Related papers: Deep learning-enabled image quality control in tom…
Deep learning has demonstrated superb efficacy in processing imaging data, yet its suitability in solving challenging inverse problems in scientific imaging has not been fully explored. Of immense interest is the determination of local…
We present a tomographic imaging technique, termed Deep Prior Diffraction Tomography (DP-DT), to reconstruct the 3D refractive index (RI) of thick biological samples at high resolution from a sequence of low-resolution images collected…
We present a novel illumination control technique for optical diffraction tomography (ODT). Various spatial frequencies of beam illumination were controlled by displaying time-averaged sinusoidal patterns using a digital micromirror device…
We propose and demonstrate a holographic imaging scheme exploiting random illuminations for recording hologram and then applying numerical reconstruction and twin removal. We use an in-line holographic geometry to record the hologram in…
Optical diffraction tomography (ODT) has emerged as a powerful label-free three-dimensional (3D) bioimaging techniques for observing living cells and thin tissue layers. We report a new reflection-mode ODT (rODT) method for imaging thick…
Reconstruction of in-line holograms of unknown objects in general suffers from twin-image artifacts due to the appearance of an out-of-focus image overlapping with the desired image to be reconstructed. Computer-based iterative phase…
The ever-growing deep learning technologies are making revolutionary changes for modern life. However, conventional computing architectures are designed to process sequential and digital programs, being extremely burdened with performing…
Computer vision tasks require processing large amounts of data to perform image classification, segmentation, and feature extraction. Optical preprocessors can potentially reduce the number of floating point operations required by computer…
Optical diffraction tomography (ODT) is a powerful non-invasive 3D imaging technique, but its combination with broadband light sources is difficult. In this study, we introduce ultrabroadband ODT, covering over 150 nm of visible spectral…
Optical coherence tomography angiography (OCTA) is a non-invasive imaging technique widely used to study vascular structures and micro-circulation dynamics in the retina and choroid. OCTA has been widely used in clinics for diagnosing…
While machine learning approaches to image restoration offer great promise, current methods risk training models fixated on performing well only for image corruption of a particular level of difficulty---such as a certain level of noise or…
Off-axis digital holographic microscopy is a high-throughput, label-free imaging technology that provides three-dimensional, high-resolution information about samples, particularly useful in large-scale cellular imaging. However, the…
Objective: The advent of Electronic Medical Records (EMR) with large electronic imaging databases along with advances in deep neural networks with machine learning has provided a unique opportunity to achieve milestones in automated image…
This study proposes a novel approach utilizing a physics-informed deep learning (DL) algorithm to reconstruct occluded objects in a terahertz (THz) holographic system. Taking the angular spectrum theory as prior knowledge, we generate a…
Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image-guided radiation therapy, implant dentistry or…
Super-resolution reconstruction techniques entail the utilization of software algorithms to transform one or more sets of low-resolution images captured from the same scene into high-resolution images. In recent years, considerable…
Color image steganography based on deep learning is the art of hiding information in the color image. Among them, image hiding steganography(hiding image with image) has attracted much attention in recent years because of its great…
Deep learning is now the gold standard in computer vision-based quality inspection systems. In order to detect defects, supervised learning is often utilized, but necessitates a large amount of annotated images, which can be costly:…
Optical diffraction tomography (ODT), initially described in the seminal paper of Emil Wolf [Opt. Comm., 1(4), 153-156 (1969)], has received renewed attention recently. The vast majority of ODT experiments reported to date have been 3D…
Optical diffraction tomography (ODT) is a tomographic technique that can be used to measure the three-dimensional (3D) refractive index distribution within living cells without the requirement of any marker. In principle, ODT can be…