| Literature DB >> 23286163 |
Ulas Bagci1, Jayaram K Udupa, Jianhua Yao, Daniel J Mollura.
Abstract
This paper presents a novel method for segmenting functional and anatomical structures simultaneously. The proposed method unifies domains of anatomical and functional images (PET-CT), represents them in a product lattice, and performs simultaneous delineation of regions based on a random walk image segmentation. In addition, we propose a simple yet efficient object/background seed localization method, where background and foreground object cues are automatically obtained from PET images and propagated onto the corresponding anatomical images (CT). In our experiments, abnormal anatomies on PET-CT images from human subjects are segmented synergistically by the proposed fully automatic co-segmentation method with high precision (mean DSC of 91.44%) in seconds (avg. 40 seconds).Entities:
Keywords: Joint Segmentation; Object Detection; PET-CT; Random Walk
Mesh:
Year: 2012 PMID: 23286163 PMCID: PMC3539250 DOI: 10.1007/978-3-642-33454-2_57
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv