AIMC Topic: Microscopy, Confocal
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Artificial intelligence model for the assessment of unstained live sperm morphology.
Reproduction & fertility
Apr 1, 2025
ABSTRACT: Traditional sperm morphology assessment requires staining and high magnification (100×), rendering sperm unsuitable for further use. We aimed to determine whether an in-house artificial intelligence (AI) model could reliably assess normal s...
[Application of neural networks for improving the methods of assessment of corneal nerve fibers (preliminary report)].
Vestnik oftalmologii
Jan 1, 2025
UNLABELLED: Processing large datasets using artificial intelligence is a promising approach in disease diagnosis and monitoring that focuses on improving research algorithms for existing technologies. Interest in studying corneal nerve fibers (CNFs) ...
A framework of multi-view machine learning for biological spectral unmixing of fluorophores with overlapping excitation and emission spectra.
Briefings in bioinformatics
Nov 22, 2024
The accuracy of assigning fluorophore identity and abundance, known as spectral unmixing, in biological fluorescence microscopy images remains a significant challenge due to the substantial overlap in emission spectra among fluorophores. In tradition...
Improved Segmentation of Confocal Calcium Videos of Hela Cells Using Deep-Learning-Assisted Watershed Algorithm.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The potential of calcium imaging in high-throughput drug screening experiments remains underutilized, primarily because of time-intensive manual identification of cells.To overcome these challenges, we propose to use deep learning enhanced watershed ...
Machine learning model quantifies mast cells in biopsies of psoriatic lesions imaged with confocal microscopy.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
May 1, 2024
[MOCK MOLE: PRODUCING SYNTHETIC IMAGES THAT RECAPITULATE CONFOCAL PATTERNS OF MELANOCYTIC NEVI VIA DEEP-LEARNING MODELS].
Harefuah
Dec 1, 2023
INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized under Reflectance Confocal Microscopy (RCM).
Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma.
Journal of biomedical optics
Jun 1, 2022
SIGNIFICANCE: Raman spectroscopy (RS) provides an automated approach for assisting Mohs micrographic surgery for skin cancer diagnosis; however, the specificity of RS is limited by the high spectral similarity between tumors and normal tissues struct...
Segmentation and Evaluation of Corneal Nerves and Dendritic Cells From In Vivo Confocal Microscopy Images Using Deep Learning.
Translational vision science & technology
Jun 1, 2022
PURPOSE: Segmentation and evaluation of in vivo confocal microscopy (IVCM) images requires manual intervention, which is time consuming, laborious, and non-reproducible. The aim of this research was to develop and validate deep learning-based methods...
Machine learning algorithms to control concentrations of carbon nanocomplexes in a biological medium via optical absorption spectroscopy: how to choose and what to expect?
Applied optics
Sep 20, 2021
A solution of spectroscopic inverse problems, implying determination of target parameters of the research object via analysis of spectra of various origins, is an overly complex task, especially in case of strong variability of the research object. O...
Generative Adversarial Network Based Automatic Segmentation of Corneal Subbasal Nerves on In Vivo Confocal Microscopy Images.
Translational vision science & technology
May 3, 2021
PURPOSE: In vivo confocal microscopy (IVCM) is a noninvasive, reproducible, and inexpensive diagnostic tool for corneal diseases. However, widespread and effortless image acquisition in IVCM creates serious image analysis workloads on ophthalmologist...
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