학술논문
Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
Document Type
Working Paper
Author
Kofler, Florian; Möller, Hendrik; Buchner, Josef A.; de la Rosa, Ezequiel; Ezhov, Ivan; Rosier, Marcel; Mekki, Isra; Shit, Suprosanna; Negwer, Moritz; Al-Maskari, Rami; Ertürk, Ali; Vinayahalingam, Shankeeth; Isensee, Fabian; Pati, Sarthak; Rueckert, Daniel; Kirschke, Jan S.; Ehrlich, Stefan K.; Reinke, Annika; Menze, Bjoern; Wiestler, Benedikt; Piraud, Marie
Source
Subject
Language
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.
Comment: 15 pages, 6 figures, 3 tables
Comment: 15 pages, 6 figures, 3 tables