AIMC Topic: Microscopy
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DeepSea is an efficient deep-learning model for single-cell segmentation and tracking in time-lapse microscopy.
Cell reports methods
Jun 12, 2023
Time-lapse microscopy is the only method that can directly capture the dynamics and heterogeneity of fundamental cellular processes at the single-cell level with high temporal resolution. Successful application of single-cell time-lapse microscopy re...
Triplet-Net Classification of Contiguous Stem Cell Microscopy Images.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 5, 2023
Cellular microscopy imaging is a common form of data acquisition for biological experimentation. Observation of gray-level morphological features allows for the inference of useful biological information such as cellular health and growth status. Cel...
PPSW-SHAP: Towards Interpretable Cell Classification Using Tree-Based SHAP Image Decomposition and Restoration for High-Throughput Bright-Field Imaging.
Cells
May 13, 2023
Advancements in high-throughput microscopy imaging have transformed cell analytics, enabling functionally relevant, rapid, and in-depth bioanalytics with Artificial Intelligence (AI) as a powerful driving force in cell therapy (CT) manufacturing. Hig...
A Compound Loss Function With Shape Aware Weight Map for Microscopy Cell Segmentation.
IEEE transactions on medical imaging
May 2, 2023
Microscopy cell segmentation is a crucial step in biological image analysis and a challenging task. In recent years, deep learning has been widely used to tackle this task, with promising results. A critical aspect of training complex neural networks...
Artificial Intelligence in Point-of-Care Testing.
Annals of laboratory medicine
Apr 21, 2023
With the projected increase in the global population, current healthcare delivery models will face severe challenges. Rural and remote areas, whether in developed or developing countries, are characterized by the same challenges: the unavailability o...
Digital Histopathology by Infrared Spectroscopic Imaging.
Annual review of analytical chemistry (Palo Alto, Calif.)
Apr 17, 2023
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy w...
Comparison of deep learning models for digital H&E staining from unpaired label-free multispectral microscopy images.
Computer methods and programs in biomedicine
Apr 5, 2023
BACKGROUND AND OBJECTIVE: This paper presents the quantitative comparison of three generative models of digital staining, also known as virtual staining, in H&E modality (i.e., Hematoxylin and Eosin) that are applied to 5 types of breast tissue. More...
Multilayer outperforms single-layer slide scanning in AI-based classification of whole slide images with low-burden acid-fast mycobacteria (AFB).
Computer methods and programs in biomedicine
Mar 28, 2023
Manual screening of Ziehl-Neelsen (ZN)-stained slides that are negative or contain rare acid-fast mycobacteria (AFB) is labor-intensive and requires repetitive refocusing to visualize AFB candidates under the microscope. Whole slide image (WSI) scann...
CenFind: a deep-learning pipeline for efficient centriole detection in microscopy datasets.
BMC bioinformatics
Mar 28, 2023
BACKGROUND: High-throughput and selective detection of organelles in immunofluorescence images is an important but demanding task in cell biology. The centriole organelle is critical for fundamental cellular processes, and its accurate detection is k...
Artificial Intelligence-based online platform assists blood cell morphology learning: A mixed-methods sequential explanatory designed research.
Medical teacher
Mar 27, 2023
BACKGROUND: The study aimed to evaluate the effectiveness of learning blood cell morphology by learning on our Artificial intelligence (AI)-based online platform.
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