A formal method for selecting evaluation metrics for image segmentation

Taha, Abdel Aziz (Vienna University of Technology) ; Hanbury, Allan (Vienna University of Technology) ; Jiménez del Toro, Oscar Alfonso (University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis))

Evaluating the quality of segmentations is an important process in image processing, especially in the medical domain. Many evaluation metrics have been used in evaluating segmentation. There exists no formal way to choose the most suitable metric(s) for a particular segmentation task and/or particular data. In this pa- per we propose a formal method for choosing the most suitable metrics for evaluating the quality of segmenta- tions with respect to ground truth segmentations. The proposed method depends on measuring the bias of metrics towards/against the properties of the the seg- mentations being evaluated. We firstly demonstrate how metrics can have bias towards/against particular properties and then we propose a general method for ranking metrics according to their overall bias. We fi- nally demonstrate for 3D medical image segmentations that ranking produced using metrics with low overall bias strongly correlate with manual rankings done by an expert.


Mots-clés:
Type de conférence:
full paper
Faculté:
Economie et Services
Ecole:
HEG VS HES-SO Valais-Wallis - Haute Ecole de Gestion & Tourisme
Institut:
Institut Informatique de gestion
Classification:
Informatique
Adresse bibliogr.:
Paris, 27-30 october 2014
Date:
Paris
27-30 october 2014
2014
Pagination:
5 p.
Titre du document hôte:
Procedings of IEEE International Conference on Image Processing 2014
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Note  Le statut de ce document est: non diffusé

Note: The status of this file is: restricted


 Notice créée le 2015-09-04, modifiée le 2018-02-15

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