Borderless research group

55 posts

Borderless research group

Borderless research group

@BorderlessSci

Our mission is to reduce health inequalities, democratize rare healthcare expertise, and to develop novel, computational techniques for health data.

Katılım Temmuz 2021
13 Takip Edilen45 Takipçiler
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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
🔎 New method in #MICCAI24 for distilling image data, analysing latent graphs, reducing the need for extensive datasets in histopathology. This allows for the creation of a small set of synthetic images that encapsulate the most critical information from large datasets.
Zhe.Li@ZheLi_FAU

🏆Big announcement! Our paper Image Distillation for Safe Data Sharing in Histopathology has been accepted by #MICCAI2024 @BernhardKainz1 arxiv.org/abs/2406.13536

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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
Fully synthetic datasets are becoming a reality. We show how to make them in @reynaud_h et al.'s latest #MICCAI24 work. Such datasets promise to solve significant data-sharing challenges in medicine by ensuring complete patient privacy, as it contains no data from real patients
Hadrien Reynaud@reynaud_h

🚨Our latest work on data generation, privacy preservation and surrogate datasets has been (early-)accepted at #MICCAI24 ! And the generation process 120x faster than last year ! 🚀 🌟EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data Sharing 🌟

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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
💨 We explored @geoffreyhinton's forward-forward ⏩⏩ learning concept and discovered some new methods to deliver rapid and resource-efficient adaptable #MachineLearning for numerous tasks in medical image analysis. More to come... ⏩⏩
Johanna P Mueller@Hanna_Paulaluap

🚀🩻 Great News! Our paper on Resource-efficient Forward-Forward networks without Back-propagation for Medical Imaging Analysis has been accepted to the #MLMI workshop at MICCAI 2024!🌍💫 @MICCAI_Society @BorderlessSci @aibe_fau @UniFAU @BernhardKainz1 arxiv.org/abs/2406.14038

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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
Fantastic work about interpretability constraints in large multi-modal language-vision #MachineLearning models by @DombrowskiMN presented @RealAAAI this week (oral).
Mischa Dombrowski@DombrowskiMN

Thrilled to announce that this week, I had the fantastic opportunity to present our paper 'Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability' as an oral presentation at @RealAAAI as part of the main conference - Safe, Robust, and Responsible AI Track

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Christian Ledig
Christian Ledig@LedigChr·
🎓Interested in pursuing fully-funded PhD or PostDoc research in (medical) image computing or explainable machine learning in general? 🚨We are currently hiring in our xAI-Lab @uni_bamberg_of Get in touch and we can chat at #MICCAI2023 @MICCAI_Society Details below.
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Daniel Rueckert
Daniel Rueckert@DanielRueckert·
Interested in topology preserving brain segmentation? Check out Liu Li’s poster at #MICCAI2023
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Daniel Rueckert
Daniel Rueckert@DanielRueckert·
Conditional Temporal Attention Networks for cortical surface reconstruction by @QiangMa_ at #MICCAI2023
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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
Addressing motion in abdominal MRI, especially in IBD patients, we propose a deep adversarial super-resolution approach that corrects motion artefacts without needing detailed intestine knowledge or paired data. 🏥🖼️ @aibe_fau @BioMedIAICL @BorderlessSci #MICCAI2023 W-06-062
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RSIP Vision
RSIP Vision@RSIPvision·
Good morning MICCAI! MICCAI Daily of today (Wednesday) Important community information at page 23! Great poster reviews, great interviews and 5 mind-blowing slides of keynote Yann LeCun. ==> rsipvision.com/MICCAI2023-Wed… Happy reading and have a great day at MICCAI 2023! @RSIPvision
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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
CoTAN for rapid, high-accuracy neonatal brain cortical surface reconstruction using MRI. With conditional attention mechanisms, @QiangMa_ efficiently predicts surface deformations, achieving minimal errors. 🧠👶 @aibe_fau @BioMedIAICL @BorderlessSci #MICCAI2023 W-05-023
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Bernhard Kainz
Bernhard Kainz@BernhardKainz1·
#ML in medical image segmentation struggles with topological accuracy. We introduce the Euler Characteristic (EC) for efficient and accurate topological constraints, enhancing segmentation quality. 🧠🖼️ @aibe_fau @BioMedIAICL @BorderlessSci #MICCAI2023 W-05-090
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Daniel Rueckert
Daniel Rueckert@DanielRueckert·
Come and see Shuting’s poster on predicting outcome after stroke at #MICCAI2023
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