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Medical Imaging

Image: Deep-learning segmentation of cine cardiac MRI images in end-diastole from a patient with non-ischaemic cardiomyopathy (Joy G, Punjabi K, Searle G et al. The Lancet Digital Health (2026). DOI: 10.1016/j.landig.2026.101042)

Cardiac MRI AI Tool Improves Mortality Risk Prediction

An AI approach to cardiac MRI ejection fraction measurement improves mortality risk prediction and speeds analysis. More...
05 Nov 2026
Image Credit: Adobe Stock

AI-Supported Approach May Improve Cervical Cancer Screening in Low-Resource Settings

An AI approach combining self-collected HPV testing with image analysis improves detection of high-grade cervical precancer in low-resource settings. More...
04 Nov 2026
Image: Two breast cancer tumors of similar size can have markedly different imaging features. Using advanced radiomics techniques, the research team identifies subtle differences in magnetic resonance images that are difficult to detect through conventional observation. This allows tumor images to provide information beyond size and location that can help predict drug response. (Image Credit: Hong Kong Polytechnic University)

Imaging Biomarker Links Breast Tumor Heterogeneity to Targeted Therapy Response

An MRI-based imaging index predicts targeted therapy response before treatment, outperforming receptor testing in breast cancer. More...
04 Nov 2026
Image Credit: Adobe Stock

AI-Guided Echocardiography Enables Mobile Cardiac Imaging in Rural Communities

An AI-guided echocardiography system lets nonsonographers capture diagnostic images in rural areas with remote review. More...
04 Nov 2026
Image: Medical imaging supports the planning of modern radiation therapy, with federated AI approaches possibly opening up new prospects. (Image Credit: Magali Hauser, KIT)

Privacy-Preserving AI Tool Synthesizes CT for Radiation Therapy Planning

An AI approach using federated learning generates privacy-friendly synthetic CT from MRI/CBCT to support radiotherapy planning. More...
02 Nov 2026
Image: Graphical summary of Q1–Q3 to localize discriminative radiomic signal: (a) preprocessing window versus mask-only; (b) sensitivity to mask erosion/dilation; (c) pure concentric-shell predictiveness. (Brahimetaj, R., Cornelis, J., Courtoy, G. et al. Breast Cancer Research, 2026. https://doi.org/10.1186/s13058-026-02362-0)

Tissue Around Breast Microcalcifications Emerges as a Key Source of Diagnostic Information

An AI approach analyzes tissue around breast microcalcifications to enhance benign–malignant classification. More...
02 Nov 2026
Image: The highlighted areas on MRI scans of patients with multiple sclerosis correspond to characteristic affected regions of various types. Modern computer vision models effectively detect the areas marked in red but have a hard time spotting the green ones. (Photo courtesy of Nadezhda Alsahanova et al.)

AI Approach Improves Brain MRI Lesion Detection in Epilepsy and Multiple Sclerosis

An AI approach steers MRI segmentation to key features, improving subtle epilepsy and MS lesion detection. More...
29 Oct 2026
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The Medical Imaging channel of HospiMedica deals with Radiography, MRI, Ultrasound, Nuclear Medicine, and similar items.
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