Deep learning (DL) is a type of artificial intelligence (AI) that utilizes artificial neural networks (ANNs) to process data through two or more layers, each of which can recognize complex features of ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

In existing breast cancer prediction research, most models rely solely on a single type of imaging data, which limits their performance. To overcome this limitation, the present study explores breast ...

The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is ...

Engineering researchers at the University of California, Los Angeles (UCLA) have developed an advanced ...

Combining microscopy, scanning, and deep learning enables more precise imaging of functional dynamics in neural networks of human cortical organoids.

Subcortical ischemic vascular disease (SIVD), driven by cerebral small vessel disease, is commonly characterized by white matter hyperintensities and multiple lacunar infarcts, and a substantial ...

COPD is widely recognized as a disease that affects more than just the lungs. Patients frequently experience systemic ...

The integration of AI into digital pathology has the potential to transform cancer diagnostics by enabling scalable, ...

Researchers have developed a method that leverages artificial intelligence to ensure accurate heart scans without added radiation or cost. Coronary artery disease is the leading cause of death ...

Gastric cancer remains one of the leading causes of cancer-related mortality worldwide, primarily due to late-stage diagnosis ...

Recent years have witnessed great advances in applying deep learning to improve fluorescence microscopy imaging. However, enhancing the fidelity of image restoration networks and improving their ...