Unmasking the potential: evaluating image inpainting techniques for masked face reconstruction.

The performance of most Face Recognizers tends to degrade when dealing with masked faces, making face recognition challenging. Image inpainting, a technique traditionally used for restoring old or damaged images, removing objects, or retouching photos, could potentially aid in reconstructing masked faces. In this paper, we compared three state-of-the-art image inpainting models-PatchMatch, a traditional algorithm, and two deep learning GAN-based models, Edge Connect and Free form image inpainting-to assess their performance in regenerating masked faces.

Effectual accuracy of OCT image retinal segmentation with the aid of speckle noise reduction and boundary edge detection strategy.

Optical coherence tomography (OCT) has shown to be a valuable imaging tool in the field of ophthalmology, and it is becoming increasingly relevant in the field of neurology. Several OCT image segmentation methods have been developed previously to segment retinal images, however sophisticated speckle noises with low-intensity restrictions, complex retinal tissues, and inaccurate retinal layer structure remain a challenge to perform effective retinal segmentation. Hence, in this research, complicated speckle noises are removed by using a novel far-flung ratio algorithm in which preprocessing has been done to treat the speckle noise thereby highly decreasing the speckle noise through new similarity and statistical measures.

Statistically Evaluating Detection Capabilities of Sub Retinal Fluid Detection Methodology in Optical Coherence Tomographic Images.

Significance of therapeutic imaging in medical image based diagnostics and treatment, and there in practice implementation in image investigation is undebatable. The cyst (fluid accumulation) development just above the Retinal Pigment Epithelium (RPE) Layer is known as Sub-Retinal Fluid (SRF). This distinct anatomical localization of SRF, differs it from normal cysts.