Limits on estimating the width of thin tubular structures in 3D images.
This work studies limits on estimating the width of thin tubular structures in 3D images. Based on nonlinear estimation theory we analyze the minimal stochastic error of estimating the width. Given a 3D analytic model of the image intensities of tubular structures, we derive a closed-form expression for the Cramér-Rao bound of the width estimate under image noise. We use the derived lower bound as a benchmark and compare it with three previously proposed accuracy limits for vessel width estimation. Moreover, by experimental investigations we demonstrate that the derived lower bound can be achieved by fitting a 3D parametric intensity model directly to the image data.
Wörz
Stefan
S
University of Heidelberg, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany s.woerz@dkfz.de
Rohr
Karl
K
D000465:Algorithms; D001158:Arteries / Q000166:cytology*; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity