EMito-Metrix is a high-performance pipeline to automatically segment and analyze mitochondrial morphology + ultrastructure from images acquired with Transmission Electron Microscopy (TEM). The interface allows to compute a set of morphometrics and texture measurements, and provides a list of graphs for optimizing data visualization. An additional machine learning (ML) module with predictive analytic tools allows determining how any given experimental condition would impact on mito-metrics. EMito-Metrix app was written by E.Morin, E.Doumard, M. Vigneau and J-P Pradère from the RESTORE Institute.
- Detection & Segmentation : Robustly Trained DL models for different species
- MitoMetrivs Analysis : Extract substantial morphological and ultrastructure informations
- Data Analysis : Evaluate the impact of any given experimental conditions on mitometrics
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- 👩🏽💼 Disclaimer: EMito-metrix app is an open Access tool to support all scientists in the field, and help our community to move forward. But in any case, Emito-Metrix staff assumes no responsibility, for errors, omissions, data interpretation, or any actions taken based on the utilization of our application.
- 📝 We strongly recommend all users to carefully follow all instructions in the Instruction manual (link) or FAQ sections (link). Installing and handling correctly EMito-Metrix may require time and patience. Please start by checking all prerequisites and computer resources needed, to make sure the application can run properly on your machine.
- ✉️ Do not hesitate to contact us (forum Github link) if you have any problems or issues.
- 📖 If you use in your publication results generated from our application, please cite our work as followed : “EMito-Metrix, a turnkey pipeline for an automatic evaluation of mitochondria morphology across species: from TEM imaging to computed data” Morin E et al (XXXX), Journal Name, Volume (Issue), page x-page y. // doi…
🔔 Important Notes 🔔
