Breast Lesion Segmentation Software For Dce-Mri: An Open Source Gpgpu Based Optimization

O. Zavala-Romero*, A. Meyer-Baese, M.B.I. Lobbes

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Efficient algorithms for segmentation are a key step in medical imaging and of fundamental importance in computer aided diagnosis of breast cancer for: diagnostics, evaluation of neoadjuvant therapy, or surgery. With the advance of high resolution images, as 3D dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) images, the computational cost of segmentation methods has become more expensive as the amount of data has grown. In this work, a segmentation method for breast cancer lesions in DCE-MRI images based on the active contour without edges (ACWE) algorithm and using parallel programming with general purpose computing on graphics processing units (GPGPUs) is presented. The performance of the segmentation algorithm is evaluated on a set of 32 breast DCE-MRI cases in terms of speedup, and compared to non-GPU based approaches. A high speedup (40 or more) is obtained for high resolution images, providing real-time outputs.
Original languageEnglish
Title of host publication2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018)
PublisherIEEE
Pages211-215
Number of pages5
ISBN (Print)9781538636367
DOIs
Publication statusPublished - 2018
Event15th IEEE International Symposium on Biomedical Imaging (ISBI) - DC
Duration: 4 Apr 20187 Apr 2018

Publication series

SeriesIEEE International Symposium on Biomedical Imaging
ISSN1945-7928

Symposium

Symposium15th IEEE International Symposium on Biomedical Imaging (ISBI)
Period4/04/187/04/18

Keywords

  • OpenCL
  • Active Contours
  • Breast image segmentation

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