autism have yielded inconsistent results. In this paper, we explore the three-dimensional profile of CC abnormalities in autism. The CC is segmented from mid-sagittal MRI and four adjacent slices on both sides, using our newly developed semiautomatic method. A subsequent contour stitching is performed to create the 3D surface of the CC, and the point correspondence problem can be simplified by our segmentation scheme. After alignment, differences from each surface to a template are computed to create a signed distance map of each subject. The group difference in the distance map is analyzed using two sample t-test, which results in a significance map. The statistical results reveal significant difference between patients and controls in the body of the CC.

  • Describing morphological changes of Corpus Callosum via shape grammar based approach

    Despite modern imaging technologies, problems are faced in quantitative brain morphology studies. Since the structural and functional organization of the human brain is complex, advanced methods are needed. Current methods are incapable of detecting complete shape anomalies. Moreover, the rapidly increasing volume of image data forces development of image analysis methodologies that can be processed fast and locally. All of these requirements create the need for an advanced shape analysis technique to characterize brain morphology. Solutions to the defined problems while monitoring the effects of neurodegenerative diseases on the Corpus Callosum morphology are being investigated in this study via shape grammars.

  • Atrophy analysis of corpus callosum in Alzheimer brain MR images using anisotropic diffusion filtering and level sets

    In this work, an attempt has been made to analyze the atrophy of Corpus Callosum (CC) in Alzheimer brain magnetic resonance images using anisotropic diffusion filtering and modified distance regularized level set method. Anisotropic diffusion filtering is used as preprocessing to obtain the edge map. The modified distance regularized level set method is employed to segment CC using this edge map. Geometric features are extracted from the segmented CC and are analyzed. Results show that anisotropic diffusion filtering is able to extract the edge map with high contrast and continuous boundaries. Modified distance regularized level set method could perform the segmentation of CC in both normal and Alzheimer images. The extracted geometric features such as minor axis, Euler number and solidity are able to demarcate the Alzheimer subjects from the control normals. As atrophy of CC is closely associated with the pathology, this study seems to be clinically useful.

  • Abnormalities in MRI traits of corpus callosum in autism subtype

    A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this paper, we apply advanced computational techniques to extract 3D models of the corpus callosum (CC) and subsequently analyze the volumetric deficit of the total CC and its five sub-regions in a homogeneous group of autistic children. Moreover, we explore new MRI traits based on the oriented bounding rectangle of the CC, which are the length, width and aspect ratio of the bounding rectangle. These measurements as well as the volumes are compared between patients and controls using t-tests. The results reveal significant reduction in all sub-regions of the CC and some MRI traits in the patients.

  • Shape modeling of the corpus callosum

    A novel approach for shape modeling of the corpus callosum (cc) is introduced where the contours of the cc are extracted by image/volume segmentation, and a Bezier curve is used to connect the vertices of the sampled contours, generating a parametric polynomial representation. These polynomials are shown to maintain the characteristics of the original cc, thus are suitable for classification of populations. The Bernstein polynomials are used in fitting the Bezier curves. The coefficients of the Bernstein polynomials are shown to capture the geometric features of the cc, and are able to describe deformations. We use these coefficients, in conjunction with the Fourier Descriptors and other features, to discriminate between autistic and normal brains. The approach is tested on T1-weighted MRI scans of 16 normal and 22 autistic subjects and shows its ability to provide perfect classification, suggesting that the approach is worth investigating on a larger population with the hope of providing early identification and intervention of autism using neuroimaging.



Standards related to Corpus Callosum

Back to Top

No standards are currently tagged "Corpus Callosum"


Jobs related to Corpus Callosum

Back to Top