Fluorescent Neuronal Cells v2: Multi-Task, Multi-Format Annotations for Deep Learning in Microscopy Article Swipe
L. Clissa
,
Antonio Macaluso
,
R. Morelli
,
Alessandra Occhinegro
,
Emiliana Piscitiello
,
Ludovico Taddei
,
Marco Luppi
,
Roberto Amici
,
Matteo Cerri
,
Timna Hitrec
,
L. Rinaldi
,
A. Zoccoli
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2307.14243
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2307.14243
Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the corresponding ground-truth annotations, designed to foster innovative research in the domains of Life Sciences and Deep Learning. This dataset encompasses three image collections in which rodent neuronal cells' nuclei and cytoplasm are stained with diverse markers to highlight their anatomical or functional characteristics. Alongside the images, we provide ground-truth annotations for several learning tasks, including semantic segmentation, object detection, and counting. The contribution is two-fold. First, given the variety of annotations and their accessible formats, we envision our work facilitating methodological advancements in computer vision approaches for segmentation, detection, feature learning, unsupervised and self-supervised learning, transfer learning, and related areas. Second, by enabling extensive exploration and benchmarking, we hope Fluorescent Neuronal Cells v2 will catalyze breakthroughs in fluorescence microscopy analysis and promote cutting-edge discoveries in life sciences. The data are available at: https://amsacta.unibo.it/id/eprint/7347
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2307.14243
- https://arxiv.org/pdf/2307.14243
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385328155
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4385328155Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2307.14243Digital Object Identifier
- Title
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Fluorescent Neuronal Cells v2: Multi-Task, Multi-Format Annotations for Deep Learning in MicroscopyWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-07-26Full publication date if available
- Authors
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L. Clissa, Antonio Macaluso, R. Morelli, Alessandra Occhinegro, Emiliana Piscitiello, Ludovico Taddei, Marco Luppi, Roberto Amici, Matteo Cerri, Timna Hitrec, L. Rinaldi, A. ZoccoliList of authors in order
- Landing page
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https://arxiv.org/abs/2307.14243Publisher landing page
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https://arxiv.org/pdf/2307.14243Direct link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2307.14243Direct OA link when available
- Concepts
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Deep learning, Artificial intelligence, Computer science, Segmentation, Transfer of learning, Microscopy, Pattern recognition (psychology), Ground truth, Fluorescence, Annotation, Task (project management), Fluorescence microscope, Pathology, Engineering, Physics, Medicine, Quantum mechanics, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 12, 22, 57, 80 |
| abstract_inverted_index.Deep | 28 |
| abstract_inverted_index.Life | 25 |
| abstract_inverted_index.This | 30 |
| abstract_inverted_index.data | 141 |
| abstract_inverted_index.hope | 121 |
| abstract_inverted_index.life | 138 |
| abstract_inverted_index.will | 126 |
| abstract_inverted_index.with | 46 |
| abstract_inverted_index.work | 91 |
| abstract_inverted_index.Cells | 2, 124 |
| abstract_inverted_index.given | 79 |
| abstract_inverted_index.image | 34 |
| abstract_inverted_index.their | 51, 85 |
| abstract_inverted_index.three | 33 |
| abstract_inverted_index.which | 37 |
| abstract_inverted_index.First, | 78 |
| abstract_inverted_index.areas. | 112 |
| abstract_inverted_index.cells' | 40 |
| abstract_inverted_index.foster | 18 |
| abstract_inverted_index.images | 10 |
| abstract_inverted_index.nuclei | 41 |
| abstract_inverted_index.object | 70 |
| abstract_inverted_index.rodent | 38 |
| abstract_inverted_index.tasks, | 66 |
| abstract_inverted_index.vision | 97 |
| abstract_inverted_index.Second, | 113 |
| abstract_inverted_index.dataset | 31 |
| abstract_inverted_index.diverse | 47 |
| abstract_inverted_index.domains | 23 |
| abstract_inverted_index.feature | 102 |
| abstract_inverted_index.images, | 58 |
| abstract_inverted_index.markers | 48 |
| abstract_inverted_index.promote | 134 |
| abstract_inverted_index.provide | 60 |
| abstract_inverted_index.related | 111 |
| abstract_inverted_index.several | 64 |
| abstract_inverted_index.stained | 45 |
| abstract_inverted_index.variety | 81 |
| abstract_inverted_index.Neuronal | 1, 123 |
| abstract_inverted_index.Sciences | 26 |
| abstract_inverted_index.analysis | 132 |
| abstract_inverted_index.catalyze | 127 |
| abstract_inverted_index.computer | 96 |
| abstract_inverted_index.designed | 16 |
| abstract_inverted_index.enabling | 115 |
| abstract_inverted_index.envision | 89 |
| abstract_inverted_index.formats, | 87 |
| abstract_inverted_index.learning | 65 |
| abstract_inverted_index.neuronal | 39 |
| abstract_inverted_index.research | 20 |
| abstract_inverted_index.semantic | 68 |
| abstract_inverted_index.transfer | 108 |
| abstract_inverted_index.Alongside | 56 |
| abstract_inverted_index.Learning. | 29 |
| abstract_inverted_index.available | 143 |
| abstract_inverted_index.counting. | 73 |
| abstract_inverted_index.cytoplasm | 43 |
| abstract_inverted_index.extensive | 116 |
| abstract_inverted_index.highlight | 50 |
| abstract_inverted_index.including | 67 |
| abstract_inverted_index.learning, | 103, 107, 109 |
| abstract_inverted_index.sciences. | 139 |
| abstract_inverted_index.two-fold. | 77 |
| abstract_inverted_index.accessible | 86 |
| abstract_inverted_index.anatomical | 52 |
| abstract_inverted_index.approaches | 98 |
| abstract_inverted_index.collection | 6 |
| abstract_inverted_index.detection, | 71, 101 |
| abstract_inverted_index.functional | 54 |
| abstract_inverted_index.innovative | 19 |
| abstract_inverted_index.microscopy | 9, 131 |
| abstract_inverted_index.Fluorescent | 0, 122 |
| abstract_inverted_index.annotations | 62, 83 |
| abstract_inverted_index.collections | 35 |
| abstract_inverted_index.discoveries | 136 |
| abstract_inverted_index.encompasses | 32 |
| abstract_inverted_index.exploration | 117 |
| abstract_inverted_index.advancements | 94 |
| abstract_inverted_index.annotations, | 15 |
| abstract_inverted_index.contribution | 75 |
| abstract_inverted_index.cutting-edge | 135 |
| abstract_inverted_index.facilitating | 92 |
| abstract_inverted_index.fluorescence | 8, 130 |
| abstract_inverted_index.ground-truth | 14, 61 |
| abstract_inverted_index.unsupervised | 104 |
| abstract_inverted_index.benchmarking, | 119 |
| abstract_inverted_index.breakthroughs | 128 |
| abstract_inverted_index.corresponding | 13 |
| abstract_inverted_index.segmentation, | 69, 100 |
| abstract_inverted_index.methodological | 93 |
| abstract_inverted_index.self-supervised | 106 |
| abstract_inverted_index.characteristics. | 55 |
| abstract_inverted_index.https://amsacta.unibo.it/id/eprint/7347 | 145 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 12 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/12 |
| sustainable_development_goals[0].score | 0.5199999809265137 |
| sustainable_development_goals[0].display_name | Responsible consumption and production |
| citation_normalized_percentile |