NDLI: Discriminative Segmentation-Based Evaluation Through Shape Dissimilarity

Content Provider	IEEE Xplore Digital Library
Author	Konukoglu, E. Glocker, B. Dong Hye Ye Criminisi, A. Pohl, K.M.
Copyright Year	1982
Abstract	Segmentation-based scores play an important role in the evaluation of computational tools in medical image analysis. These scores evaluate the quality of various tasks, such as image registration and segmentation, by measuring the similarity between two binary label maps. Commonly these measurements blend two aspects of the similarity: pose misalignments and shape discrepancies. Not being able to distinguish between these two aspects, these scores often yield similar results to a widely varying range of different segmentation pairs. Consequently, the comparisons and analysis achieved by interpreting these scores become questionable. In this paper, we address this problem by exploring a new segmentation-based score, called normalized Weighted Spectral Distance (nWSD), that measures only shape discrepancies using the spectrum of the Laplace operator. Through experiments on synthetic and real data we demonstrate that nWSD provides additional information for evaluating differences between segmentations, which is not captured by other commonly used scores. Our results demonstrate that when jointly used with other scores, such as Dice's similarity coefficient, the additional information provided by nWSD allows richer, more discriminative evaluations. We show for the task of registration that through this addition we can distinguish different types of registration errors. This allows us to identify the source of errors and discriminate registration results which so far had to be treated as being of similar quality in previous evaluation studies.
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Nuclear and Plasma Sciences Society IEEE Signal Processing Society IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society
Page Count	12
File Size	1383062
Starting Page	2278
Ending Page	2289
File Format	PDF
ISSN	02780062
Volume Number	31
Issue Number	12
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-12-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Image segmentation Eigenvalues and eigenfunctions High definition video Laplace equations Accuracy Geometry spectral distance Accuracy assessment evaluation image registration image segmentation Laplace operators overlap measures shape dissimilarity
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Radiological and Ultrasound Technology Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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