Assessment of similarity indices to quantify segmentation accuracy of scaffold images for tissue engineering

Srinivasan Rajagopalan; Richard Robb

doi:10.1117/12.594654

29 April 2005 Assessment of similarity indices to quantify segmentation accuracy of scaffold images for tissue engineering

Srinivasan Rajagopalan, Richard Robb

Author Affiliations +

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.594654
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

Existing similarity metrics to compare the accuracy of n-Dimensional image segmentation with the corresponding ground truth is restricted to a limited set of volume fractions which, by themselves, lack robustness. This paper introduces a comprehensive list of linear and non-linear similarity measures widely used in such diverse fields as ecology, toxicology and patent trending. These metrics based on the binary "absence/presence" data were computed for assessing the delineation of tissue engineering scaffold images into porous and polymeric space using a wide variety of thresholding techniques.

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Srinivasan Rajagopalan and Richard Robb "Assessment of similarity indices to quantify segmentation accuracy of scaffold images for tissue engineering", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.594654

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