I had the great opportunity to present in the AARnet Reseracher Talks webinar Winter Series 2021 and in this Research Showcase Webinar I highlighted interoperability examples between AARnet CloudStor with external tools and services like Zotero, the open science foundation Read more…
I recently had the wonderful opportunity to present our deep learning work in magnetic resonance imaging at the ML4AU CoP showcase event to more than 65 participants. I showed one example on efficiently solving an ill-posed inverse problem for quantitative Read more…
When using a High Performance Computing System you also might have run into the problem of how to get data in and out of this system. We are very lucky in Australia to have CloudStor, which is Aarnets hosted OwnCloud Read more…
Zotero is an open source reference and citation management tool that probably everyone knows and loves. Zotero stores the PDFs of publicaitons and books and when you want to keep your library synchronized you need some central storage. Now it’s Read more…
I am extremely lucky to have been awarded an ARC Linkage grant together with our partner Siemens Healthineers to advance deep learning applications for medical imaging in the next 3 years. It’s not just exciting because this is my first Read more…
Our new preprint is online. NeXtQSM is a deep learning pipeline for data-consistent quantitative susceptibility mapping trained with simulated data build by our CIBIT MPhil student Francesco Cognolato: [2107.07752] NeXtQSM — A complete deep learning pipeline for data-consistent quantitative susceptibility Read more…
For the OHBM 2021 I created a short 2 minute summary of our NeuroDesk project 🙂
I was invited to present my view on fast fMRI acquisitions and analyses at the Spinoza User Meeting (Spinoza Centre for Neuroimaging, Amsterdam, Netherlands) in May 2021. Below you can find the slides, which I hope are a useful resource Read more…
Our latest preprint describes the QSMxT pipeline developed by Ashley Stewart – a CIBIT PhD student in our team: QSMxT enables robust & automated quantitative susceptibility mapping and extraction of quantitative information from regions of interest. The code can be Read more…
We were very fortunate to be highlighted in MRM for our paper “Improving FLAIR SAR efficiency at 7T by adaptive tailoring of adiabatic pulse power through deep learning B1+ estimation” and the reproducible research habits in our group 🙂 The Read more…