SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 626–650 of 1207 papers

TitleStatusHype
Cross Modality 3D Navigation Using Reinforcement Learning and Neural Style TransferCode1
Diagnosis of COVID-19 Using Machine Learning and Deep Learning: A review—0
Novel coronavirus pneumonia lesion segmentation in CT images—0
"One-Shot" Reduction of Additive Artifacts in Medical Images—0
Cross-Vendor CT Image Data Harmonization Using CVH-CT—0
Stochastic Primal-Dual Deep Unrolling—0
GAN-based disentanglement learning for chest X-ray rib suppression—0
Body Part Regression for CT ImagesCode1
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans—0
Comparing One-step and Two-step Scatter Correction and Density Reconstruction in X-ray CT—0
Single volume lung biomechanics from chest computed tomography using a mode preserving generative adversarial network—0
A Teacher-Student Framework with Fourier Augmentation for COVID-19 Infection Segmentation in CT Images—0
CyTran: A Cycle-Consistent Transformer with Multi-Level Consistency for Non-Contrast to Contrast CT TranslationCode1
AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation—0
Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT's Semantic SegmentationCode0
Automated airway segmentation by learning graphical structure—0
Semi-Supervised Segmentation of Radiation-Induced Pulmonary Fibrosis from Lung CT Scans with Multi-Scale Guided Dense AttentionCode1
Improving Tuberculosis (TB) Prediction using Synthetically Generated Computed Tomography (CT) ImagesCode0
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search—0
Asymmetric 3D Context Fusion for Universal Lesion DetectionCode0
RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT ScansCode0
DeepMTS: Deep Multi-task Learning for Survival Prediction in Patients with Advanced Nasopharyngeal Carcinoma using Pretreatment PET/CTCode1
Conditional Synthetic Data Generation for Robust Machine Learning Applications with Limited Pandemic Data—0
Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learningCode1
Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CT—0
Show:102550
← PrevPage 26 of 49Next →

No leaderboard results yet.