The Experts below are selected from a list of 3915 Experts worldwide ranked by ideXlab platform

Michael A Silver - One of the best experts on this subject based on the ideXlab platform.

  • functional mapping of the magnocellular and parvocellular subdivisions of human lgn
    NeuroImage, 2014
    Co-Authors: Rachel N Denison, An T Vu, Essa Yacoub, David A Feinberg, Michael A Silver
    Abstract:

    article i nfo The magnocellular (M) and parvocellular (P) subdivisions of primate LGN are known to process complementary types of visual stimulus information, but a method for noninvasively defining these subdivisions in humans has provenelusive. As a result, thefunctional rolesof these subdivisions inhumans havenot been investigated phys- iologically. To functionally map the M and P subdivisions of human LGN, we used high-resolution fMRI at high field (7 T and 3 T) together with a combination of spatial, temporal, luminance, and chromatic stimulus manip- ulations. We found that stimulus factors that differentially drive magnocellular and parvocellular neurons in pri- mate LGN also elicit differential BOLD fMRI responses in human LGN and that these responses exhibit a spatial organization consistent with theknown anatomicalorganization of theM andP subdivisions. In test-retest stud- ies, the relative responses of Individual Voxels to M-type and P-type stimuli were reliable across scanning ses- sions on separate days and across sessions at different field strengths. The ability to functionally identify magnocellular and parvocellular regions of human LGN with fMRI opens possibilities for investigating the func- tions of these subdivisions in human visual perception, in patient populations with suspected abnormalities in one of these subdivisions, and in visual cortical processing streams arising from parallel thalamocortical pathways.

  • Functional mapping of the magnocellular and parvocellular subdivisions of human LGN.
    NeuroImage, 2014
    Co-Authors: Rachel N Denison, An T Vu, Essa Yacoub, David A Feinberg, Michael A Silver
    Abstract:

    The magnocellular (M) and parvocellular (P) subdivisions of primate LGN are known to process complementary types of visual stimulus information, but a method for noninvasively defining these subdivisions in humans has proven elusive. As a result, the functional roles of these subdivisions in humans have not been investigated physiologically. To functionally map the M and P subdivisions of human LGN, we used high-resolution fMRI at high field (7 T and 3 T) together with a combination of spatial, temporal, luminance, and chromatic stimulus manipulations. We found that stimulus factors that differentially drive magnocellular and parvocellular neurons in primate LGN also elicit differential BOLD fMRI responses in human LGN and that these responses exhibit a spatial organization consistent with the known anatomical organization of the M and P subdivisions. In test-retest studies, the relative responses of Individual Voxels to M-type and P-type stimuli were reliable across scanning sessions on separate days and across sessions at different field strengths. The ability to functionally identify magnocellular and parvocellular regions of human LGN with fMRI opens possibilities for investigating the functions of these subdivisions in human visual perception, in patient populations with suspected abnormalities in one of these subdivisions, and in visual cortical processing streams arising from parallel thalamocortical pathways.

Bjørn Fortling - One of the best experts on this subject based on the ideXlab platform.

  • The Advantages of Volume Rendering in Three-Dimensional Endosonography of the Anorectum
    Diseases of the Colon & Rectum, 2007
    Co-Authors: Giulio A. Santoro, Bjørn Fortling
    Abstract:

    Anorectal diseases require imaging for proper case management. At present, endoanal ultrasonography and endorectal ultrasonography have become important parts of diagnostic workup of patients with fecal incontinence, perianal fistulas, and rectal cancer and provides sufficient information for clinical decision-making in many cases. However, with the currently available ultrasonographic equipment and techniques, a good deal of relevant information may remain hidden. The advent of high-resolution three-dimensional endoluminal ultrasound, constructed from a synthesis of standard two-dimensional cross-sectional images, and of “Volume Render Mode,” a technique to analyze information inside a three-dimensional volume by digitally enhancing Individual Voxels, promises to revolutionize diagnosis of pelvic floor disorders. By use of the different postprocessing display parameters, the volume-rendered image provides better visualization performance when there are not large differences in the signal levels of pathologic structures compared with surrounding tissues. The anatomic structures in the pelvis, the axial and longitudinal extension of anal sphincter defects, the anatomy of the fistulous tract in complex perianal sepsis, and the presence of slight or massive submucosal invasion in early rectal cancer may be imaged in greater detail. This additional information will bring an improvement for both planning and conduct of surgical procedures.

Paul Suetens - One of the best experts on this subject based on the ideXlab platform.

