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Orientation-Sensitive Overlap Measures for the Validation of Medical Image Segmentations

Papastylianou, Tasos and Dall’ Armellina, Erica and Grau, Vicente (2016) Orientation-Sensitive Overlap Measures for the Validation of Medical Image Segmentations. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2016), 2016-10-17 - 2016-10-21, Athens, Greece.

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Abstract

Validation is a key concept in the development and assessment of medical image segmentation algorithms. However, the proliferation of modern, non-deterministic segmentation algorithms has not been met by an equivalent improvement in validation strategies. In this paper, we briefly examine the state of the art in validation, and propose an improved validation method for non-deterministic segmentations, showing that it improves validation precision and accuracy on both synthetic and clinical sets, compared to more traditional (but still widely used) methods and state of the art.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Papastylianou T., Dall’ Armellina E., Grau V. (2016) Orientation-Sensitive Overlap Measures for the Validation of Medical Image Segmentations. In: Ourselin S., Joskowicz L., Sabuncu M., Unal G., Wells W. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2016. MICCAI 2016. Lecture Notes in Computer Science, vol 9901
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > R Medicine (General)
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 18 Jun 2019 14:53
Last Modified: 18 Jun 2019 15:15
URI: http://repository.essex.ac.uk/id/eprint/24856

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