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Computed Tomography (CT)

The term “computed tomography”, or CT, refers to a computerized x-ray imaging procedure in which a narrow beam of x-rays is aimed at a patient and quickly rotated around the body, producing signals that are processed by the machine's computer to generate cross-sectional images—or “slices”—of the body.

( Image credit: Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector )

Papers

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Showing 626–650 of 1207 papers

TitleStatusHype
Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction—0
Patch-based field-of-view matching in multi-modal images for electroporation-based ablations—0
PatchFCN for Intracranial Hemorrhage Detection—0
PathVLM-R1: A Reinforcement Learning-Driven Reasoning Model for Pathology Visual-Language Tasks—0
PELE scores: Pelvic X-ray Landmark Detection by Pelvis Extraction and Enhancement—0
PEMMA: Parameter-Efficient Multi-Modal Adaptation for Medical Image Segmentation—0
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling—0
PhD Thesis. Computer-Aided Assessment of Tuberculosis with Radiological Imaging: From rule-based methods to Deep Learning—0
PHT-bot: Deep-Learning based system for automatic risk stratification of COPD patients based upon signs of Pulmonary Hypertension—0
Physics-Based Iterative Reconstruction for Dual Source and Flying Focal Spot Computed Tomography—0
Physiology-Informed Generative Multi-Task Network for Contrast-Free CT Perfusion—0
PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans—0
Pitfalls of defacing whole-head MRI: re-identification risk with diffusion models and compromised research potential—0
Pixel-weighted Multi-pose Fusion for Metal Artifact Reduction in X-ray Computed Tomography—0
PFCM: Poisson flow consistency models for low-dose CT image denoising—0
Predicting Lung Cancer's Metastats' Locations Using Bioclinical Model—0
Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models—0
Prediction of post-radiotherapy recurrence volumes in head and neck squamous cell carcinoma using 3D U-Net segmentation—0
Prediction of recurrence free survival of head and neck cancer using PET/CT radiomics and clinical information—0
Pristine annotations-based multi-modal trained artificial intelligence solution to triage chest X-ray for COVID-19—0
Probabilistic self-learning framework for Low-dose CT Denoising—0
ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification—0
PSGR: Pixel-wise Sparse Graph Reasoning for COVID-19 Pneumonia Segmentation in CT Images—0
Pulmonary Artery–Vein Classification in CT Images Using Deep Learning—0
Pyramid Focusing Network for mutation prediction and classification in CT images—0
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