Accelerating 3D medical volume segmentation using GPUs.
Saved in:
| 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.
Login for full access.
|
|
| 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] |
|---|---|
| ISSN: | 13807501 |
| DOI: | 10.1007/s11042-016-4218-0 |
