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Jong Sung Park Profile
Jong Sung Park

@get_user_data

Followers
29
Following
279
Media
9
Statuses
132

At Indiana University wanna be Ph.D. Works on image analysis/deep learning on neuroimaging. One of the biggest carbon emitting students using supercomputers.

Bloomington, IN
Joined November 2012
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@dipymri
dipy
5 days
In Week 3 of #DiffusionMRIZerotoHero, we examine the NIfTI format and how it consolidates sequential 3D diffusion acquisitions into a standardized 4D dataset. Read more on: https://t.co/NLrR6Ud3qv #dMRI #DIPY #Neuroimaging
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@dipymri
dipy
15 days
Introducing our paper, FORCE: A forward modeling dMRI framework by @ShahAtharv57469 et al. It simulates signals to find the best match, unifying analysis in a single step. 🧠 More on LinkedIn: https://t.co/8yEIJhoMbE Paper: https://t.co/cwnE02m5x3 #dMRI #NeuroScience #DIPY
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@dipymri
dipy
19 days
Our Diffusion MRI Zero to Hero series is here! πŸš€ What is dMRI? How does it work? What is its clinical significance? 🧠 Read the full post on LinkedIn: https://t.co/2VTjKnYz5D
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@dipymri
dipy
1 month
🧠 Join us for the next edition of the DIPY Workshop! πŸ—“ March 16–20, 2026 | 100% Online 5 days of hands-on learning on preprocessing, reconstruction, tractography, advanced analytics, and much more. Registrations now open β†’ https://t.co/WDDBrAgH0m #DW2026 #Neuroimaging #MRI
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@dipymri
dipy
7 months
🌟 Get ready to catch The Perfect Wave: AI-Powered Advances in Image Segmentation at #ISMRM2025, featuring a presentation by Jong Sung Park @get_user_data ! πŸ—“οΈ Date: Monday, May 12, 2025 πŸ•“ Session Time: 4:00 PM (Hawaii Time) πŸ•’ Presentation Time: 4:36 PM (Hawaii Time) Join
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@dipymri
dipy
7 months
🌟 Join us at #ISMRM2025 for an exciting oral presentation by Dr. Bramsh Chandio @BramshQ in the session Clinical Neuroimaging in Alzheimer's Disease: Current Trends & Future Directions. πŸ—“οΈ Date: Monday, May 12, 2025 πŸ•‘ Session Time: 1:45 PM (Hawaii Time) πŸ•’ Presentation Time:
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@kurtschilling5
kurt.schilling
7 months
Can confirm - works great on human AND animal models where b-vectors may have unique or proprietary formats.
@dipymri
dipy
7 months
🚨 Dealing with flipped b-vectors in your diffusion MRI data? Check out the Fiber Coherence Index (FCI) by Schilling et al.β€”a straightforward and effective method for detecting and correcting B-table orientation errors. πŸ“„ A fiber coherence index for quality control of B-table
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@dipymri
dipy
8 months
A heartfelt thank you to everyone who made #DIPYWorkshop2025 so meaningful. To the speakers and attendeesβ€”your insights, curiosity, and energy made it truly inspiring. Grateful to be part of such a passionate, collaborative community. Until next time! πŸ§ πŸ“Šβœ¨ #DIPY #DiffusionMRI
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@dipymri
dipy
9 months
πŸš€ 2 DAYS TO GO! πŸš€ Join us at DIPY Workshop 2025 – a masterclass in structural & diffusion imaging! 🧠✨ πŸ“… March 17-21, 2025 πŸ“ Online (Zoom & Discord) πŸ”¬ Hands-on tutorials, expert talks, and networking πŸ’‘ Register & learn more: πŸ‘‰ https://t.co/9gh65ZngaR #DIPYWorkshop
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@dipymri
dipy
9 months
πŸš€ Excited to welcome Alexandra Badea (@portokalh) to #DIPYWorkshop2025! πŸ”¬ Associate Professor at Duke University, specializing in Alzheimer’s disease & brain imaging with advanced MRI techniques like diffusion tensor imaging. Her work focuses on brain connectivity,
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@dipymri
dipy
9 months
Excited to announce Prof. Maxime Descoteaux (@maxdescoteaux) from UniversitΓ© de Sherbrooke & SCIL, a pioneer in advanced diffusion MRI and connectomics, as a speaker at #DIPYworkshop2025! Join us to explore his cutting-edge presentation on Spherical Harmonic Reconstruction with
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@dipymri
dipy
10 months
Ever seen the Handbook of Diffusion MR Tractography by Flavio Dell'Acqua (@flaviodellacqua), Maxime Descoteaux (@maxdescoteaux) & Alexander Leemans (@Alex_Leemans)? πŸ“–πŸ”¬ We’re beyond excited about this new book! The depth of topics covered is truly impressive, making this an
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@dipymri
dipy
10 months
πŸš€ DIPY v1.11.0 – Tractography at Ultra Speed! ⚑ DIPY v1.11.0 is bringing Ultra Fast Tracking – up to 100x faster! πŸ”₯ Supercharge your tractography workflows with unmatched speed & precision! 🌟 Speakers Gabriel Girard (@GabrielPGirard) & John Kruper (@360_0_0) will introduce
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@dipymri
dipy
1 year
A big thank you to everyone who stopped by the DIPY booth at #RSNA2024! πŸ™Œ It was amazing connecting with so many of you to discuss #DiffusionImaging and #AI in healthcare. We’re excited for the future and grateful for your support and interest. See you next year! πŸš€
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@dipymri
dipy
1 year
πŸš€βœ¨ Check out this compelling talk by Professor Paul Thompson (@PTenigma) from USC at #DipyWorkshop2024 on the power of diffusion MRI & generative AI in neuroimaging! πŸ§ πŸ’‘ Discover groundbreaking insights into brain disorders like Parkinson's disease, major depression, bipolar
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@Jo_Youngheun
Youngheun Jo
2 years
Excited to share the latest preprintπŸ’« now available on @BioRxiv titled "Variation in high-amplitude events across the human lifespan"!!! A joint effort by @JacobCTanner1 @caioseguin @joshfasky @richardfbetzel Here, we demonstrate the following in🧡1/n
@biorxivpreprint
bioRxiv
2 years
Variation in high-amplitude events across the human lifespan https://t.co/yWkbS50l1Z #bioRxiv
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@dipymri
dipy
2 years
Less than 24 hours until the DIPY workshop begins! Secure your spot now for an immersive experience in medical imaging analysis.πŸ©ΊπŸ“·βœ¨ Register here: https://t.co/9gh65ZngaR #DIPYWorkshp2024 #ArtificialIntelligence #opensource #Python #AIinMedicine #DIPY #DMRI #MedicalAnalysis
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@dipymri
dipy
2 years
Only 3 days left until the DIPY workshop! Don’t miss your chance to register and secure your spot! Register here - https://t.co/9gh65ZngaR Overview video here - https://t.co/Ls1ZRq14J0 #DIPY #Workshop2024 #ArtificialIntelligence #MedicalImaging #MachineLearning
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@get_user_data
Jong Sung Park
2 years
If you want to hear more about this work, the progress, and everything going on DIPY, register for the DIPY workshop :)
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@get_user_data
Jong Sung Park
2 years
Our work uses a unique way of combining CRFasRNN Layers with the 3D U-net like structure for brain extraction, and possibly general volumetric medical image segmentation.
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