A new study from ⁦Ospedale San Raffaele⁩ NET team reveals the potential of ☢️68Ga-PET #radiomics in aiding surgical planning for pancreatic NET
📈Increase diagnostic sensitivity from 24% to 77% in detecting nodal metastases link.springer.com/article/10.100…

Great start to #ARS2024 with #MedPhys and #RadBio on normal tissue toxicity ranging from biomarkers to radiomics and patient outcomes! Thanks to Lauren E. Colbert, MD MSCR for being an outstanding co-organizer for Amer. Radium Society!

CRUK Cambridge Centre and Cambridge #ECMC members attending the Cancer Core Europe #CCE_DART annual meeting Karolinska Institutet. Fantastic talks and great progress made 👏🏼
#imaging #AI #translationalresearch #radiomics #clinicaltrials #ctDNA #Collaboration #statistics #genomics

'The existence of multiple frameworks catering to #radiomics researchers and educators instills optimism for expediting the translation of radiomics into clinical practice.'

#EuropeanRadiology

👇 New on the #AI blog from Hyun Ko and Kevin Tran!
buff.ly/4bmie6V

❓ Are radiomics features reproducible across readers?

🧐 Multi-sequence MRI radiomics of colorectal liver metastases

🖇️ ejradiology.com/article/S0720-…

Elsevier Radiology Carlos Carnelli, MD

Breast #Ultrasound Study: #AI #Radiomics Model May Help Predict Lymphovascular Invasion with #BreastCancer diagnosticimaging.com/view/breast-ul…
ACR RFS ACR YPS American College of Radiology ARRS Society of Breast Imaging SBI RFS UCLA Radiology UCSF Imaging Mayo Clinic Radiology UofURadiology
#radiology #RadRes

Ya-Ting Jan et al. explain the development of an #AI model with #radiomics and #DeepLearning features extracted from CT images to distinguish benign from malignant ovarian tumors, showing improvement of less-experienced radiolgists. #InsightsIntoImaging

🔗buff.ly/4b8P8aV

🫁
Building on our #ArtificialInteligence theme. Dr Mitch Chen educating us on #radiomics . 🫁

#BSTI2024 Mitch Chen BSTI The Society of Radiologists in Training

Radiomics-based machine learning can predict gastric cancer treatment outcomes with improved accuracy, supporting personalized patient care. #GastricCancer #Radiomics #MachineLearning

Meta-analysis shows MRI radiomics can predict microvascular invasion in HCC with 82% sensitivity and 79% specificity, potentially refining pre-op assessments. Calls for more robust studies. #HCCRadiomics #MedicalImaging #CancerDiagnosis

The combination of #DTL features from #MR -T2WI, #radiomics features, and clinical characteristics can effectively predict #LVSI in cervical cancer.
med-sci.cn/cgzcx/article/…

Check out our collection of articles on 'Mitigating Bias' from MayoAILab Brad Erickson pubs.rsna.org/page/ai/mitiga… #ML #DeepLearning #Radiomics

Here is a sneak peek at tonight's #RadAIchat at 8 PM ET on 'Medical #AI Regulation: A Primer & Future Directions' moderated by Merel Huisman MD PhD Tugba Akinci D'Antonoli and panelists Dania Daye, MD PhD James Hillis Woojin Kim #radiomics #AI #DL #radres RSNA Charles Kahn, MD Hesham Elhalawani

Sign up online! Get e-mail alerts for The Vasty Deep, the Radiology: Artificial Intelligence editor's blog pubs.rsna.org/page/ai/blog #AI #DeepLearning #Radiomics

Advances in Radiomics Irène Buvat
Institute Curie
High-throughput extraction of quantitative features from medical images
⬆️precision medicine
ComBat harmonisation: international benchmarking (ie TMTV/Dmax) setting ref values
Add biomarker?
Req reproducibility
#MSKlymphomaCME

The #EuSoMII webinar #65 ‘The METhodological RadiomiCs Score’ by Renato Cuocolo , moderated by Pinar Yilmaz Pınar Yılmaz and Gennaro D'Anna, MD, EDiNR is now available at: eusomii.org/webinars/

Repeatability and reproducibility analysis identifies precise #radiomics features of CT tumor habitats in lung and liver lesions doi.org/10.1148/ryai.2… Kinga Bernatowicz Raquel Perez-Lopez Vall d’Hebron Institute of Oncology (VHIO) #habitats #CancerHabitats #DL

Explore leading-edge research in Radiology: Artificial Intelligence

➡️ pubs.rsna.org/journal/ai

@IPMI2023 #IPMI2024 #AI #DeepLearning #Radiomics

Repeatability and reproducibility analysis identifies precise #radiomics features of CT tumor habitats in lung and liver lesions doi.org/10.1148/ryai.2… Olivia Prior 🌸 Marta Ligero Radiomics Group #oncology #AI #ML

“Prior and colleagues offer important insights regarding the factors that most affect radiomics feature repeatability and reproducibility” doi.org/10.1148/ryai.2… Hersh Penn Radiology Penn Medicine #TumorHabitats #DeepLearning #MachineLearning