Zhaolin Chen

Associate Professor and ARC MCR Industry Fellow. MRI, PET, deep learning, image recon and analysis

[Zhaolin Chen @zchen_imaging]

Great opportunity to submit a simple abstract & to know better your local MRI community !!

[ISMRM_AusNZ @ISMRM_AusNZ]

💡 Got groundbreaking MRI research? Share it with the ISMRM ANZ community. Just ONE week left to submit your abstract! #ISMRMANZ2024 #MRI #Research

https://t.co/rM1C8GNDvG

[Australian National Imaging Facility @NIFAus]

#NIFSymposium2024 Session Highlight | Accessible Imaging: Technology underpinning community outcomes

Featuring speakers:
Samantha Holdsworth, @MonikaJanda, Paul Parizel, Stuart Crozier, @RosenLab, @Shawna_Far, @zchen_imaging

Full program and register: https://t.co/CRaT4grkgi

[Zhaolin Chen @zchen_imaging]

@adeelrazi Congratulations Adeel! Very well deserved!

[Zhaolin Chen @zchen_imaging]

@ISMRM ANZ chapter #workshop on #AI in MRI. Great line up of speakers!!

[Caerwen Ellery @CaerwenBeaton]

ANZ ISMRM are hosting an online workshop on Artificial Intelligence in MRI Research!

To join us on the 24th of June, register here: https://t.co/DIbIdyO26f

[Zhaolin Chen @zchen_imaging]

@MRI_Dan In return, the food in Singapore is top tier

[Zhaolin Chen @zchen_imaging]

Informative

[Campbell 🍅🥫 @lofiMRI]

FDA released it's latest AI stats: 📈🤖
- 882 authorized AI-enabled devices
- 671 (76%) from radiology
- Largest players are @GEHealthCare, @SiemensHealth @PhilipsHealth, @CanonUSA, and @aidocmed

Worth reviewing @realmargaretta's article:
👉 https://t.co/vF2qukpi2e

[Zhaolin Chen @zchen_imaging]

Groundbreaking at ultra low field MRI! Whole body imaging at 0.05T

[Science Magazine @ScienceMagazine]

In a new Science study, researchers present a safer, low-cost, and low-energy whole-body MRI device.

The findings could help address unmet clinical needs in diverse healthcare settings worldwide. https://t.co/UytEldEceN

[Zhaolin Chen @zchen_imaging]

@NIFAus @Shawna_Far @ISMRT_ISMRM @ISMRM @ISMRTANZ @ISMRM_ANZ Congratulations @Shawna_Far. Great lecture!

[Zhaolin Chen @zchen_imaging]

#ISMRM24, we have abstracts to show our progress in ultra low field MRI w AI & clinical translation:
CSF quantification in Curating Synthetic Imaging Data session, Monday, 5pm;
Radiological image assessment in Synthetic MR session, Wednesday, 2:30pm

Come over for a chat!

[Zhaolin Chen @zchen_imaging]

@AFornito @jchrispang @NSB_Lab Congrats James!

[Zhaolin Chen @zchen_imaging]

Thank you very much for sharing our work. Medical imaging carries signifiant cost for both health providers and patients. Our goal is to make more MRI cost effective and sustainable.

[Susan Elliott @ProfSueElliott]

I'm regularly impressed by the capability of our #MonashUni researchers. A 5-minute full-body MRI scan is closer than we might think, with the help of a promising new AI method developed by Monash engineers: https://t.co/p9q8UtckB1

[Zhaolin Chen @zchen_imaging]

McSRA - transformer based MRI recon using sampling point spread function and leverage global MRI context.

[Mevan Ekanayake @mevanekanayake]

Check out our recent paper published in ELSEVIER - Computers in Biology and Medicine, which presents a novel AI-based solution for accelerated MRI reconstruction. @zchen_imaging @MehrtashH @gary_egan

link to the paper: https://t.co/YThq3asHuw

[Zhaolin Chen @zchen_imaging]

#MRI #PET #CT #GenerativeAI #medicaliamging

[Zhaolin Chen @zchen_imaging]

Really excited to see our large review piece out in Medical Image Analysis; we review medical image synthesis, analyse distinct network architectures, loss functions, quantify performance & provide overview of datasets. Challenges and opportunities are discussed. 👉

[Sanuwani Dayarathna @SanuwaniU]

We are excited to announce that our survey paper "Deep Learning based Synthesis of MRI, CT and PET: Review and Analysis" has been published in the Medical Image Analysis Journal (MedIA).

Check it out here : https://t.co/1y4TkASQ8n

[Monash Victorian Heart Institute @MonashVHI]

At the close of the #VHIsummit @ProfSNicholls awarded our Innovation Prize, as voted by the people, to the best presentation in our digital poster session.

Congratulations to this year's winner @mevanekanayake for 'Continuous Representation of Cardiac MRI data using AI'!

[Zhaolin Chen @zchen_imaging]

Collaboration cross multiple @NIFAus nodes and hospitals in Aus (Monash, UQ, Royal Perth Hospital, Alfred Hospital, HIRF, SAHMRI). @MarkusBarth2 @MengLaw1 @gary_egan @Mon_Bio_Imaging @MonashInfotech @Hyperfine

[Zhaolin Chen @zchen_imaging]

Excited to see our PoC MRI project @SciReports. We developed & validated a generative AI model for improving low field MRI. We acquired 90+ low & high field data. We show image quality improvement in resolution, SNR, quantitative volume accuracy in brain. https://t.co/WN5Q3g7ieP

[Zhaolin Chen @zchen_imaging]

Huge congratulations on @HimaAma92 being awarded the Victoria Biomedical Imaging Capability @VicBioImaging Early Career Award !! Excellent work.

[Zhaolin Chen @zchen_imaging]

@jchrispang @AFornito Congrats!

[Zhaolin Chen @zchen_imaging]

@ACNS_Official Congrats Sharna!