Publications by authors named "Ibrahim Abd El-Sadek"

The germination process of radish sprouts was investigated in detail using volumetric dynamic optical coherence tomography (OCT). Dynamic OCT involves the sequential acquisition of 16 OCT images and subsequent temporal variance analysis of each pixel, enabling non-invasive visualization of the cellular and tissue activities of plants. The radish sprouts were longitudinally investigated for up to 12 days, and changes in morphology and dynamic OCT image patterns were observed as the plants developed.

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We demonstrate deep-learning neural network (NN)-based dynamic optical coherence tomography (DOCT), which generates high-quality logarithmic-intensity-variance (LIV) DOCT images from only four OCT frames. The NN model is trained for tumor spheroid samples using a customized loss function: the weighted mean absolute error. This loss function enables highly accurate LIV image generation.

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  • A new deep-learning scatterer density estimator (SDE) was developed to analyze speckle patterns in optical coherence tomography (OCT) images and accurately estimate the density of scatterers.
  • This SDE was trained on a large dataset of simulated OCT images that included a sophisticated noise model, accounting for shot noise, relative-intensity noise, and non-optical noise.
  • Evaluations using scattering phantoms and tumor spheroids showed that the SDE significantly improved estimation accuracy compared to previous versions that used less effective noise models.
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  • The text mentions a correction to an article found on page 168 of volume 13.
  • The article is identified by its PubMed ID (PMID) 35154862.
  • This correction likely addresses errors or updates that need to be noted for accuracy in the original publication.
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We demonstrate label-free dynamic optical coherence tomography (D-OCT)-based visualization and quantitative assessment of patterns of tumor spheroid response to three anti-cancer drugs. The study involved treating human breast adenocarcinoma (MCF-7 cell-line) with paclitaxel (PTX), tamoxifen citrate (TAM), and doxorubicin (DOX) at concentrations of 0 (control), 0.1, 1, and 10 µM for 1, 3, and 6 days.

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This study aims at demonstrating label-free drug-response-patterns assessment of different tumor spheroids and drug types by dynamic optical coherence tomography (D-OCT). The study involved human breast cancer (MCF-7) and colon cancer (HT-29) spheroids. The MCF-7 and HT-29 spheroids were treated with paclitaxel (Taxol; PTX) and the active metabolite of irinotecan SN-38, respectively.

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Renal tubule has distinct metabolic features and functional activity that may be altered during kidney disease. In this paper, we present label-free functional activity imaging of renal tubule in normal and obstructed mouse kidney models using three-dimensional (3D) dynamic optical coherence tomography (OCT) ex vivo. To create an obstructed kidney model, we ligated the ureter of the left kidney for either 7 or 14 days.

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A new formulation of the lateral imaging process of point-scanning optical coherence tomography (OCT) and a new differential contrast method designed by using this formulation are presented. The formulation is based on a mathematical sample model called the dispersed scatterer model (DSM), in which the sample is represented as a material with a spatially slowly varying refractive index and randomly distributed scatterers embedded in the material. It is shown that the formulation represents a meaningful OCT image and speckle as two independent mathematical quantities.

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An organoid is a three-dimensional (3D) cell culture emulating human organs. We applied 3D dynamic optical coherence tomography (DOCT) to visualize the intratissue and intracellular activities of human induced pluripotent stem cells (hiPSCs)-derived alveolar organoids in normal and fibrosis models. 3D DOCT data were acquired with an 840-nm spectral domain optical coherence tomography with axial and lateral resolutions of 3.

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Label-free metabolic imaging of non-alcoholic fatty liver disease (NAFLD) mouse liver is demonstrated by dynamic optical coherence tomography (OCT). The NAFLD mouse is a methionine choline-deficient (MCD)-diet model, and two mice fed the MCD diet for 1 and 2 weeks are involved in addition to a normal-diet mouse. The dynamic OCT is based on repeating raster scan and logarithmic intensity variance (LIV) analysis that enables volumetric metabolic imaging with a standard-speed (50,000 A-lines/s) OCT system.

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  • The study explores the use of zebrafish as a model for pre-clinical cancer research, employing advanced imaging technologies like Jones matrix optical coherence tomography (JM-OCT) and intensity-based spectral-domain OCT.
  • Researchers characterized various anatomical features of the zebrafish based on scattering and polarization to identify abnormalities related to tumors, particularly in the brain and eye regions.
  • The findings indicate a significant reduction in birefringence in tumor areas, demonstrating the effectiveness of OCT and JM-OCT for non-invasive, high-resolution imaging in cancer research.
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  • Researchers developed a deep convolutional neural network (DCNN) to estimate key parameters such as tissue scatterer density, resolution, signal-to-noise ratio, and effective number of scatterers from optical coherence tomography (OCT) images.
  • The DCNN was trained on a massive dataset of 1,280,000 digitally generated image patches and was validated both numerically and experimentally, showing high accuracy in its estimations.
  • Experimental results indicated that the model could effectively measure scatterer density in scattering phantoms and even demonstrated its application in monitoring changes in a tumor cell spheroid during cell necrosis.
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  • * Researchers aimed to visualize and analyze the scattering and polarization features of the zebrafish's organs, including eyes, gills, and muscles, to understand developmental changes.
  • * The findings demonstrated that JM-OCT effectively captured detailed images of zebrafish organs and their blood vessels without using labels, providing a promising tool for studying zebrafish biology in real-time.
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We present a completely label-free three-dimensional (3D) optical coherence tomography (OCT)-based tissue dynamics imaging method for visualization and quantification of the metabolic and necrotic activities of tumor spheroid. Our method is based on a custom 3D scanning protocol that is designed to capture volumetric tissue dynamics tomography images only in a few tens of seconds. The method was applied to the evaluation of a tumor spheroid.

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We demonstrate label-free imaging of the functional and structural properties of microvascular complex in mice liver. The imaging was performed by a custom-built Jones-matrix based polarization sensitive optical coherence tomography (JM-OCT), which is capable of measuring tissue's attenuation coefficient, birefringence, and tiny tissue dynamics. Two longitudinal studies comprising a healthy liver and an early fibrotic liver model were performed.

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We present optical coherence tomography (OCT)-based tissue dynamics imaging method to visualize and quantify tissue dynamics such as subcellular motion based on statistical analysis of rapid-time-sequence OCT signals at the same location. The analyses include logarithmic intensity variance (LIV) method and two types of OCT correlation decay speed analysis (OCDS). LIV is sensitive to the magnitude of the signal fluctuations, while OCDSs including early- and late-OCDS (OCDS and OCDS , respectively) are sensitive to the fast and slow tissue dynamics, respectively.

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