We look forward to your innovative contributions to this exciting area of research! This challenge is jointly organized by @JuanEugenioIgl1, @RosenLab, Bene Wiestler, @neuronflow, myself, and the @BraTS_challenge organizing team.

A step-by-step tutorial to get you started is available here: 📖: https://t.co/Xi2tzmdauM. Our evaluation criteria prioritize not only overall image quality (e.g., SSIM), but also importantly assess the clinical utility of synthesized tumor structures in segmentation tasks.

We invite you to participate in our new benchmark (part of the @MICCAI_Society Lighthouse Challenge): 👉 https://t.co/YNZbHlJanJ. Our challenge aims to develop generalizable 3D image synthesis algorithms for brain MRI scans, targeting three major types of brain tumors.

#MICCAIChallenge Synthetic 3D MRI images have enormous potential in medical imaging. Here's an example showing how synthetic MRI can effectively reduce motion artifacts in brain tumor imaging: the algorithm, trained on glioma patients, generalizes robustly to meningioma cases.

More great news: Our collaborative work with @RolfsMicrobes, Tobi, @HongweiBran, @menze_group, @DQBM_uzh is now in @PLOSONE Lab Protocols! Discover our new automated pipeline for imaging bacterial infections in zebrafish 🐟 Grateful for this collaboration! https://t.co/fPDi710MsR

@ja_schnabel gave a talk on “Resolving MR motion artefacts using deep learning” showcasing their works by @oksuzilkay @KingsImaging @SmartHeartUK and @hannah_eichhorn and @spieker_vj @HelmholtzMunich 👏. Check out their recent review on motion correction in MRI:

Amazing talks by Professors @DanielRueckert and @ja_schnabel at the Martinos Center @MGHMartinos , followed by engaging discussions with research fellows! Huge thanks to Matt @RosenLab and Eugenio @JuanEugenioIgl1 for their incredible support. #AI #MedicalImaging #MotionModeling

Thank you! @midl_conference

thanks!

Excited to announce that the @BraTS_Challenge willl take place again at the annual meeting of the @MICCAI_Society #MICCAI24 in #Marrakesh. Even more exciting are the newly introduced #openscience #benchmarks/#challenges releasing new #data. @MiccaiStudents @bias_sig Stay tuned!!!

Are curious about the Multi-Center #FeTA2022 #MICCAI challenge results? Have a look at the @arxiv paper here ➡️ https://t.co/x34EehCdBj @PayetteKelly @_Roxane_L @AndrasJakabMD @menze_group @HongweiBran @MeriBach @lanavasung @FIT_NGIn @PIPPIworkshop

Also… neural implicit representation could be used for k-space interpolation (IPMI2023): https://t.co/v0Tl4KWXoj , and multi-view reconstruction (MICCAI 2023)

We are hiring: Postdoc in Machine Learning in Neuroimaging. Please RT and spread the word. #jobsearch #Careers #MachineLearning @MICCAI_Society @ISMRM #GenerativeAI

Yes, it seems that we gain more robustness in k-space interpolation when using masked auto-encoding by a vision transformer. @PeterPanJZ will tell you more!

Alina will present her great work on 3D vessel segmentation with single 2D projections and extra supervision from depth maps!

Day 2 begins with an oral talk focusing on reconstruction!

welcome to the sister challenge - local inpainting challenge at BraTS!

@compImgTUM @JuanEugenioIgl1 @giemmecci @SpyridonBakas @ujjwalbaid0408 @BraTS_challenge @menze_group @BraTS_inpaint

We'll host this event within the great @BraTS_challenge framework. 🎉 If you're passionate about bridging this gap in neuroimaging and want to contribute, we invite you to participate! Click here for more info: 👉 https://t.co/uHo9cnIlJe 💙 Arxiv: