Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis5 months ago
5 months ago
6 months ago
Postoperative glioma segmentation in CT image using deep feature fusion model guided by multi-sequence MRIs6 months ago
Combining DWI radiomics features with transurethral resection promotes the differentiation between muscle-invasive bladder cancer and non-muscle-invasive bladder cancer7 months ago
Multiparametric MRI and auto-fixed volume of interest-based radiomics signature for clinically significant peripheral zone prostate cancer8 months ago
Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images9 months ago
MRI-based radiomics nomogram may predict the response to induction chemotherapy and survival in locally advanced nasopharyngeal carcinoma10 months ago
Welcome to the blog on Artificial Intelligence of the European Society of Radiology
This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.
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- CTO Peter Schardt talks radiology tech and innovation at premium ESOR event
- AI for reading screening mammograms: the need for circumspection
- Deep learning for the determination of myometrial invasion depth and automatic lesion identification in endometrial cancer MR imaging
- Can training data help radiologists to open deep learning black box?
- Looking outside the box: inspector robots, machine learning helping to catalogue history, and sanitizing work spaces without humans