Comparing axial CT slices in quantized N-dimensional SURF descriptor space to estimate the visible body region

In this paper, a method is described to automatically estimate the visible body region of a computed tomography (CT) volume image. In order to quantify the body region, a body coordinate (BC) axis is used that runs in longitudinal direction. Its origin and unit length are patient-specific and depend on anatomical landmarks. The body region of a test volume is estimated by registering it only along the longitudinal axis to a set of reference CT volume images with known body coordinates. During these 1-D registrations, an axial image slice of the test volume is compared to an axial slice of a reference volume by extracting a descriptor from both slices and measuring the similarity of the descriptors. A slice descriptor consists of histograms of visual words. Visual words are code words of a quantized feature space and can be thought of as classes of image patches with similar appearance. A slice descriptor is formed by sampling a slice on a regular 2-D grid and extracting a Speeded Up ...

• Type: Journal
• Year: 2011
• Where: CMIG
• Authors: Johannes Feulner, Shaohua Kevin Zhou, Elli Angelopoulou, Sascha Seifert, Alexander Cavallaro, Joachim Hornegger, Dorin Comaniciu
• Keywords: Anatomical Landmarks, CMIG 2011, Distributed And Parallel Computing, Image Analysis Algorithms, Medical Image Databases