@inproceedings{8e086851f0b2474e8b6792b610091d9f,
title = "Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings",
abstract = "Human ratings are abstract representations of segmentation quality. To approximate human quality ratings on scarce expert data, we train surrogate quality estimation models. We evaluate on a complex multi-class segmentation problem, specifically glioma segmentation, following the BraTS annotation protocol. The training data features quality ratings from 15 expert neuroradiologists on a scale ranging from 1 to 6 stars for various computer-generated and manual 3D annotations. Even though the networks operate on 2D images and with scarce training data, we can approximate segmentation quality within a margin of error comparable to human intra-rater reliability. Segmentation quality prediction has broad applications. While an understanding of segmentation quality is imperative for successful clinical translation of automatic segmentation quality algorithms, it can play an essential role in training new segmentation models. Due to the split-second inference times, it can be directly applied within a loss function or as a fully-automatic dataset curation mechanism in a federated learning setting.",
keywords = "BraTS, automatic quality control, glioma, quality estimation, segmentation quality metrics",
author = "Florian Kofler and Ivan Ezhov and Lucas Fidon and Izabela Horvath and {de la Rosa}, Ezequiel and John LaMaster and Hongwei Li and Tom Finck and Suprosanna Shit and Johannes Paetzold and Spyridon Bakas and Marie Piraud and Jan Kirschke and Tom Vercauteren and Claus Zimmer and Benedikt Wiestler and Bjoern Menze",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Proceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022 ; Conference date: 18-09-2022 Through 22-09-2022",
year = "2023",
doi = "10.1007/978-3-031-33842-7_1",
language = "English",
isbn = "9783031338410",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "3--13",
editor = "Spyridon Bakas and Ujjwal Baid and Bhakti Baheti and Alessandro Crimi and Sylwia Malec and Monika Pytlarz and Maximilian Zenk and Reuben Dorent",
booktitle = "Brainlesion",
}