Spontaneous breaking of symmetry in overlapping cell instance segmentation using diffusion models Article Swipe
Julius B. Kirkegaard
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.07.07.548066
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1101/2023.07.07.548066
Instance segmentation is the task of assigning unique identifiers to individual objects in images. Solving this task requires breaking the inherent symmetry that semantically similar objects must result in distinct outputs. Deep learning algorithms bypass this break-of-symmetry by training specialized predictors or by utilizing intermediate label representations. However, many of these approaches break down when faced with overlapping labels that can appear, e.g., in biological cell layers. Here, we discuss the reason for this failure and offer a novel approach for instance segmentation based on diffusion models that breaks this symmetry spontaneously. Our method outputs pixel-level instance segmentations matching the performance of models such as cellpose on the cellpose fluorescent cell dataset while also permitting overlapping labels.
Related Topics
Concepts
Segmentation
Symmetry (geometry)
Computer science
Task (project management)
Symmetry breaking
Artificial intelligence
Matching (statistics)
Diffusion
Pixel
Identifier
Pattern recognition (psychology)
Algorithm
Mathematics
Geometry
Physics
Thermodynamics
Programming language
Quantum mechanics
Statistics
Management
Economics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2023.07.07.548066
- https://www.biorxiv.org/content/biorxiv/early/2023/07/07/2023.07.07.548066.full.pdf
- OA Status
- green
- Cited By
- 2
- References
- 10
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4383500283
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4383500283Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2023.07.07.548066Digital Object Identifier
- Title
-
Spontaneous breaking of symmetry in overlapping cell instance segmentation using diffusion modelsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-07-07Full publication date if available
- Authors
-
Julius B. KirkegaardList of authors in order
- Landing page
-
https://doi.org/10.1101/2023.07.07.548066Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2023/07/07/2023.07.07.548066.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.biorxiv.org/content/biorxiv/early/2023/07/07/2023.07.07.548066.full.pdfDirect OA link when available
- Concepts
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Segmentation, Symmetry (geometry), Computer science, Task (project management), Symmetry breaking, Artificial intelligence, Matching (statistics), Diffusion, Pixel, Identifier, Pattern recognition (psychology), Algorithm, Mathematics, Geometry, Physics, Thermodynamics, Programming language, Quantum mechanics, Statistics, Management, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1Per-year citation counts (last 5 years)
- References (count)
-
10Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.overlapping | 58, 116 |
| abstract_inverted_index.performance | 101 |
| abstract_inverted_index.pixel-level | 96 |
| abstract_inverted_index.specialized | 40 |
| abstract_inverted_index.intermediate | 45 |
| abstract_inverted_index.segmentation | 2, 83 |
| abstract_inverted_index.semantically | 24 |
| abstract_inverted_index.segmentations | 98 |
| abstract_inverted_index.spontaneously. | 92 |
| abstract_inverted_index.representations. | 47 |
| abstract_inverted_index.break-of-symmetry | 37 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5013570173 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 1 |
| citation_normalized_percentile.value | 0.81623767 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |