Share Email Print

Proceedings Paper

Estimating the body portion of CT volumes by matching histograms of visual words
Author(s): Johannes Feulner; S. Kevin Zhou; Sascha Seifert; Alexander Cavallaro; Joachim Hornegger; Dorin Comaniciu
Format Member Price Non-Member Price
PDF $17.00 $21.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Being able to automatically determine which portion of the human body is shown by a CT volume image offers various possibilities like automatic labeling of images or initializing subsequent image analysis algorithms. This paper presents a method that takes a CT volume as input and outputs the vertical body coordinates of its top and bottom slice in a normalized coordinate system whose origin and unit length are determined by anatomical landmarks. Each slice of a volume is described by a histogram of visual words: Feature vectors consisting of an intensity histogram and a SURF descriptor are first computed on a regular grid and then classified into the closest visual words to form a histogram. The vocabulary of visual words is a quantization of the feature space by offline clustering a large number of feature vectors from prototype volumes into visual words (or cluster centers) via the K-Means algorithm. For a set of prototype volumes whose body coordinates are known the slice descriptions are computed in advance. The body coordinates of a test volume are computed by a 1D rigid registration of the test volume with the prototype volumes in axial direction. The similarity of two slices is measured by comparing their histograms of visual words. Cross validation on a dataset of 44 volumes proved the robustness of the results. Even for test volumes of ca. 20cm height, the average error was 15.8mm.

Paper Details

Date Published: 27 March 2009
PDF: 8 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72591V (27 March 2009); doi: 10.1117/12.810240
Show Author Affiliations
Johannes Feulner, Univ. Erlangen-Nuremberg (Germany)
S. Kevin Zhou, Siemens Corporate Research, Inc. (United States)
Sascha Seifert, Siemens Corporate Technology (Germany)
Alexander Cavallaro, Imaging Science Institute Erlangen (Germany)
Joachim Hornegger, Univ. Erlangen-Nuremberg (Germany)
Dorin Comaniciu, Siemens Corporate Research, Inc. (United States)

Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

© SPIE. Terms of Use
Back to Top