AI Medical Compendium Topic

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Microscopy, Confocal

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CAM/TMA-DPH as a promising alternative to SYTO9/PI for cell viability assessment in bacterial biofilms.

Frontiers in cellular and infection microbiology
INTRODUCTION: Accurately assessing biofilm viability is essential for evaluating both biofilm formation and the efficacy of antibacterial treatments. Traditional SYTO9 and propidium iodide (PI) live/dead staining in biofilm viability assays often ace...

Artificial intelligence model for the assessment of unstained live sperm morphology.

Reproduction & fertility
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...

Domain-specific AI segmentation of IMPDH2 rod/ring structures in mouse embryonic stem cells.

BMC biology
BACKGROUND: Inosine monophosphate dehydrogenase 2 (IMPDH2) is an enzyme that catalyses the rate-limiting step of guanine nucleotides. In mouse embryonic stem cells (ESCs), IMPDH2 forms large multi-protein complexes known as rod-ring (RR) structures t...

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
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 ...

[Application of neural networks for improving the methods of assessment of corneal nerve fibers (preliminary report)].

Vestnik oftalmologii
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) ...

Artificial intelligence-enabled lipid droplets quantification: Comparative analysis of NIS-elements Segment.ai and ZeroCostDL4Mic StarDist networks.

Methods (San Diego, Calif.)
Lipid droplets (LDs) are dynamic organelles that are present in almost all cell types, with a particularly high prevalence in adipocytes. The phenotype of LDs in these cells reflects their maturity, metabolic activity and function. Although LDs quant...

Protocol for AI-based segmentation and quantification of interstitial cells of Cajal in murine gastric muscle.

STAR protocols
Interstitial cells of Cajal (ICCs), pacemaker and neuromodulator cells in the gastrointestinal (GI) tract, play an important role in GI motility. However, quantifying ICCs is challenging due to their mixed morphologies. Here, we present a protocol fo...

A lightweight PCT-Net for segmenting neural fibers in low-quality CCM images.

Computers in biology and medicine
In this paper, we propose a lightweight Position Channel Transformer Network (PCT-Net) for segmenting slender neural fibers in low-quality corneal confocal microscopy images with speckle noise and uneven lighting. Three modules including the channel ...

Artificial intelligence to enhance the diagnosis of ocular surface squamous neoplasia.

Scientific reports
To provide an artificial intelligence (AI) method using in vivo confocal microscopy (IVCM) to differentiate ocular surface squamous neoplasia (OSSN) from other lesions and compare the performance of well-known AI-related solutions. A dataset of 2,774...

Artificial intelligence-aided optical biopsy improves the diagnosis of esophageal squamous neoplasm.

World journal of gastroenterology
BACKGROUND: Early detection of esophageal squamous neoplasms (ESN) is essential for improving patient prognosis. Optical diagnosis of ESN remains challenging. Probe-based confocal laser endomicroscopy (pCLE) enables accurate histological observation...