AIMC Topic: Artifacts

Clear Filters Showing 451 to 460 of 721 articles

DW-Net: A cascaded convolutional neural network for apical four-chamber view segmentation in fetal echocardiography.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Fetal echocardiography (FE) is a widely used medical examination for early diagnosis of congenital heart disease (CHD). The apical four-chamber view (A4C) is an important view among early FE images. Accurate segmentation of crucial anatomical structu...

Removal of computed tomography ring artifacts via radial basis function artificial neural networks.

Physics in medicine and biology
Ring artifacts in computed tomography (CT) images are caused by the undesirable response of detector pixels, which leads to the degradation of CT images. Accordingly, it affects the image interpretation, post-processing, and quantitative analysis. In...

CNN-based PET sinogram repair to mitigate defective block detectors.

Physics in medicine and biology
Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by adding an ever expanding array of block detectors. As they age, one or more block detectors may lose sensitivity due to a malfunction or component fail...

Orbit image analysis machine learning software can be used for the histological quantification of acute ischemic stroke blood clots.

PloS one
Our aim was to assess the utility of a novel machine learning software (Orbit Image Analysis) in the histological quantification of acute ischemic stroke (AIS) clots. We analyzed 50 AIS blood clots retrieved using mechanical thrombectomy procedures. ...

Skin lesion segmentation using high-resolution convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Skin lesion segmentation is an important but challenging task in computer-aided diagnosis of dermoscopy images. Many segmentation methods based on convolutional neural networks often fail to extract accurate lesion boundarie...

Twin Robotic X-Ray System for 3D Cone-Beam CT of the Wrist: An Evaluation of Image Quality and Radiation Dose.

AJR. American journal of roentgenology
The purpose of this study was to assess image quality and radiation dose of a novel twin robotic x-ray system's 3D cone-beam CT (CBCT) function for the depiction of cadaveric wrists. Sixteen cadaveric wrists were scanned using dedicated low-dose an...

A dual-stream deep convolutional network for reducing metal streak artifacts in CT images.

Physics in medicine and biology
Machine learning and deep learning are rapidly finding applications in the medical imaging field. In this paper, we address the long-standing problem of metal artifacts in computed tomography (CT) images by training a dual-stream deep convolutional n...

QSMGAN: Improved Quantitative Susceptibility Mapping using 3D Generative Adversarial Networks with increased receptive field.

NeuroImage
Quantitative susceptibility mapping (QSM) is a powerful MRI technique that has shown great potential in quantifying tissue susceptibility in numerous neurological disorders. However, the intrinsic ill-posed dipole inversion problem greatly affects th...

DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING.

Artificial intelligence in medicine
Today's life assistive devices were playing significant role in our life to communicate with others. In that modality Human Computer Interface (HCI) based Electrooculogram (EOG) playing vital part. By using this method we can able to overcome the con...