A common problem in the field of deep-learning-based low-level vision medical images is
that most of the research is based on single task learning (STL), which is dedicated to …

Optical coherence tomography (OCT), an interferometric imaging technique, provides non-
invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However …

As a medical imaging modality, many researches have been devoted to improving the
resolution of optical coherence tomography (OCT). We developed a deep-learning based …

Machine learning has transformed ophthalmology, particularly in predictive and
discriminatory models for vitreoretinal pathologies. However, generative modeling …

High-resolution spectral domain optical coherence tomography (SD-OCT) is a vital clinical
technique that suffers from the inherent compromise between transverse resolution and …

Optical coherence tomography (OCT) is a fast and non-invasive optical interferometric
imaging technique that can provide high-resolution cross-sectional images of biological …

Optical coherence tomography (OCT) suffers from speckle noise, causing the deterioration
of image quality, especially in high-resolution modalities like visible light OCT (vis-OCT). The …

Optical coherence tomography (OCT) has stimulated a wide range of medical image-based
diagnosis and treatment in fields such as cardiology and ophthalmology. Such applications …

Accurate risk prediction for myocardial infarction (MI) is crucial for preventive strategies,
given its significant impact on global mortality and morbidity. Here, we propose a novel deep …

Achieving high resolution in optical coherence tomography typically requires the continuous
extension of the spectral bandwidth of the light source. This work demonstrates an …