CT images of abdomen and pelvis: effect of nonlinear three-dimensional optimized reconstruction algorithm on image quality and lesion characteristics.
PulseAugur coverage of CT images of abdomen and pelvis: effect of nonlinear three-dimensional optimized reconstruction algorithm on image quality and lesion characteristics. — every cluster mentioning CT images of abdomen and pelvis: effect of nonlinear three-dimensional optimized reconstruction algorithm on image quality and lesion characteristics. across labs, papers, and developer communities, ranked by signal.
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New framework generates subcortical CT scan labels using MRI data
Researchers have developed a novel ensemble framework to generate subcortical segmentation labels for CT scans by transferring knowledge from existing MRI-based models. This approach addresses the scarcity of labeled CT…
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Few-shot deep learning framework improves transcranial focused ultrasound accuracy
Researchers have developed a novel few-shot deep learning framework to correct phase-amplitude aberrations in transcranial focused ultrasound (tFUS). This method utilizes a geometry-aware encoder to extract skull featur…
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New GRC-ProbNet method boosts cardiovascular disease classification accuracy
Researchers have developed GRC-ProbNet, an uncertainty-aware feature extraction method designed to improve cardiovascular disease (CVD) classification from CT images. This new approach builds upon the existing GRC-Net p…
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New AI model segments all blood vessels in CT scans
Researchers have developed vesselFM-CT, a novel model designed to segment all blood vessels within CT images. This advancement aims to overcome the limitations of previous studies that focused on isolated vascular segme…
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AI method automates cardiac fat segmentation with 98.4% accuracy
Researchers have developed an automated method for segmenting epicardial and mediastinal fats from CT images, aiming to improve health risk assessments. The proposed technique involves image registration, feature extrac…