ABLE: an activity-based level set segmentation algorithm for two-photon calcium imaging data
- Submitting institution
-
Imperial College of Science, Technology and Medicine
- Unit of assessment
- 12 - Engineering
- Output identifier
- 396
- Type
- D - Journal article
- DOI
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10.1523/ENEURO.0012-17.2017
- Title of journal
- eNeuro
- Article number
- ENEURO.0012-17.2017
- First page
- 1
- Volume
- 4
- Issue
- 5
- ISSN
- 2373-2822
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
10.1523/ENEURO.0012-17.2017
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Our method for detecting neurons in two-photon calcium imaging datasets is relevant to high-content screening in the pharmaceutical industry and advances neuroscience research. The paper resulted in invitations to speak to pharmaceutical industry researchers at Eli Lilly (contact: FoEREF@ic.ac.uk) and Janssen (FoEREF@ic.ac.uk), presentations at industry-focused neurotechnology conferences (3rd and 4th Annual Neuroscience R&D Technologies Conference, London 2017 and Munich 2018), the National Institutes of Health (USA), NSF NeuroNex workshops held at UC Santa Barbara in Jan 2019 and 2020, as well as a plenary lecture at the INCF Congress on Neuroinformatics in Montreal in 2018.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -