Introduction: The recently introduced Compressed Sensing (CS) theory illustrates that a small number of random linear measurements can be sufficient to reconstruct sparse or compressible signals [1,2,3]. Since the number of measurements necessary for perfect reconstruction using the CS theory can be drastically smaller than the number of measurements required by the Nyquist sampling theory, CS ...

Volumetric imaging of the Optic Nerve Head (ONH) morphometry with Optical Coherence Tomography (OCT) requires dense sampling and relatively long acquisition times. Compressive Sampling (CS) is an emerging technique to reduce volume acquisition time with minimal image degradation by sparsely sampling the object and reconstructing the missing data in software. In this report, we demonstrated real...

Compressive sensing (CS) theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling, higher quality image reconstructions are often achievable. Considering that the structure of sampling protocols has such a profound impact on the quality of image reconstructions, we formulate a new sampling scheme motivated by physiological receptive field structure, loc...

In medical imaging, the application of retinal images demands a lot photos to analyze and requires efficient compression techniques for image storage. Retinal must meet stringent quality requirements clinical data be accurate dependable. This paper proposes compressive sampling (CS) framework color (CRI) compression, which relies on spread spectrum Fourier (SSFS) total variant (TV)-based recons...

Background & aim: Cesarean section (CS) rates have been increasing steadily, worldwide. The knowledge and attitude of health professionals towards natural childbirth and CS are important factors in selecting a mode of delivery. The purpose of this study was to determine the knowledge and attitude of midwifery and nursing students towards different modes of delivery. Methods:In this descriptive,...

The main challenge in the implementation of long-lasting vibration monitoring systems is to tackle constantly evolving complexity modern “mesoscale” structures. Thus, design energy-aware solutions promoted for joint optimization data sampling rates, onboard storage requirements, and communication payloads. In this context, present work explores feasibility rakeness-based compressed sensing (Rak...

Abstract We study the properties of interacting line defects in four-dimensional Chern Simons (CS) gauge theory with invariance given by S mathvariant="normal">L <mml:mro...