AIMC Topic: Image Processing, Computer-Assisted

Clear Filters Showing 2581 to 2590 of 10288 articles

Neural network aided extended Kalman filtering for inverse imaging of cardiac transmembrane potential.

Physics in medicine and biology
The aim of this study is to address the limitations in reconstructing the electrical activity of the heart from the body surface electrocardiogram, which is an ill-posed inverse problem. Current methods often assume values commonly used in the litera...

Advancements in computer vision and pathology: Unraveling the potential of artificial intelligence for precision diagnosis and beyond.

Advances in cancer research
The integration of computer vision into pathology through slide digitalization represents a transformative leap in the field's evolution. Traditional pathology methods, while reliable, are often time-consuming and susceptible to intra- and interobser...

Comparison of image quality between Deep learning image reconstruction and Iterative reconstruction technique for CT Brain- a pilot study.

F1000Research
BACKGROUND: Non-contrast Computed Tomography (NCCT) plays a pivotal role in assessing central nervous system disorders and is a crucial diagnostic method. Iterative reconstruction (IR) methods have enhanced image quality (IQ) but may result in a blot...

Suppressing the HIFU interference in ultrasound guiding images with a diffusion-based deep learning model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In ultrasound guided high-intensity focused ultrasound (HIFU) surgery, it is necessary to transmit sound waves at different frequencies simultaneously using two transducers: one for the HIFU therapy and another for the ultr...

A retrospective study of deep learning generalization across two centers and multiple models of X-ray devices using COVID-19 chest-X rays.

Scientific reports
Generalization of deep learning (DL) algorithms is critical for the secure implementation of computer-aided diagnosis systems in clinical practice. However, broad generalization remains to be a challenge in machine learning. This research aims to ide...

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Scientific data
Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality...

An automated in vitro wound healing microscopy image analysis approach utilizing U-net-based deep learning methodology.

BMC medical imaging
BACKGROUND: The assessment of in vitro wound healing images is critical for determining the efficacy of the therapy-of-interest that may influence the wound healing process. Existing methods suffer significant limitations, such as user dependency, ti...

Binary classification of dead detector elements in flat panel detectors using convolutional neural networks.

Biomedical physics & engineering express
Medical physicists routinely perform quality assurance on digital detection systems, part of which involves the testing of flat panel detectors. Flat panels may degrade over time as an increasing number of individual detector elements begin to malfun...

CMR-net: A cross modality reconstruction network for multi-modality remote sensing classification.

PloS one
In recent years, the classification and identification of surface materials on earth have emerged as fundamental yet challenging research topics in the fields of geoscience and remote sensing (RS). The classification of multi-modality RS data still p...