AIMC Journal:
European radiology
Showing 641 to 646 of 646 articles
Preoperative prediction of malignant transformation in sinonasal inverted papilloma: a novel MRI-based deep learning approach.
European radiology
May 12, 2025
OBJECTIVE: To develop a novel MRI-based deep learning (DL) diagnostic model, utilizing multicenter large-sample data, for the preoperative differentiation of sinonasal inverted papilloma (SIP) from SIP-transformed squamous cell carcinoma (SIP-SCC).
Performance of fully automated deep-learning-based coronary artery calcium scoring in ECG-gated calcium CT and non-gated low-dose chest CT.
European radiology
May 10, 2025
OBJECTIVES: This study aimed to validate the agreement and diagnostic performance of a deep-learning-based coronary artery calcium scoring (DL-CACS) system for ECG-gated and non-gated low-dose chest CT (LDCT) across multivendor datasets.
Medical machine learning operations: a framework to facilitate clinical AI development and deployment in radiology.
European radiology
May 8, 2025
The integration of machine-learning technologies into radiology practice has the potential to significantly enhance diagnostic workflows and patient care. However, the successful deployment and maintenance of medical machine-learning (MedML) systems ...
nnU-Net-based high-resolution CT features quantification for interstitial lung diseases.
European radiology
May 8, 2025
OBJECTIVES: To develop a new high-resolution (HR)CT abnormalities quantification tool (CVILDES) for interstitial lung diseases (ILDs) based on the nnU-Net network structure and to determine whether the quantitative parameters derived from this new so...
Predicting treatment response to systemic therapy in advanced gallbladder cancer using multiphase enhanced CT images.
European radiology
May 8, 2025
BACKGROUND: Accurate estimation of treatment response can help clinicians identify patients who would potentially benefit from systemic therapy. This study aimed to develop and externally validate a model for predicting treatment response to systemic...
Minimally interactive segmentation of soft-tissue tumors on CT and MRI using deep learning.
European radiology
May 1, 2025
BACKGROUND: Segmentations are crucial in medical imaging for morphological, volumetric, and radiomics biomarkers. Manual segmentation is accurate but not feasible in clinical workflow, while automatic segmentation generally performs sub-par.
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