Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps

• URL: http://arxiv.org/abs/2312.02608v1
• Date: Tue, 5 Dec 2023 09:34:56 GMT
• Title: Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
• Authors: Florian Kofler, Hendrik M\"oller, Josef A. Buchner, Ezequiel de la Rosa, Ivan Ezhov, Marcel Rosier, Isra Mekki, Suprosanna Shit, Moritz Negwer, Rami Al-Maskari, Ali Ert\"urk, Shankeeth Vinayahalingam, Fabian Isensee, Sarthak Pati, Daniel Rueckert, Jan S. Kirschke, Stefan K. Ehrlich, Annika Reinke, Bjoern Menze, Benedikt Wiestler, Marie Piraud
• Abstract summary: panoptica is a versatile and performance-optimized package for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. panoptica is open-source, implemented in Python, and accompanied by comprehensive documentation and tutorials.
• Score: 9.140078680017046
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. panoptica addresses the limitations of existing metrics and provides a modular framework that complements the original intersection over union-based panoptic quality with other metrics, such as the distance metric Average Symmetric Surface Distance. The package is open-source, implemented in Python, and accompanied by comprehensive documentation and tutorials. panoptica employs a three-step metrics computation process to cover diverse use cases. The efficacy of panoptica is demonstrated on various real-world biomedical datasets, where an instance-wise evaluation is instrumental for an accurate representation of the underlying clinical task. Overall, we envision panoptica as a valuable tool facilitating in-depth evaluation of segmentation methods.

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