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Microscopy

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A deep learning approach to the screening of malaria infection: Automated and rapid cell counting, object detection and instance segmentation using Mask R-CNN.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate and early diagnosis is critical to proper malaria treatment and hence death prevention. Several computer vision technologies have emerged in recent years as alternatives to traditional microscopy and rapid diagnostic tests. In this work, we ...

Quantitative analysis of blood cells from microscopic images using convolutional neural network.

Medical & biological engineering & computing
Blood cell count provides relevant clinical information about different kinds of disorders. Any deviation in the number of blood cells implies the presence of infection, inflammation, edema, bleeding, and other blood-related issues. Current microscop...

Developing a Qualification and Verification Strategy for Digital Tissue Image Analysis in Toxicological Pathology.

Toxicologic pathology
Digital tissue image analysis is a computational method for analyzing whole-slide images and extracting large, complex, and quantitative data sets. However, as with any analysis method, the quality of generated results is dependent on a well-designed...

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy.

PloS one
The accurate segmentation and tracking of cells in microscopy image sequences is an important task in biomedical research, e.g., for studying the development of tissues, organs or entire organisms. However, the segmentation of touching cells in image...

An end-to-end breast tumour classification model using context-based patch modelling - A BiLSTM approach for image classification.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Researchers working on computational analysis of Whole Slide Images (WSIs) in histopathology have primarily resorted to patch-based modelling due to large resolution of each WSI. The large resolution makes WSIs infeasible to be fed directly into the ...

Super resolution microscopy and deep learning identify Zika virus reorganization of the endoplasmic reticulum.

Scientific reports
The endoplasmic reticulum (ER) is a complex subcellular organelle composed of diverse structures such as tubules, sheets and tubular matrices. Flaviviruses such as Zika virus (ZIKV) induce reorganization of ER membranes to facilitate viral replicatio...

A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

Nature communications
Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic diagnosis requires labor-intensive reading of a large number of tissue slides with high diagnostic accuracy equal or close to 100 percent to guide trea...

Detecting cells in intravital video microscopy using a deep convolutional neural network.

Computers in biology and medicine
The analysis of leukocyte recruitment in intravital video microscopy (IVM) is essential to the understanding of inflammatory processes. However, because IVM images often present a large variety of visual characteristics, it is hard for an expert huma...