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

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