AIMC Topic: Microscopy

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A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning.

Journal of healthcare engineering
Vaginitis is a gynecological disease affecting the health of millions of women all over the world. The traditional diagnosis of vaginitis is based on manual microscopy, which is time-consuming and tedious. The deep learning method offers a fast and r...

Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning.

The Science of the total environment
Microplastics quantification and classification are demanding jobs to monitor microplastic pollution and evaluate the potential health risks. In this paper, microplastics from daily supplies in diverse chemical compositions and shapes are imaged by s...

Robotic and Microrobotic Tools for Dental Therapy.

Journal of healthcare engineering
Robotic and microrobotic tools such as dental operating microscopes and dental endoscopes are being used extensively in dental therapy, which have a significant impact on dental therapy and education. Herein, this paper reviews the state of the art o...

Automatic Colorectal Cancer Screening Using Deep Learning in Spatial Light Interference Microscopy Data.

Cells
The surgical pathology workflow currently adopted by clinics uses staining to reveal tissue architecture within thin sections. A trained pathologist then conducts a visual examination of these slices and, since the investigation is based on an empiri...

Speeding up reconstruction of 3D tomograms in holographic flow cytometry deep learning.

Lab on a chip
Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us ...

Examination of blood samples using deep learning and mobile microscopy.

BMC bioinformatics
BACKGROUND: Microscopic examination of human blood samples is an excellent opportunity to assess general health status and diagnose diseases. Conventional blood tests are performed in medical laboratories by specialized professionals and are time and...

Deep Multi-Feature Transfer Network for Fourier Ptychographic Microscopy Imaging Reconstruction.

Sensors (Basel, Switzerland)
Fourier ptychographic microscopy (FPM) is a potential imaging technique, which is used to achieve wide field-of-view (FOV), high-resolution and quantitative phase information. The LED array is used to irradiate the samples from different angles to ob...

Artificial intelligence and deep learning to map immune cell types in inflamed human tissue.

Journal of immunological methods
Biopsies of inflammatory tissue contain a complex network of interacting cells, orchestrating the immune or autoimmune response. While standard histological examination can identify relationships, it is clear that a great amount of data on each slide...

Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms.

Scientific reports
The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabli...

Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.

Pharmaceutical research
OBJECTIVE: Digital microscopy is used to monitor particulates such as protein aggregates within biopharmaceutical products. The images that result encode a wealth of information that is underutilized in pharmaceutical process monitoring. For example,...