SSA:Using machine learning to improve data analysis from complex in vivo datasets:lifespan cellular resolution images of the zebrafish musculoskeletal
Lead Research Organisation:
University of Bristol
Department Name: Physiology and Pharmacology
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
Publications
Salazar-Silva R
(2021)
NCOA3 identified as a new candidate to explain autosomal dominant progressive hearing loss.
in Human molecular genetics
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| BB/R505626/1 | 30/09/2017 | 29/09/2021 | |||
| 2117425 | Studentship | BB/R505626/1 | 23/09/2018 | 24/09/2021 | Abdelwahab Kawafi |
| Description | This project focuses on improving the analysis of CT scans and 3D microscopy images. So far I have developed two machine learning models, one to automatically detect bones and cartilage from CT scans, and one to detect and track particles and cells from microscopy. |
| Exploitation Route | New zebrafish lines are constantly being generated with bone disease mutations and shared between labs, more are constantly being CT scanned which this model can be used for automated analysus |
| Sectors | Digital/Communication/Information Technologies (including Software) Healthcare Pharmaceuticals and Medical Biotechnology |
| URL | https://github.com/wahabk/ctfishpy |