Papers with Code 아카이브
X-Ray
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Structure-Aware Sparse-View X-ray 3D Reconstruction
NAF: Neural Attenuation Fields for Sparse-View CBCT Reconstruction
TensoRF: Tensorial Radiance Fields
NeAT: Neural Adaptive Tomography
ADJUST: A Dictionary-Based Joint Reconstruction and Unmixing Method for Spectral Tomography
TorchXRayVision: A library of chest X-ray datasets and models
XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
4D X-Ray CT Reconstruction using Multi-Slice Fusion
Group-Attention Single-Shot Detector (GA-SSD): Finding Pulmonary Nodules in Large-Scale CT Images
Joint Vertebrae Identification and Localization in Spinal CT Images by Combining Short- and Long-Range Contextual Information
Adversarial Sparse-View CBCT Artifact Reduction
XNet: A convolutional neural network (CNN) implementation for medical X-Ray image segmentation suitable for small datasets
Learning Bone Suppression from Dual Energy Chest X-rays using Adversarial Networks
Shape and Margin-Aware Lung Nodule Classification in Low-dose CT Images via Soft Activation Mapping
Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction
Efficient Low Dose X-ray CT Reconstruction through Sparsity-Based MAP Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.