Segmentation of human functional tissue units in support of a Human Reference Atlas

The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurat...

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Published in:Communications biology Vol. 6; no. 1; pp. 717 - 13
Main Authors: Jain, Yashvardhan, Godwin, Leah L., Ju, Yingnan, Sood, Naveksha, Quardokus, Ellen M., Bueckle, Andreas, Longacre, Teri, Horning, Aaron, Lin, Yiing, Esplin, Edward D., Hickey, John W., Snyder, Michael P., Patterson, Nathan Heath, Spraggins, Jeffrey M., Börner, Katy
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 19.07.2023
Nature Publishing Group
Nature Portfolio
Subjects:
631/114/1305
631/114/1314
Adult
Algorithms
Biology
Biomedical and Life Sciences
Humans
Kidneys
Life Sciences
Machine Learning
Magnetic Resonance Imaging
Pilot Projects
Segmentation
ISSN:2399-3642, 2399-3642
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Abstract The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale—showcasing the value of Kaggle competitions for advancing research. Results from a Kaggle competition and expanded analysis of the winning algorithms are presented for segmentation of functional tissue units as part of the Human BioMolecular Atlas Program (HuBMAP).
AbstractList The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale—showcasing the value of Kaggle competitions for advancing research.
The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale-showcasing the value of Kaggle competitions for advancing research.The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale-showcasing the value of Kaggle competitions for advancing research.
The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale—showcasing the value of Kaggle competitions for advancing research. Results from a Kaggle competition and expanded analysis of the winning algorithms are presented for segmentation of functional tissue units as part of the Human BioMolecular Atlas Program (HuBMAP).
Abstract The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale—showcasing the value of Kaggle competitions for advancing research.
The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue units (FTUs), relevant for HRA construction, are of pathobiological significance. Manual segmentation of FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms are needed. We designed and hosted a Kaggle competition that focused on development of such algorithms and 1200 teams from 60 countries participated. We present the competition outcomes and an expanded analysis of the winning algorithms on additional kidney and colon tissue data, and conduct a pilot study to understand spatial location and density of FTUs across the kidney. The top algorithm from the competition, Tom, outperforms other algorithms in the expanded study, while using fewer computational resources. Tom was added to the HuBMAP infrastructure to run kidney FTU segmentation at scale—showcasing the value of Kaggle competitions for advancing research. Results from a Kaggle competition and expanded analysis of the winning algorithms are presented for segmentation of functional tissue units as part of the Human BioMolecular Atlas Program (HuBMAP).
ArticleNumber 717
Author Patterson, Nathan Heath
Jain, Yashvardhan
Lin, Yiing
Börner, Katy
Godwin, Leah L.
Longacre, Teri
Snyder, Michael P.
Hickey, John W.
Quardokus, Ellen M.
Ju, Yingnan
Bueckle, Andreas
Esplin, Edward D.
Spraggins, Jeffrey M.
Horning, Aaron
Sood, Naveksha
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  organization: Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University
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  fullname: Longacre, Teri
  organization: Department of Pathology, Stanford University School of Medicine
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  organization: Thermo Fisher Scientific
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  surname: Hickey
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  surname: Börner
  fullname: Börner, Katy
  email: katy@indiana.edu
  organization: Department of Intelligent Systems Engineering, Luddy School of Informatics, Computing, and Engineering, Indiana University
BackLink https://www.ncbi.nlm.nih.gov/pubmed/37468557$$D View this record in MEDLINE/PubMed
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Snippet The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level. Functional tissue...
Abstract The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Human Reference Atlas (HRA) for the healthy adult body at the cellular level....
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631/114/1314
Adult
Algorithms
Biology
Biomedical and Life Sciences
Humans
Kidneys
Life Sciences
Machine Learning
Magnetic Resonance Imaging
Pilot Projects
Segmentation
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Title Segmentation of human functional tissue units in support of a Human Reference Atlas
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