Abstract:
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Purpose: Our goal is to evaluate the performance of a segmentation algorithm
to remove bone from head/neck CT Angiography by 2 radiologists and 2 evaluation
methods.
Methods and Materials: CT Angiography data sets of the head/neck region were
acquired using different configurations of CT scanners (GE Medical Systems,
Milwaukee, USA). The algorithm loads each case as a series of axial slices for
processing. An automatic partition algorithm is applied to identify the skull
base region and create separate sub-volumes. The sub-volumes are processed
separately and merged together using a constrained region growing. The
segmented models are reviewed by two different radiologists. The first
evaluation is performed using static panels of the 3-D models displayed using
volume rendering and MIP modes. A second evaluation is performed by the use of
a VTK based interactive evaluation tool. The tool allows the user to scroll
through the slices and select a suitable window/level setting. The original and
the segmented data both be examined. The 3-D vessel model can be rotated and
zoom in/out to allow the user a 360 degree viewing capability. All the
radiologists use a set of questions as a guide to evaluate the algorithm
performance and determine a rating. The rating is on a 1-5 scale, going from
worst to best. While using the VTK evaluation tool, the questions are built
into the GUI where the radiologist can click on the rating number. The mean
rating is compared across the radiologists using the static panels and the 3-D
tool.
Results: The overall mean rating (1: worst, 5: best) of this bone segmentation
algorithm by radiologist A was 3.52 (Std. Dev. 0.68) using panels of 2-D VR and
MIP images and rated 3.13 (Std. Dev. 0.42) using the interactive 3-D evaluation
tool. The ratings from radiologist B using static 2-D panels was 3.56 (Std.
Dev. 1.27) and the ratings from using the 3-D evaluation tool was 3.58 (Std.
Dev.: 0.69). For Case #2, radiologist A rated it 4.17 (Std. Dev 0.75) from 2-D
panels and 3.5 (Std. Dev 1.05) using the 3-D interactive tool. For the same
case, radiologist B rated it 4.17 (Std. Dev. 1.13) from 2-D panels and rated it
3.67 (Std. Dev. 1.03) using the 3-D tool.
Conclusion: Six head/neck CT Angiography data sets were used to evaluate a bone
segmentation algorithm. The segmented models were reviewed by 2 radiologists
using 2-D static panels. They also used a VTK based tool that allowed minimal
3-D interactivity. There was no difference between the ratings obtained from
the 2 radiologists for these cases, as well as using the 2 different evaluation
techniques. (S.S., R.M. and V.K. are employees of GE Corporation; A.K. has a
research agreement with GE.)
Questions about this event email: srikanth.suryanarayanan@ge.com
Suryanarayananan PhD, S,
Evaluation of the Performance of a Bone Segmentation Algorithm for Head/Neck CTA. Radiological Society of North America 2003 Scientific Assembly and Annual Meeting, November 30 - December 5, 2003 ,Chicago IL.
http://archive.rsna.org/2003/3107374.html
