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Microscopy

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Artificial Intelligence in Point-of-Care Testing.

Annals of laboratory medicine
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.)
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
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
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
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
BACKGROUND: The study aimed to evaluate the effectiveness of learning blood cell morphology by learning on our Artificial intelligence (AI)-based online platform.

Tile-based microscopic image processing for malaria screening using a deep learning approach.

BMC medical imaging
BACKGROUND: Manual microscopic examination remains the golden standard for malaria diagnosis. But it is laborious, and pathologists with experience are needed for accurate diagnosis. The need for computer-aided diagnosis methods is driven by the enor...

Moving perfusion culture and live-cell imaging from lab to disc: proof of concept toxicity assay with AI-based image analysis.

Lab on a chip
, cell-based assays are essential in diagnostics and drug development. There are ongoing efforts to establish new technologies that enable real-time detection of cell-drug interaction during culture under flow conditions. Our compact (10 × 10 × 8.5 c...

Detection of malignancy in whole slide images of endometrial cancer biopsies using artificial intelligence.

PloS one
In this study we use artificial intelligence (AI) to categorise endometrial biopsy whole slide images (WSI) from digital pathology as either "malignant", "other or benign" or "insufficient". An endometrial biopsy is a key step in diagnosis of endomet...

Deep Learning Enhanced Electrochemiluminescence Microscopy.

Analytical chemistry
Limited by the efficiency of electrochemiluminescence, tens of seconds of exposure time are typically required to get a high-quality image. Image enhancement of short exposure time images to obtain a well-defined electrochemiluminescence image can me...