Brain And SIgnal Research & Analysis laboratory

Develop your research skills in brain data learning
“My training has given me the tools and the confidence to understand and critically assess the contents of research papers so that I can direct my own research.”
Can Gafuroğlu (Undergrad student)

Applications for internships are open now.

PRESENTATION

BASIRA (Brain And SIgnal Research & Analysis) aims to infuse advanced computer vision and machine-learning methods into big neuroimaging and signal data analysis for improving healthcare and wellbeing.  Specifically, since one can look at the brain as an image, a shape, or a connectional network, we aspire to develop advanced image-based, shape-based, and network-based medical data analysis techniques, that will provide a foundation for better understanding normal brain development and ageing, as well as how the brain gets affected by neuropsychiatric or neurodegenerative disorders. We aim to develop algorithms and architectures for mapping the healthy brain and computer-aided tools for examining the diseased/disordered brain.
More broadly, we also aim to devise efficient algorithms that perform several medical image and signal analysis tasks such as segmentation/labeling, registration, prediction, classification and regression.​

News and Events

Islem Rekik, Ph.D.

Highlights

Zeynep's paper on federated brain graph evolution prediction with temporally-varying acquisitions is accepted for publication in the journal of IEEE Transactions on Medical Imaging (IF: 11.03)!

Congratulations!

November 21, 2022

Zeynep's paper on graph registration network for brain connectivity classification is accepted for publication in the journal of Computerized Medical Imaging and Graphics (IF: 7.42)!

Congratulations!

November 7, 2022

Oytun's paper on recurrent multigraph neural networks for predicting the evolution trajectory of population-driven connectional brain templates is accepted for publication in the journal of Medical Image Analysis (IF: 13.82)!

Congratulations!

September 30, 2022

Alaa's review paper on "Graph Neural Networks in Network Neuroscience" is accepted for publication in the journal of IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) (IF: 24.31)!

Congratulations!

September 18, 2022

We have 8 papers accepted for publication in the LNCS Springer proceedings of the main MICCAI 2022 conference & MICCAI workshops (PRIME & GRAIL)! 6 out of 8 are from ITU undergraduate students.

Congratulations everyone!

July 20, 2022

Congratulations to Fatih and Xuesong for their accepted MICCAI 2022 papers on Connectional Brain Template Learning using GNNs and Contrastive Functional Connectivity Graph Learning, respectively!

June 2, 2022

WANT TO JOIN OUR LAB ?

If you are interested, please contact us and send your CV and letter of motivation to i.rekik@imperial.ac.uk

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