Microscopy (Oxford, England)
Mar 31, 2025
Three-dimensional (3D) reconstruction is time-consuming owing to segmentation work. We evaluated the accuracy of the artificial intelligence (AI)-based segmentation and tracking model SAM-Track for segmentation of anatomical or histological structure...
Microscopy (Oxford, England)
Jun 8, 2023
Nuclei segmentation of cells is the preliminary and essential step of pathological image analysis. However, robust and accurate cell nuclei segmentation is challenging due to the enormous variability of staining, cell sizes, morphologies, cell adhesi...
Microscopy (Oxford, England)
Feb 8, 2023
Tumor-infiltrating lymphocytes are specialized lymphocytes that can detect and kill cancerous cells. Their detection poses many challenges due to significant morphological variations, overlapping occurrence, artifact regions and high-class resemblanc...
Microscopy (Oxford, England)
Feb 8, 2023
Dense connective tissue, including the ligament, tendon, fascia and cornea, is formed by regularly arranged collagen fibres synthesized by fibroblasts (Fbs). The mechanism by which fibre orientation is determined remains unclear. Periodontal ligament...
Microscopy (Oxford, England)
Aug 1, 2022
Quality control of special steel is accomplished through visual inspection of its microstructure based on microscopic images. This study proposes an 'automatic-quality-level-estimation system' based on machine learning. Visual inspection of this type...
Microscopy (Oxford, England)
Feb 18, 2022
We review the growing use of machine learning in electron microscopy (EM) driven in part by the availability of fast detectors operating at kiloHertz frame rates leading to large data sets that cannot be processed using manually implemented algorithm...
Microscopy (Oxford, England)
Jan 29, 2022
Accompanied with the clinical routine examination demand increase sharply, the efficiency and accuracy are the first priority. However, automatic classification and localization of cells in microscopic images in super depth of Field (SDoF) system rem...
Microscopy (Oxford, England)
Apr 8, 2020
Image processing is one of the most important applications of recent machine learning (ML) technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML architecture, have been developed for image processing applications. Howev...
Microscopy (Oxford, England)
Apr 8, 2020
In this review, we focus on the applications of machine learning methods for analyzing image data acquired in imaging flow cytometry technologies. We propose that the analysis approaches can be categorized into two groups based on the type of data, r...
Microscopy (Oxford, England)
Apr 8, 2020
Single-molecule imaging analysis has been applied to study the dynamics and kinetics of molecular behaviors and interactions in living cells. In spite of its high potential as a technique to investigate the molecular mechanisms of cellular phenomena,...