Robot-assisted medical imaging entails the use of a robot to acquire a medical image.
Examples include robot-assisted endoscopic camera imaging, ultrasound imaging where …

Data recovery from monolithic storage devices (MSDs) is in high demand for legal or
business purposes. However, the conventional data recovery methods are destructive …

Optical coherence tomography (OCT) can be used to image microstructures of human
kidneys. However, current OCT probes exhibit inadequate field-of-view, leading to …

Optical coherence tomography angiography (OCTA) can provide depth resolved image of
microvasculature but fail to acquire both high resolution and large field imaging of an …

Deep learning has been successfully applied to OCT segmentation. However, for data from
different manufacturers and imaging protocols, and for different regions of interest (ROIs), it …

Purpose: To evaluate the diagnostic performance of a robotically aligned optical coherence
tomography (RAOCT) system coupled with a deep learning model in detecting referable …

Diabetic macular edema (DME) has emerged as the foremost cause of vision loss in the
population with diabetes. Early detection of DME is paramount, yet the prevailing screening …

The detection of latent fingerprints plays a crucial role in criminal investigations and
biometrics. However, conventional techniques are limited by their lack of depth-resolved …

Optical coherence tomography (OCT) has revolutionized diagnostics in ophthalmology.
However, it requires pa-tient cooperation to fixate on multiple targets and stabilize their head …

Photoreceptor loss and resultant thinning of the outer nuclear layer (ONL) is an important
pathological feature of retinal degenerations and may serve as a useful imaging biomarker …