View in EDS HTML Full Text PDF Full Text

Accelerating 3D medical volume segmentation using GPUs.

Saved in:
Bibliographic Details
Title: Accelerating 3D medical volume segmentation using GPUs.
Authors: Al-Ayyoub, Mahmoud1 maalshbool@just.edu.jo, Alzu'bi, Shadi2 smalzubi@zuj.edu.jo, Jararweh, Yaser1 yijararweh@just.edu.jo, Shehab, Mohammed A.1 mohammed_shihab@daad-alumni.de, Gupta, Brij B.3 gupta.brij@gmail.com
Source: Multimedia Tools & Applications. Feb2018, Vol. 77 Issue 4, p4939-4958. 20p.
Subjects: Product usage segmentation, Fuzzy algorithms, Graphics processing units, Diagnostic imaging, Parallel programming
Abstract: Medical images have an undeniably integral role in the process of diagnosing and treating of a very large number of ailments. Processing such images (for different purposes) can significantly improve the efficiency and effectiveness of this process. The first step in many medical image processing applications is segmentation, which is used to extract the Region of Interest (ROI) from a given image. Due to its effectiveness, a very popular segmentation algorithm is the Fuzzy C-Means (FCM) algorithm. However, FCM takes a long processing time especially for 3D model. This problem can be solved by utilizing parallel programming using Graphics Processing Unit (GPU). In this paper, a hybrid parallel implementation of FCM for extracting volume object from medical DICOM files has been proposed. The proposed algorithm improves the performance 5× compared with the sequential version. [ABSTRACT FROM AUTHOR]
Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 128053891
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Accelerating 3D medical volume segmentation using GPUs.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Al-Ayyoub%2C+Mahmoud%22">Al-Ayyoub, Mahmoud</searchLink><relatesTo>1</relatesTo><i> maalshbool@just.edu.jo</i><br /><searchLink fieldCode="AR" term="%22Alzu'bi%2C+Shadi%22">Alzu'bi, Shadi</searchLink><relatesTo>2</relatesTo><i> smalzubi@zuj.edu.jo</i><br /><searchLink fieldCode="AR" term="%22Jararweh%2C+Yaser%22">Jararweh, Yaser</searchLink><relatesTo>1</relatesTo><i> yijararweh@just.edu.jo</i><br /><searchLink fieldCode="AR" term="%22Shehab%2C+Mohammed+A%2E%22">Shehab, Mohammed A.</searchLink><relatesTo>1</relatesTo><i> mohammed_shihab@daad-alumni.de</i><br /><searchLink fieldCode="AR" term="%22Gupta%2C+Brij+B%2E%22">Gupta, Brij B.</searchLink><relatesTo>3</relatesTo><i> gupta.brij@gmail.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Multimedia+Tools+%26+Applications%22">Multimedia Tools & Applications</searchLink>. Feb2018, Vol. 77 Issue 4, p4939-4958. 20p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Product+usage+segmentation%22">Product usage segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+algorithms%22">Fuzzy algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Graphics+processing+units%22">Graphics processing units</searchLink><br /><searchLink fieldCode="DE" term="%22Diagnostic+imaging%22">Diagnostic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Parallel+programming%22">Parallel programming</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Medical images have an undeniably integral role in the process of diagnosing and treating of a very large number of ailments. Processing such images (for different purposes) can significantly improve the efficiency and effectiveness of this process. The first step in many medical image processing applications is segmentation, which is used to extract the Region of Interest (ROI) from a given image. Due to its effectiveness, a very popular segmentation algorithm is the Fuzzy C-Means (FCM) algorithm. However, FCM takes a long processing time especially for 3D model. This problem can be solved by utilizing parallel programming using Graphics Processing Unit (GPU). In this paper, a hybrid parallel implementation of FCM for extracting volume object from medical DICOM files has been proposed. The proposed algorithm improves the performance 5× compared with the sequential version. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Multimedia Tools & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=128053891
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11042-016-4218-0
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 4939
    Subjects:
      – SubjectFull: Product usage segmentation
        Type: general
      – SubjectFull: Fuzzy algorithms
        Type: general
      – SubjectFull: Graphics processing units
        Type: general
      – SubjectFull: Diagnostic imaging
        Type: general
      – SubjectFull: Parallel programming
        Type: general
    Titles:
      – TitleFull: Accelerating 3D medical volume segmentation using GPUs.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Al-Ayyoub, Mahmoud
      – PersonEntity:
          Name:
            NameFull: Alzu'bi, Shadi
      – PersonEntity:
          Name:
            NameFull: Jararweh, Yaser
      – PersonEntity:
          Name:
            NameFull: Shehab, Mohammed A.
      – PersonEntity:
          Name:
            NameFull: Gupta, Brij B.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 02
              Text: Feb2018
              Type: published
              Y: 2018
          Identifiers:
            – Type: issn-print
              Value: 13807501
          Numbering:
            – Type: volume
              Value: 77
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Multimedia Tools & Applications
              Type: main
ResultId 1