Author

Parnesh Raniga

Commonwealth Scientific and Industrial Research OrganisationORCID 0000-0002-0106-6322Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 3 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:imaging· 2 Approach:Bayesian inference· 1 Research Focus:cell-cell communication· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Gary F. EganiD· 2 shared Jürgen FrippiD· 2 shared Aishwarya Dhruva· 1 shared Amanda Ng· 1 shared Amir FazlollahiiD· 1 shared Ashley I. Bush· 1 shared Bryan K. PatoniD· 1 shared David G. BarnesiD· 1 shared

Activity by Year

2016-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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2 shared papersNeuroscience

Gary F. EganORCID

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4 papers

Recent·Most cited

Shared genetic architecture between brain iron deposition and Alzheimer's disease

Md Rezanur Rahman, Ying Xia, Parnesh Raniga, Amir Fazlollahi, Tania Islam, Aishwarya Dhruva, Jue‐Sheng Ong, Stuart MacGregor, Ashley I. Bush, Jürgen Fripp, Michelle K. Lupton

This study identifies shared genetic factors between brain iron deposition and Alzheimer's disease, revealing a polygenic basis and potential neuroimmune mechanisms.

medRxiv · Sep 9, 2026 · PreprintGenetic & Genomic Medicine

Multi T1-weighted contrast imaging and T1 mapping with Compressed sensing FLAWS at 3T

Jérémy Beaumont, Jürgen Fripp, Parnesh Raniga, Oscar Acosta, Jean‐Christophe Ferré, Katie Louise McMahon, Julie Trinder, Tobias Kober, Giulio Gambarota

This paper optimizes the FLAWS MRI sequence with compressed sensing to reduce acquisition time while maintaining image quality and enables T1-weighted imaging and mapping at 3T.

Magnetic Resonance Materials in Physics Biology and Medicine · Feb 27, 2023Peer-reviewedNeuroscience

Combining images and anatomical knowledge to improve automated vein segmentation in MRI

Phillip G. D. Ward, Nicholas J. Ferris, Parnesh Raniga, David L. Dowe, Amanda Ng, David G. Barnes, Gary F. Egan

This study improves automated vein segmentation in MRI by combining susceptibility-weighted images, quantitative susceptibility maps, and a vein atlas into a composite vein image, showing significant performance gains.

NeuroImage · Oct 25, 2017Peer-reviewedNeuroscience

Resting state functional coupling between the ascending synchronising system, limbic system and the default mode network via theta oscillations

Parnesh Raniga, Bryan K. Paton, Gary F. Egan

The paper uses resting state fMRI to show functional coupling between the default mode network, medial temporal lobe, and ascending synchronising system via theta oscillations.

bioRxiv · Nov 8, 2016 · PreprintNeuroscience