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Found 7 papers, 0 papers with code
Virtual Gram staining of label-free bacteria using darkfield microscopy and deep learning
Gram staining has been one of the most frequently used staining protocols in microbiology for over a century, utilized across various fields, including diagnostics, food safety, and environmental monitoring.
DUBLINE: A Deep Unfolding Network for B-line Detection in Lung Ultrasound Images
In the context of lung ultrasound, the detection of B-lines, which are indicative of interstitial lung disease and pulmonary edema, plays a pivotal role in clinical diagnosis.
Rapid and stain-free quantification of viral plaque via lens-free holography and deep learning
We also demonstrated that this data-driven plaque assay offers the capability of quantifying the infected area of the cell monolayer, performing automated counting and quantification of PFUs and virus-infected areas over a 10-fold larger dynamic range of virus concentration than standard viral plaque assays.
Deep Learning-enabled Detection and Classification of Bacterial Colonies using a Thin Film Transistor (TFT) Image Sensor
Due to the large scalability, ultra-large field-of-view, and low cost of the TFT-based image sensors, this platform can be integrated with each agar plate to be tested and disposed of after the automated CFU count.
Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer
We report a field-portable and cost-effective imaging flow cytometer that uses deep learning to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput of 100 mL/h.
Early-detection and classification of live bacteria using time-lapse coherent imaging and deep learning
Our experiments further confirmed that this method successfully detects 90% of bacterial colonies within 7-10 h (and >95% within 12 h) with a precision of 99. 2-100%, and correctly identifies their species in 7. 6-12 h with 80% accuracy.
Cultural Vocal Bursts Intensity Prediction
General Classification
Deep learning enhanced mobile-phone microscopy
Mobile-phones have facilitated the creation of field-portable, cost-effective imaging and sensing technologies that approach laboratory-grade instrument performance.
