AIMC Topic: Microscopy
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Label-free sensor for automatic identification of erythrocytes using digital in-line holographic microscopy and machine learning.
Biosensors & bioelectronics
Dec 15, 2017
Cell types of erythrocytes should be identified because they are closely related to their functionality and viability. Conventional methods for classifying erythrocytes are time consuming and labor intensive. Therefore, an automatic and accurate eryt...
Egg Excretion does not Increase after Exercise: Implications for Diagnostic Testing.
The American journal of tropical medicine and hygiene
Dec 14, 2017
Children are frequently invited to exercise before micturition, as it is believed that this activity will result in higher egg excretion, and hence, increases sensitivity of microscopic diagnoses. However, the evidence of this recommendation is scan...
Construction of a system using a deep learning algorithm to count cell numbers in nanoliter wells for viable single-cell experiments.
Scientific reports
Dec 4, 2017
For single-cell experiments, it is important to accurately count the number of viable cells in a nanoliter well. We used a deep learning-based convolutional neural network (CNN) on a large amount of digital data obtained as microscopic images. The tr...
Deep Learning in Microscopy Image Analysis: A Survey.
IEEE transactions on neural networks and learning systems
Nov 22, 2017
Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerging as a l...
A deep convolutional neural network for classification of red blood cells in sickle cell anemia.
PLoS computational biology
Oct 19, 2017
Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological...
A dictionary learning approach for human sperm heads classification.
Computers in biology and medicine
Oct 10, 2017
BACKGROUND AND OBJECTIVE: To diagnose infertility in men, semen analysis is conducted in which sperm morphology is one of the factors that are evaluated. Since manual assessment of sperm morphology is time-consuming and subjective, automatic classifi...
Automatic Classification of Cancerous Tissue in Laserendomicroscopy Images of the Oral Cavity using Deep Learning.
Scientific reports
Sep 20, 2017
Oral Squamous Cell Carcinoma (OSCC) is a common type of cancer of the oral epithelium. Despite their high impact on mortality, sufficient screening methods for early diagnosis of OSCC often lack accuracy and thus OSCCs are mostly diagnosed at a late ...
Identification and segmentation of myelinated nerve fibers in a cross-sectional optical microscopic image using a deep learning model.
Journal of neuroscience methods
Aug 31, 2017
BACKGROUND: The morphometric analysis of myelinated nerve fibers of peripheral nerves in cross-sectional optical microscopic images is valuable. Several automated methods for nerve fiber identification and segmentation have been reported. This paper ...
A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.
Scientific reports
Aug 9, 2017
Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method ...
Holographic deep learning for rapid optical screening of anthrax spores.
Science advances
Aug 4, 2017
Establishing early warning systems for anthrax attacks is crucial in biodefense. Despite numerous studies for decades, the limited sensitivity of conventional biochemical methods essentially requires preprocessing steps and thus has limitations to be...
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