AIMC Topic: Artifacts

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Metal Artifacts Reduction in CT Scans using Convolutional Neural Network with Ground Truth Elimination.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Metal artifacts are very common in CT scans since metal insertion or replacement is performed for enhancing certain functionality or mechanism of patient's body. These streak artifacts could degrade CT image quality severely, and consequently, they c...

Automatic detection of artifacts in EEG by combining deep learning and histogram contour processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper introduces a simple approach combining deep learning and histogram contour processing for automatic detection of various types of artifact contaminating the raw electroencephalogram (EEG). The proposed method considers both spatial and tem...

Deep Learning for Low-Dose CT Denoising Using Perceptual Loss and Edge Detection Layer.

Journal of digital imaging
Low-dose CT denoising is a challenging task that has been studied by many researchers. Some studies have used deep neural networks to improve the quality of low-dose CT images and achieved fruitful results. In this paper, we propose a deep neural net...

Highly accurate and explainable detection of specimen mix-up using a machine learning model.

Clinical chemistry and laboratory medicine
Background Delta check is widely used for detecting specimen mix-ups. Owing to the inadequate specificity and sparseness of the absolute incidence of mix-ups, the positive predictive value (PPV) of delta check is considerably low as it is labor consu...

Multimodal Medical Image Fusion using Rolling Guidance Filter with CNN and Nuclear Norm Minimization.

Current medical imaging
BACKGROUND: Medical image fusion is very important for the diagnosis and treatment of diseases. In recent years, there have been a number of different multi-modal medical image fusion algorithms that can provide delicate contexts for disease diagnosi...

[Use of artificial intelligence for image reconstruction].

Der Radiologe
CLINICAL/METHODOLOGICAL PROBLEM: In the reconstruction of three-dimensional image data, artifacts that interfere with the appraisal often occur as a result of trying to minimize the dose or due to missing data. Used iterative reconstruction methods a...

One network to solve all ROIs: Deep learning CT for any ROI using differentiated backprojection.

Medical physics
PURPOSE: Computed tomography for the reconstruction of region of interest (ROI) has advantages in reducing the x-ray dose and the use of a small detector. However, standard analytic reconstruction methods such as filtered back projection (FBP) suffer...

Metal artifact reduction for practical dental computed tomography by improving interpolation-based reconstruction with deep learning.

Medical physics
PURPOSE: Metal artifact is a quite common problem in diagnostic dental computed tomography (CT) images. Due to the high attenuation of heavy materials such as metal, severe global artifacts can occur in reconstructions. Typical metal artifact reducti...

The Role of Generative Adversarial Networks in Radiation Reduction and Artifact Correction in Medical Imaging.

Journal of the American College of Radiology : JACR
Adversarial networks were developed to complete powerful image-processing tasks on the basis of example images provided to train the networks. These networks are relatively new in the field of deep learning and have proved to have unique strengths th...

Hybrid Neural Network for Photoacoustic Imaging Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Photoacoustic imaging (PAI) is an emerging noninvasive imaging modality combining the advantages of ultrasound imaging and optical imaging. Image reconstruction is an essential topic in photoacoustic imaging, which is unfortunately an ill-posed probl...