computed tomography
PulseAugur coverage of computed tomography — every cluster mentioning computed tomography across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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SynthRAD2025 challenge shows AI improves synthetic CT for radiotherapy
The SynthRAD2025 challenge report details advancements in generating synthetic computed tomography (sCT) images for radiotherapy planning. This year's challenge focused on converting MRI or cone-beam CT (CBCT) into CT-e…
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New H3D-MarNet framework enhances CT image quality for radiotherapy
Researchers have developed H3D-MarNet, a novel two-stage framework designed to improve CT image quality for radiotherapy. The system first suppresses metal artifacts using wavelet-based denoising and then transforms kil…
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Insurance companies deny coverage for common neck surgery implants, overriding medical consensus.
Insurance companies are increasingly refusing to cover interbody device spacers used in anterior cervical discectomy and fusion (ACDF) surgeries, labeling them as experimental. This practice overrides current medical ev…
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Medical foundation models lag behind radiomics for renal lesion CT analysis
A new benchmark study evaluated the effectiveness of three medical foundation models (FMs) for stratifying renal lesions in CT scans. While FMs showed promise by matching the performance of a 3D ResNet trained from scra…
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LLMs filter clinical scans to create whole-body CT reference charts
Researchers have developed an LLM-based system to filter pathological findings from clinical CT scan reports. This method allows for the creation of healthier reference cohorts from over 350,000 CT examinations. The sys…
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MedGemma 1.5 model enhances medical imaging and EHR understanding
Researchers have introduced MedGemma 1.5 4B, an advanced medical AI model designed to handle diverse medical data modalities. This new version integrates capabilities for high-dimensional medical imaging like CT and MRI…
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MedSR-Vision framework benchmarks deep learning for medical image super-resolution
Researchers have developed MedSR-Vision, a new deep learning framework designed to enhance the quality of medical images across various modalities like MRI, CT, and X-ray. This framework allows for the evaluation and co…
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Researchers develop region-adaptive AI for enhanced CT image reconstruction
Researchers have developed RA-CMF, a novel conditional MeanFlow pipeline for CT image reconstruction that enhances image quality for cancer diagnosis. The system uses a conditional MeanFlow network to predict image-cond…
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New self-supervised methods improve low-dose CT denoising for medical imaging
Researchers have developed new self-supervised learning methods for denoising low-dose CT scans, a crucial step for reducing radiation exposure in medical imaging. One approach, Progressive $\mathcal{J}$-Invariant Learn…
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AI lung nodule screening sensitivity varies with CT reconstruction and nodule phase
A new paper explores how the position of a lung nodule within a CT scan's reconstruction cycle, known as z-phase, can significantly impact the sensitivity of AI-based detection systems. The study found that when the rat…
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AI optimizes surgical planning for enhanced bone union in mandibular reconstruction
Researchers have developed OsteoOpt++, a novel image-to-decision planning loop designed to enhance bone union in mandibular reconstruction surgeries. This system creates a personalized digital twin from pre-operative CT…
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New augmentation technique boosts medical image segmentation across CT and MRI
Researchers have developed a novel data augmentation technique to improve the cross-modality generalization of deep learning models for 3D spine segmentation in medical imaging. This approach significantly boosts perfor…
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AI generates synthetic PET scans to improve lung cancer histology classification
Researchers have developed a novel framework using a 3D Pix2Pix Generative Adversarial Network (GAN) to create synthetic PET scans from CT data for non-small cell lung cancer (NSCLC) histology classification. This "virt…
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New Gated Differential Linear Attention boosts medical image segmentation accuracy
Researchers have developed a new Gated Differential Linear Attention (GDLA) mechanism designed to improve medical image segmentation. This approach combines the efficiency of linear attention with enhanced boundary pres…
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Mayo Clinic AI model detects pancreatic cancer up to three years earlier
Mayo Clinic has developed an AI model named REDMOD that can detect pancreatic cancer on routine CT scans up to three years earlier than current methods. The model analyzes hundreds of imaging features to identify subtle…
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Deep learning models segment peritoneal cancer regions in CT scans
Researchers have developed a deep learning method to automatically segment regions for the radiological Peritoneal Cancer Index (rPCI) from CT scans. The study evaluated nnU-Net and Swin UNETR on 62 CT scans, with nnU-N…
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Zuckerberg's Biohub commits $500M to AI biology, Mayo Clinic AI spots cancer early
Mark Zuckerberg and Priscilla Chan's Biohub has launched a $500 million Virtual Biology Initiative aimed at accelerating AI's role in understanding and combating disease. The five-year project will focus on generating v…
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Simple MIL matches complex models for 3D neuroimage classification
Researchers have published a benchmark comparing multiple instance learning (MIL) methods against 3D CNNs and ViTs for classifying 3D neuroimages. The study found that a simple mean pooling MIL approach, without attenti…
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AI and VR create patient-specific surgical simulations from medical scans
Researchers have developed a novel system that uses AI and computer vision to create patient-specific virtual reality simulations for spine surgery training. This platform automates the generation of 3D anatomical model…
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Withdrawn paper proposes novel 3D BIT for medical imaging volume computation
A research paper introduced a novel algorithm for accurately computing the volume of 3D reconstructed models from medical imaging data, such as CT and MR scans. The method combines calculus, the marching cube algorithm,…