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Bidirectional local distance measure for comparing segmentations
Author(s) -
Kim Hak Soo,
Park Samuel B.,
Lo Simon S.,
Monroe James I.,
Sohn Jason W.
Publication year - 2012
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4754802
Subject(s) - measure (data warehouse) , surface (topology) , point (geometry) , distance transform , mathematics , critical distance , distance measures , minimum distance , distance measurement , signed distance function , geometry , algorithm , computer vision , artificial intelligence , computer science , statistics , physics , image (mathematics) , database , sound power , acoustics , sound (geography)
Purpose: To accurately quantify the local difference between two contour surfaces in two‐ or three‐dimensional space, a new, robust point‐to‐surface distance measure is developed. Methods: To evaluate and visualize the local surface differences, point‐to‐surface distance measures have been utilized. However, previously well‐known point‐to‐surface distance measures have critical shortfalls. Previous distance measures termed “normal distance (ND),” “radial distance,” or “minimum distance (MD)” can report erroneous results at certain points where the surfaces under comparison meet certain conditions. These skewed results are due to the monodirectional characteristics of these methods. ComGrad distance was also proposed to overcome asymmetric characteristics of previous point‐to‐surface distance measures, but their critical incapability of dealing with a fold or concave contours. In this regard, a new distance measure termed the bidirectional local distance (BLD) is proposed which minimizes errors of the previous methods by taking into account the bidirectional characteristics with the forward and backward directions. BLD measure works through three steps which calculate the maximum value between the forward minimum distance (FMinD) and the backward maximum distance (BMaxD) at each point. The first step calculates the FMinD as the minimum distance to the test surface from a point, p ref on the reference surface. The second step involves calculating the minimum distances at every point on the test surface to the reference surface. During the last step, the BMaxD is calculated as the maximum distance among the minimum distances found at p ref on the reference surface. Tests are performed on two‐ and three‐dimensional artificial contour sets in comparison to MD and ND measure techniques. Three‐dimensional tests performed on actual liver and head‐and‐neck cancer patients. Results: The proposed BLD measure provides local distances between segmentations, even in situations where ND, MD, or ComGrad measures fail. In particular, the standard deviation measure is not distorted at certain geometries where ND, MD, and ComGrad measures report skewed results. Conclusions: The proposed measure provides more reliable statistics on contour comparisons. From the statistics, specific local and global distances can be extracted. Bidirectional local distance is a reliable distance measure in comparing two‐ or three‐dimensional organ segmentations.