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Microscopy

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Current Landscape of Advanced Imaging Tools for Pathology Diagnostics.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Histopathology relies on century-old workflows of formalin fixation, paraffin embedding, sectioning, and staining tissue specimens on glass slides. Despite being robust, this conventional process is slow, labor-intensive, and limited to providing two...

Protocol to train a support vector machine for the automatic curation of bacterial cell detections in microscopy images.

STAR protocols
Manual curation of bacterial cell detections in microscopy images remains a time-consuming and laborious task. This work offers a comprehensive, step-by-step tutorial on training a support vector machine to autonomously distinguish between good and b...

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network.

IEEE transactions on medical imaging
Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein,...

A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.

Scientific data
Urinary tract infection (UTI) is a common disorder. Its diagnosis can be made by microscopic examination of voided urine for markers of infection. This manual technique is technically difficult, time-consuming and prone to inter-observer errors. The ...

Dual contrastive learning based image-to-image translation of unstained skin tissue into virtually stained H&E images.

Scientific reports
Staining is a crucial step in histopathology that prepares tissue sections for microscopic examination. Hematoxylin and eosin (H&E) staining, also known as basic or routine staining, is used in 80% of histopathology slides worldwide. To enhance the h...

Content-aware frame interpolation (CAFI): deep learning-based temporal super-resolution for fast bioimaging.

Nature methods
The development of high-resolution microscopes has made it possible to investigate cellular processes in 3D and over time. However, observing fast cellular dynamics remains challenging because of photobleaching and phototoxicity. Here we report the i...

Smart lattice light-sheet microscopy for imaging rare and complex cellular events.

Nature methods
Light-sheet microscopes enable rapid high-resolution imaging of biological specimens; however, biological processes span spatiotemporal scales. Moreover, long-term phenotypes are often instigated by rare or fleeting biological events that are difficu...

Microscopic urinary particle detection by different YOLOv5 models with evolutionary genetic algorithm based hyperparameter optimization.

Computers in biology and medicine
The diagnosis of kidney disease often involves analysing urine sediment particles. Traditionally, urinalysis was performed manually by collecting urine samples and using a centrifuge, which was prone to manual errors and relied on labour-intensive pr...

Deep learning for fast super-resolution ultrasound microvessel imaging.

Physics in medicine and biology
. Ultrasound localization microscopy (ULM) enables microvascular reconstruction by localizing microbubbles (MBs). Although ULM can obtain microvascular images that are beyond the ultimate resolution of the ultrasound (US) diffraction limit, it requir...

Accurate staging of chick embryonic tissues via deep learning of salient features.

Development (Cambridge, England)
Recent work shows that the developmental potential of progenitor cells in the HH10 chick brain changes rapidly, accompanied by subtle changes in morphology. This demands increased temporal resolution for studies of the brain at this stage, necessitat...