Tanzania
Research Article
A Novel NMF Guided Level-set for DWI Prostate Segmentation
Author(s): Patrick McClure, Fahmi Khalifa, Ahmed Soliman, Mohamed Abou El-Ghar, Georgy Gimelfarb, Adel Elmagraby and Ayman El-BazPatrick McClure, Fahmi Khalifa, Ahmed Soliman, Mohamed Abou El-Ghar, Georgy Gimelfarb, Adel Elmagraby and Ayman El-Baz
Objective: To develop an automated 3D framework for prostate segmentation from diffusion-weighted imaging (DWI).
Methods: The proposed framework integrates level-set deformable model and nonnegative matrix factorization (NMF) techniques. In the proposed framework, the level-set is guided by a novel speed function that is derived using NMF, which extracts meaningful features from a large dimensional feature space. The NMF attributes are calculated using information from the DWI intensity, a probabilistic shape model, and the spatial interactions between prostate voxels. The shape model is constructed using a set of training prostate volumes and is then updated during the segmentation process using an appearance-based method that takes into account both a voxel’s location and its intensity value. The spatial interactions.. Read More»
DOI:
10.4172/jcsb.1000158
Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report