Recent advancements in MRI techniques and tumor biology have led to updated hepatocellular carcinoma (HCC) diagnostic guidelines from various liver study associations. Conducted across 11 South…
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Federated Learning (FL) enables collaborative model training without data centralization – a crucial aspect for radiological image analysis where privacy regulations would otherwise hinder the use of…
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Deep learning (DL) has become an important part of radiological image analysis. To train these deep-learning models, access to large and diverse datasets is required. While the use of a centralized…
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Our expert Steffen Rupp recently visited the Technical University of Munich to continue the on-site BZKF BORN Roll-Out Trainings. As mentioned earlier this month in a press release by the…
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The COVID-19 pandemic wreaked havoc on healthcare systems worldwide, requiring a comprehensive understanding of disease progression for optimal treatment strategies. Amidst this backdrop, the RACOON…
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Brain cancers account for more than 15% of childhood cancers and are the second most common childhood cancer [1]. Mint Medical is Going Gray in May to mark Brain Tumor Awareness Month in May, and…
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We all know the phrase “a picture is worth a thousand words”; yet, in specific fields, one thousand words are simply too many and can potentially prove problematic. Radiologists still usually prefer…
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A first impression of the on-site BZKF BORN Roll-Out Trainings at LMU Klinikum München with our expert Steffen Rupp. The project is in full swing: the templates that were previously developed at six…
GoToA multicenter study [1] based on the German research infrastructure project RACOON (Radiological Cooperative Network of the COVID-19 pandemic; a Netzwerk Universitätsmedizin project) investigated the…
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A recent study conducted at UKE Hamburg compared manual and software-assisted assessments of computed tomography (CT) scans according to iRECIST (immune Response Evaluation Criteria in Solid Tumors)…
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