Bettina Baeßler

UKW #radiologist; #radiomics; #MachineLearning; #deeplearning; #AI; #CMR; education; #diversity; #inclusion; @DRG.de; @EurRadiology

[Hyun Ko @HyunKoMD]

Fresh off the press @EurRadiology
Advancing radiomics research translation through a public database
https://t.co/pIWpUZf85u

Commentary to an article by @Tugba_Akinci_MD @Baessler_Rad @renatocuocolo @pintodrad https://t.co/waP6yeb8Xv

[Bettina Baeßler @Baessler_Rad]

Congratulations to the winners! 👏🥳 Well deserved. #EuropeanRadiology @renatocuocolo @cannella_rob https://t.co/DyDTApD2bQ @EurRadiology @InsightsImaging @EuSoMII

[Roberto Cannella @cannella_rob]

@EuSoMII Award to the most cited papers in @InsightsImaging and @EurRadiology!

Congratulations to the winners 🏆 🏆

@renatocuocolo @pintodrad

[Bettina Baeßler @Baessler_Rad]

Interesting study on the reproducibility of radiomics 👇 #EuropeanRadiology

[ESR Journals @ESRJournals]

Using a convolutional neural network-based image conversion technique significantly improves the reproducibility of radiomic features in hepatocellular carcinomas. (Heejin Lee et al)

#EuropeanRadiology

🔗 https://t.co/0UYMI2iYJT

[EuSoMII @EuSoMII]

🤩 Hurray! The 17th chapter on AI in Radiology from
@myESR 's Undergraduate Education e-book is out!

👏Thanks all the @EuSoMII contributors!

Available fo free https://t.co/RJjHUWD3NY

#AI #MedicalImaging #Education #eBook
#FreeResource #RadiologyAI

[ESR Journals @ESRJournals]

This study demonstrates the validity and reliability of automated ASPECTS evaluation for supporting neurologists in the clinical care process for acute ischemic stroke patients. (Shu Wan et al)

#EuropeanRadiology

🔗 https://t.co/Wd2JOaQvNH

[ESR Journals @ESRJournals]

The reproducibility across different VOI sizes in normal #liver #MRI was improved when translating images into parametric maps before feature extraction. (Laura Jacqueline Jensen et al.)

#EuropeanRadiologyExperimental

🔗 https://t.co/Ng7kNCJGLv

[Bettina Baeßler @Baessler_Rad]

I really like the new graphical abstracts in @EurRadiology! 👏 What do you think of it?

[ESR Journals @ESRJournals]

📣 Introducing this exciting new meta-research by Dr. Hameed et al (@MairaHameed_) from @UCLHresearch @DoM_UCL published in #EuropeanRadiology

Follow the 🧵 for more insight by Dr. Hameed

1/6

[ESR Journals @ESRJournals]

Application of #AI-derived contours yields results comparable to manual segmentations. (Jan Gröschel et al.)

#EuropeanRadiology

Read more here 👉 https://t.co/ut3xW957dv

[Bettina Baeßler @Baessler_Rad]

Interesting study, thanks for sharing @BernhardKainz1 !

[Bernhard Kainz @BernhardKainz1]

📢 Just out! A leap in object segmentation using pre-trained latent diffusion models! Generate accurate foreground-background models from textual descriptions WITHOUT segmentation labels. 🚀 Surpasses prior methods and nears fully supervised training. 🩺#AIResearch @BorderlessSci

[Insights into Imaging @InsightsImaging]

Critical Review: #Radiology #ArtificialIntelligence, a systematic evaluation of methods (RAISE). (@BSKellyRad et al.)

#InsightsIntoImaging

Want to learn more? Click here ➡️ https://t.co/PF4frpvL7d

[Insights into Imaging @InsightsImaging]

Educational Review: Role of diagnostic imaging in psoriatic #arthritis - how, when, and why. (Ana María Crespo-Rodríguez et al.)

#InsightsIntoImaging

🔗 https://t.co/NfZplZsQPN

[Bettina Baeßler @Baessler_Rad]

Still an underrecognized problem, but a tremendously important one (of course, not only in #radiology)! Interesting read 👇👇 #EuropeanRadiology

[ESR Journals @ESRJournals]

How prevalent is #burnout among #radiology residents and what are the risks? (Ziqi Wan et al.)

#EuropeanRadiology

Want to read more? Click the link below ⬇️
https://t.co/FLMqDffcGN

[ESR Journals @ESRJournals]

Commentary: Generalizability of prostate #MRI deep learning: does one size fit all data? (@StanzioneMD & @renatocuocolo)

#EuropeanRadiology

Commentary 👉 https://t.co/4kDTy4f5dn
Original Article 👉 https://t.co/ubv86vcHyU

[ESR Journals @ESRJournals]

Commentary: Explainable #AI - current status and future potential. (@BasvanderVelden)

#EuropeanRadiology

Read the full commentary here ➡️ https://t.co/5ybFiZhvlL

[Francis Deng, MD @francisdeng]

Apps for radiology residency are due soon. Do you know how competitive it's been?
We reviewed match data: https://t.co/cweHIvqkYb
with bonus thoughts in podcast: https://t.co/dqvpRlQL7p
Google https://t.co/8xWe2FP9c9; Apple https://t.co/rYml558hoD; Spotify https://t.co/Kn9nGFO0UP

[Bettina Baeßler @Baessler_Rad]

Thanks for sharing @Tugba_Akinci_MD! Looking forward to seeing more studies adhering to checklists like #CLAIM in the future. @EurRadiology

[Tugba Akinci D'Antonoli @Tugba_Akinci_MD]

Using the @Radiology_AI #CLAIM checklist is a crucial component in ensuring high-quality reporting of AI research in radiology

According to the recently published CLAIM citation analysis:
🧵👇

[Mike Klontzas @Klonmich]

The reproducibility of RQS is extremely low. This has now been highlighted in @EurRadiology and should be taken into account in future studies assessing the quality of radiomics analyses. @Tugba_Akinci_MD @renatocuocolo @EuSoMII

[Bettina Baeßler @Baessler_Rad]

Congrats on this important work, dear Radiomics Auditing Group! @EuSoMII

[Renato Cuocolo @renatocuocolo]

The RQS has undoubtedly had an important role in raising awareness on #radiomics and #MachineLearning research. It's also showing limitations, as seen in the latest @EuSoMII Radiomics Auditing Group paper. Now available on @EurRadiology (#openaccess). https://t.co/sv8222kp5z

[ESR Journals @ESRJournals]

#Cardiac implantable electronic device-related artefacts may reduce the diagnostic value of cardiac magnetic resonance. (Aino-Maija Vuorinen et al.)

#EuropeanRadiology #RadiologyHeadToToe

Read more here 👉 https://t.co/Xo8W5FmuCA

[Akshay Chaudhari @Dr_ASChaudhari]

Thanks @_akhaliq for featuring this work! A full thread on the methods/implications is

https://t.co/hmyQ1gSI8b