학술논문

Current Progress and Challenges in Large-Scale 3D Mitochondria Instance Segmentation
Document Type
Periodical
Source
IEEE Transactions on Medical Imaging IEEE Trans. Med. Imaging Medical Imaging, IEEE Transactions on. 42(12):3956-3971 Dec, 2023
Subject
Bioengineering
Computing and Processing
Image segmentation
Measurement
Three-dimensional displays
Annotations
Cancer
Morphology
Benchmark testing
Mitochondria
electron microscopy
3D instance segmentation
connectomics
brain
Language
ISSN
0278-0062
1558-254X
Abstract
In this paper, we present the results of the MitoEM challenge on mitochondria 3D instance segmentation from electron microscopy images, organized in conjunction with the IEEE-ISBI 2021 conference. Our benchmark dataset consists of two large-scale 3D volumes, one from human and one from rat cortex tissue, which are 1,986 times larger than previously used datasets. At the time of paper submission, 257 participants had registered for the challenge, 14 teams had submitted their results, and six teams participated in the challenge workshop. Here, we present eight top-performing approaches from the challenge participants, along with our own baseline strategies. Posterior to the challenge, annotation errors in the ground truth were corrected without altering the final ranking. Additionally, we present a retrospective evaluation of the scoring system which revealed that: 1) challenge metric was permissive with the false positive predictions; and 2) size-based grouping of instances did not correctly categorize mitochondria of interest. Thus, we propose a new scoring system that better reflects the correctness of the segmentation results. Although several of the top methods are compared favorably to our own baselines, substantial errors remain unsolved for mitochondria with challenging morphologies. Thus, the challenge remains open for submission and automatic evaluation, with all volumes available for download.