AIMC Topic: Microscopy

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Segmentation of corneal endothelium images using a U-Net-based convolutional neural network.

Artificial intelligence in medicine
Diagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracte...

Deep learning massively accelerates super-resolution localization microscopy.

Nature biotechnology
The speed of super-resolution microscopy methods based on single-molecule localization, for example, PALM and STORM, is limited by the need to record many thousands of frames with a small number of observed molecules in each. Here, we present ANNA-PA...

Assessing microscope image focus quality with deep learning.

BMC bioinformatics
BACKGROUND: Large image datasets acquired on automated microscopes typically have some fraction of low quality, out-of-focus images, despite the use of hardware autofocus systems. Identification of these images using automated image analysis with hig...

Computational Sensing of Staphylococcus aureus on Contact Lenses Using 3D Imaging of Curved Surfaces and Machine Learning.

ACS nano
We present a cost-effective and portable platform based on contact lenses for noninvasively detecting Staphylococcus aureus, which is part of the human ocular microbiome and resides on the cornea and conjunctiva. Using S. aureus-specific antibodies a...

AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks.

Scientific reports
Segmentation of axon and myelin from microscopy images of the nervous system provides useful quantitative information about the tissue microstructure, such as axon density and myelin thickness. This could be used for instance to document cell morphom...

Automated Interpretation of Blood Culture Gram Stains by Use of a Deep Convolutional Neural Network.

Journal of clinical microbiology
Microscopic interpretation of stained smears is one of the most operator-dependent and time-intensive activities in the clinical microbiology laboratory. Here, we investigated application of an automated image acquisition and convolutional neural net...

Computer Aided Solution for Automatic Segmenting and Measurements of Blood Leucocytes Using Static Microscope Images.

Journal of medical systems
Blood leucocytes segmentation in medical images is viewed as difficult process due to the variability of blood cells concerning their shape and size and the difficulty towards determining location of Blood Leucocytes. Physical analysis of blood tests...

SetSVM: An Approach to Set Classification in Nuclei-Based Cancer Detection.

IEEE journal of biomedical and health informatics
Due to the importance of nuclear structure in cancer diagnosis, several predictive models have been described for diagnosing a wide variety of cancers based on nuclear morphology. In many computer-aided diagnosis (CAD) systems, cancer detection tasks...

Leukocyte Image Segmentation Using Novel Saliency Detection Based on Positive Feedback of Visual Perception.

Journal of healthcare engineering
This paper presents a novel method for salient object detection in nature image by simulating microsaccades in fixational eye movements. Due to a nucleated cell usually stained that is salient obviously, the proposed method is suitable to segment nuc...