Papers Metal Artifact Reduction
“Metal Artifact Reduction” 태그가 달린 논문 48편 · 필터 해제
Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact Reduction
Metal artifacts in computed tomography (CT) images can significantly degrade image quality and impede accurate diagnosis. Supervised metal artifact reduction (MAR) methods, trained using simulated datasets, often struggl…
Computed Tomography (CT)Metal Artifact ReductionMAR-DTN: Metal Artifact Reduction using Domain Transformation Network for Radiotherapy Planning
For the planning of radiotherapy treatments for head and neck cancers, Computed Tomography (CT) scans of the patients are typically employed. However, in patients with head and neck cancer, the quality of standard CT sca…
Computed Tomography (CT)Metal Artifact ReductionDual-Domain CLIP-Assisted Residual Optimization Perception Model for Metal Artifact Reduction
Metal artifacts in computed tomography (CT) imaging pose significant challenges to accurate clinical diagnosis. The presence of high-density metallic implants results in artifacts that deteriorate image quality, manifest…
Computed Tomography (CT)Contrastive LearningMetal Artifact ReductionPrompt EngineeringPixel-weighted Multi-pose Fusion for Metal Artifact Reduction in X-ray Computed Tomography
X-ray computed tomography (CT) reconstructs the internal morphology of a three dimensional object from a collection of projection images, most commonly using a single rotation axis. However, for objects containing dense …
Computed Tomography (CT)Metal Artifact ReductionObjectUnlocking the Potential of Early Epochs: Uncertainty-aware CT Metal Artifact Reduction
In computed tomography (CT), the presence of metallic implants in patients often leads to disruptive artifacts in the reconstructed images, hindering accurate diagnosis. Recently, a large amount of supervised deep learni…
Computed Tomography (CT)Metal Artifact ReductionSolving Energy-Independent Density for CT Metal Artifact Reduction via Neural Representation
X-ray CT often suffers from shadowing and streaking artifacts in the presence of metallic materials, which severely degrade imaging quality. Physically, the linear attenuation coefficients (LACs) of metals vary significa…
Image InpaintingMetal Artifact ReductionMARformer: An Efficient Metal Artifact Reduction Transformer for Dental CBCT Images
Cone Beam Computed Tomography (CBCT) plays a key role in dental diagnosis and surgery. However, the metal teeth implants could bring annoying metal artifacts during the CBCT imaging process, interfering diagnosis and dow…
Metal Artifact ReductionUnsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains
During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Several supervised deep learning-based approaches have been pro…
Computed Tomography (CT)Metal Artifact ReductionNeural Representation-Based Method for Metal-induced Artifact Reduction in Dental CBCT Imaging
This study introduces a novel reconstruction method for dental cone-beam computed tomography (CBCT), focusing on effectively reducing metal-induced artifacts commonly encountered in the presence of prevalent metallic imp…
CT ReconstructionMetal Artifact ReductionDense Transformer based Enhanced Coding Network for Unsupervised Metal Artifact Reduction
CT images corrupted by metal artifacts have serious negative effects on clinical diagnosis. Considering the difficulty of collecting paired data with ground truth in clinical settings, unsupervised methods for metal arti…
DisentanglementMetal Artifact ReductionUnsupervised Polychromatic Neural Representation for CT Metal Artifact Reduction
Emerging neural reconstruction techniques based on tomography (e.g., NeRF, NeAT, and NeRP) have started showing unique capabilities in medical imaging. In this work, we present a novel Polychromatic neural representation…
Metal Artifact ReductionNeRFMEPNet: A Model-Driven Equivariant Proximal Network for Joint Sparse-View Reconstruction and Metal Artifact Reduction in CT Images
Sparse-view computed tomography (CT) has been adopted as an important technique for speeding up data acquisition and decreasing radiation dose. However, due to the lack of sufficient projection data, the reconstructed CT…
Computed Tomography (CT)Metal Artifact ReductionRetinexFlow for CT metal artifact reduction
Metal artifacts is a major challenge in computed tomography (CT) imaging, significantly degrading image quality and making accurate diagnosis difficult. However, previous methods either require prior knowledge of the loc…
Computed Tomography (CT)Metal Artifact ReductionOrientation-Shared Convolution Representation for CT Metal Artifact Learning
During X-ray computed tomography (CT) scanning, metallic implants carrying with patients often lead to adverse artifacts in the captured CT images and then impair the clinical treatment. Against this metal artifact reduc…
Computed Tomography (CT)Metal Artifact ReductionMetal-conscious Embedding for CBCT Projection Inpainting
The existence of metallic implants in projection images for cone-beam computed tomography (CBCT) introduces undesired artifacts which degrade the quality of reconstructed images. In order to reduce metal artifacts, proje…
Metal Artifact ReductionTriDoNet: A Triple Domain Model-driven Network for CT Metal Artifact Reduction
Recent deep learning-based methods have achieved promising performance for computed tomography metal artifact reduction (CTMAR). However, most of them suffer from two limitations: (i) the domain knowledge is not fully em…
Contrastive LearningMetal Artifact ReductionMetal Inpainting in CBCT Projections Using Score-based Generative Model
During orthopaedic surgery, the inserting of metallic implants or screws are often performed under mobile C-arm systems. Due to the high attenuation of metals, severe metal artifacts occur in 3D reconstructions, which de…
Metal Artifact ReductionDeep learning based projection domain metal segmentation for metal artifact reduction in cone beam computed tomography
Metal artifact correction is a challenging problem in cone beam computed tomography (CBCT) scanning. Metal implants inserted into the anatomy cause severe artifacts in reconstructed images. Widely used inpainting-based m…
AnatomyDeep LearningMetal Artifact ReductionSegmentationQuad-Net: Quad-domain Network for CT Metal Artifact Reduction
Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various methods were developed for CT metal art…
Computed Tomography (CT)DiagnosticMetal Artifact ReductionAdaptive Convolutional Dictionary Network for CT Metal Artifact Reduction
Inspired by the great success of deep neural networks, learning-based methods have gained promising performances for metal artifact reduction (MAR) in computed tomography (CT) images. However, most of the existing approa…
Computed Tomography (CT)Metal Artifact Reduction