ArticleIEEE transactions on medical imaging2023
Current Progress and Challenges in Large-Scale 3D Mitochondria Instance Segmentation.
Article in IEEE transactions on medical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Neuroimage analysis using artificial intelligence approaches: a systematic review.Medical & biological engineering & computing · 2024Pooled it
- Three-dimensional mapping of intact ovaries reveals the aging dynamics of the ovarian reserve.Nature aging · 2026Article
- Review
- Automated segmentation of neurons and spinal cord structures in immunofluorescence images using SpineDL.Scientific reports · 2026Article
- MambaSSM: efficient segmentation of brain structures in anisotropic 3D EM images via state-space models.Frontiers in neuroscience · 2026Article
- MitoEM 2.0: A Benchmark for Challenging 3D Mitochondria Instance Segmentation from EM Images.bioRxiv : the preprint server for biology · 2025Article
- PETFormer-SCL: a supervised contrastive learning-guided CNN-transformer hybrid network for Parkinsonism classification from FDG-PET.Annals of nuclear medicine · 2025Article
- A narrative review of foundation models for medical image segmentation: zero-shot performance evaluation on diverse modalities.Quantitative imaging in medicine and surgery · 2025Review
- Efficient cell-wide mapping of mitochondria in electron microscopic volumes using webKnossos.Cell reports methods · 2025Article
Corrections and comments
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Authors and funding
27 authors at 12 institutions in 6 countries.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.