computed tomography
PulseAugur coverage of computed tomography — every cluster mentioning computed tomography across labs, papers, and developer communities, ranked by signal.
- instance of DagsHub 90%
- instance of alphaXiv 90%
- instance of Gotit.pub 90%
- instance of Cone Beam Ct 90%
- used by Segment Anything Model 80%
- used by Gaussian splatting 80%
- instance of magnetic resonance imaging 70%
- used by nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation 70%
- instance of ScienceCast 70%
- used by Gotit.pub 70%
- used by deep learning 70%
- developed by CatalyzeX 70%
19 day(s) with sentiment data
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New CADS dataset enables comprehensive whole-body CT segmentation
Researchers have introduced CADS, a comprehensive dataset and segmentation framework designed for whole-body anatomy in computed tomography (CT) scans. This new resource harmonizes anatomical labels from over 100 imagin…
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Uni-Loc framework achieves accurate 3D CT pathology localization with weak supervision
Researchers have developed Uni-Loc, a novel vision-language framework designed to accurately pinpoint abnormalities within 3D CT scans using only scan-level supervision. This method unifies pathology classification and …
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New framework QueryREPA enhances multimodality medical object detection
Researchers have developed a new framework called QueryREPA to improve multimodality medical object detection. This approach addresses the challenge of training a single detector on diverse medical imaging types like X-…
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ImageCLEFmedical 2026 task explores GANs for synthetic medical images and privacy
The 2026 ImageCLEFmedical GANs Task, now in its fourth iteration, focuses on the privacy and security implications of generating synthetic medical images. This year's task includes three subtasks: detecting real images …
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Automated CT scan pipeline aids prostatectomy phantom segmentation
Researchers have developed an automated 3D segmentation pipeline for prostate surgical phantoms using CT scans. This pipeline leverages anatomical priors and classical image-processing techniques, eliminating the need f…
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CUFormer framework enhances CT-Ultrasound registration for orthopedic navigation
Researchers have developed CUFormer, a novel framework designed to improve the accuracy of registering intraoperative Ultrasound (US) bone-surface point clouds with preoperative Computed Tomography (CT) models. This adv…
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MedHiVE framework enhances 3D medical imaging with hierarchical vision-language modeling
Researchers have developed MedHiVE, a novel framework for 3D medical vision-language modeling that addresses the limitations of existing models by incorporating hierarchical anatomical structure. MedHiVE utilizes a two-…
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New Ultrasound Guidance Testbed USB Gym Shows Limited Success
Researchers have developed USB Gym, a new testbed designed to evaluate methods for closed-loop ultrasound view matching. The system simulates ultrasound imaging from patient CT scans and allows for the integration of va…
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New TACT-KV method compresses 3D medical VLM caches, boosting batch size 8x
Researchers have developed TACT-KV, a novel method for compressing the key-value (KV) cache in vision-language models (VLMs) that process 3D medical imaging data. Unlike previous methods that only consider 1D or 2D tran…
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Taurus LLM system halves CT annotation cost, matches expert agents
Researchers have developed Taurus, a system that uses Large Language Models (LLMs) to assist in the annotation of computed tomography (CT) scans, specifically focusing on the aorta. In blind tests using public datasets,…
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MedHiVE framework uses hierarchical MoE for 3D medical vision-language modeling
Researchers have developed MedHiVE, a novel framework for 3D medical vision-language modeling that leverages a hierarchical Mixture-of-Experts (SMoE) architecture. This approach addresses the limitations of existing mod…
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SSFMamba framework enhances 3D medical image segmentation using symmetry and frequency modeling
Researchers have developed SSFMamba, a novel framework for 3D medical image segmentation that integrates spatial and frequency domain modeling. This approach, based on Mamba, incorporates Hermitian symmetry and a Multi-…
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New method assesses trustworthiness of 2D/3D registration for pelvic fracture surgery
Researchers have developed a method to assess the trustworthiness of multi-fragment 2D/3D registration for pelvic fracture fluoroscopy. This approach provides calibrated error bounds for each fracture fragment and flags…
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LungMend corrects TB CT lung masks using healthy-only diffusion model
Researchers have developed LungMend, a novel post-processing model designed to correct lung segmentation masks in computed tomography (CT) scans affected by severe tuberculosis. Unlike existing models that struggle with…
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HoloCT: New 3D Foundation Model Unifies CT Interpretation and Segmentation
Researchers have developed HoloCT, a novel 3D foundation model that unifies computed tomography (CT) interpretation and segmentation tasks. By jointly modeling whole-volume context and fine-grained anatomical detail, Ho…
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AI advancements viewed as a fever dream, with Anthropic warning of self-acceleration
A commentary piece from c't Magazin argues that current AI advancements are akin to a "fever dream," suggesting a disconnect from reality. In parallel, Anthropic has issued a warning about the potential for AI to enter …
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New AI framework diagnoses unseen diseases by composing radiological findings
Researchers have developed a new framework called Diagnosis by Composition (DbC) that aims to improve the interpretability and adaptability of deep learning models in radiological diagnosis. Unlike traditional models th…
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New Diffusion Model Enhances CT Image Synthesis from CBCT Data
Researchers have developed EPC-RawDC, a novel 3D diffusion framework for synthesizing CT images from CBCT data. This method integrates physics-based constraints, specifically geometry equivariance and raw data consisten…
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New method converts CT scans to real-time 3D Gaussian splats in minutes
Researchers have developed a new method called CTBakeGS that allows for the rapid conversion of computed tomography (CT) volume renderings into 3D Gaussian splatting (3DGS) models. This training-free approach significan…
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AI translates spinal MRI to CT for surgical planning
Researchers have developed a novel three-stage framework to synthesize Computed Tomography (CT) images from Magnetic Resonance Imaging (MRI) scans of the spine. This method aims to improve surgical planning by providing…