  • An information theoretic approach for non-rigid image registration using voxel class probabilities
    Medical Image Analysis, 2006
    Co-Authors: Emiliano D'agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens
    Abstract:

    We propose a multimodal free-form registration algorithm that matches voxel class labels rather than image intensities. Individual Voxels are displaced such as to minimize the Kullback-Leibler distance between the actual and ideal joint probability distribution of voxel class labels, which are assigned to each image Individually by a previous segmentation process. We evaluate the performance of the method for inter-subject brain registration with simulated deformations, using a viscous fluid model for regularization. The root mean square difference between recovered and ground truth deformations is smaller than 1 voxel.

  • WBIR - An Information Theoretic Approach for Non-rigid Image Registration Using Voxel Class Probabilities
    Biomedical Image Registration, 2003
    Co-Authors: Emiliano D'agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens
    Abstract:

    We propose a multimodal free-form registration algorithm that matches voxel class labels rather than image intensities. Individual Voxels are displaced such as to minimize the Kullback-Leibler distance between the actual and ideal joint probability distribution of voxel class labels, which are assigned to each image Individually by a previous segmentation process. We evaluate the performance of the method for inter-subject brain registration with simulated deformations, using a viscous fluid model for regularization. The root mean square difference between recovered and ground truth deformations is smaller than 1 voxel.

  • MICCAI (2) - An Information Theoretic Approach for Non-rigid Image Registration Using Voxel Class Probabilities
    Lecture Notes in Computer Science, 2003
    Co-Authors: Emiliano D'agostino, Frederik Maes, Dirk Vandermeulen, Paul Suetens
    Abstract:

    We propose a multimodal free-form registration algorithm that matches voxel class labels rather than image intensities. Individual Voxels are displaced such as to minimize the Kullback-Leibler distance between the actual and ideal joint probability distribution of voxel class labels, which are assigned to each image Individually by a previous segmentation process. We evaluate the performance of the method for inter-subject brain registration with simulated deformations, using a viscous fluid model for regularization. The root mean square difference between recovered and ground truth deformations is smaller than 1 voxel.

Giulio A. Santoro - One of the best experts on this subject based on the ideXlab platform.

  • The Advantages of Volume Rendering in Three-Dimensional Endosonography of the Anorectum
    Diseases of the Colon & Rectum, 2007
    Co-Authors: Giulio A. Santoro, Bjørn Fortling
    Abstract:

    Anorectal diseases require imaging for proper case management. At present, endoanal ultrasonography and endorectal ultrasonography have become important parts of diagnostic workup of patients with fecal incontinence, perianal fistulas, and rectal cancer and provides sufficient information for clinical decision-making in many cases. However, with the currently available ultrasonographic equipment and techniques, a good deal of relevant information may remain hidden. The advent of high-resolution three-dimensional endoluminal ultrasound, constructed from a synthesis of standard two-dimensional cross-sectional images, and of “Volume Render Mode,” a technique to analyze information inside a three-dimensional volume by digitally enhancing Individual Voxels, promises to revolutionize diagnosis of pelvic floor disorders. By use of the different postprocessing display parameters, the volume-rendered image provides better visualization performance when there are not large differences in the signal levels of pathologic structures compared with surrounding tissues. The anatomic structures in the pelvis, the axial and longitudinal extension of anal sphincter defects, the anatomy of the fistulous tract in complex perianal sepsis, and the presence of slight or massive submucosal invasion in early rectal cancer may be imaged in greater detail. This additional information will bring an improvement for both planning and conduct of surgical procedures.

Flemming Friche Rodler - One of the best experts on this subject based on the ideXlab platform.

  • Wavelet Based 3D Compression for Very Large Volume Data Supporting Fast Random Access
    BRICS Report Series, 1999
    Co-Authors: Flemming Friche Rodler
    Abstract:

    We propose a wavelet based method for compressing volumetric data with little loss in quality. The method supports fast random access to Individual Voxels within the compressed volume. Such a method is important since storing and visualising very large volumes impose heavy demands on internal memory and external storage facilities making it accessible only to users with huge and expensive computers. This problem is not likely to become less in the future. Experimental results on the CT dataset of the Visible Human have shown that our method provides very high compression rates with fairly fast random access.

  • Pacific Conference on Computer Graphics and Applications - Wavelet based 3D compression with fast random access for very large volume data
    Proceedings. Seventh Pacific Conference on Computer Graphics and Applications (Cat. No.PR00293), 1
    Co-Authors: Flemming Friche Rodler
    Abstract:

    In this paper we propose a wavelet based method for compressing volumetric data with little loss in quality allowing fast random access to Individual Voxels within the volume. Such a method is important since storing and visualising very large volumes impose heavy demands on internal memory and external storage facilities, a problem not likely to become less in the future, making it accessible only to users with huge and expensive computers. Experimental results on the CT dataset of the Visible Human have shown that our method provides very high compression rates with fairly fast random access.