AIMC Topic: Microscopy

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Fine-tuning TrailMap: The utility of transfer learning to improve the performance of deep learning in axon segmentation of light-sheet microscopy images.

PloS one Mar 29, 2024
Light-sheet microscopy has made possible the 3D imaging of both fixed and live biological tissue, with samples as large as the entire mouse brain. However, segmentation and quantification of that data remains a time-consuming manual undertaking. Mach...
Deep Learning Brain Microscopy Machine Learning Mice Axons Animals
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The multimodality cell segmentation challenge: toward universal solutions.

Nature methods Mar 26, 2024
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different exp...
Microscopy Image Processing, Computer-Assisted Algorithms Animals Deep Learning Single-Cell Analysis Humans
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DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus.

Journal of imaging informatics in medicine Mar 25, 2024
Depth of focus (DOF) is defined as the axial range in which the specimen stage moves without losing focus while the imaging apparatus remains stable. It may not be possible to capture an image that includes the entire specimen in focus due to the nar...
Algorithms Deep Learning Image Processing, Computer-Assisted Microscopy Humans
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Dual-channel neural network for instance segmentation of synapse.

Computers in biology and medicine Mar 13, 2024
Detection and segmentation of neural synapses in electron microscopy images are the committed steps for analyzing neural ultrastructure. To date, manual annotation of the structure in synapses has been the primary method, which is time-consuming and ...
Microscopy Synapses Neural Networks, Computer Image Processing, Computer-Assisted Automation
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Features in Backgrounds of Microscopy Images Introduce Biases in Machine Learning Analyses.

Journal of pharmaceutical sciences Mar 12, 2024
Subvisible particles may be encountered throughout the processing of therapeutic protein formulations. Flow imaging microscopy (FIM) and backgrounded membrane imaging (BMI) are techniques commonly used to record digital images of these particles, whi...
Machine Learning Algorithms Neural Networks, Computer Bias Microscopy
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Enhancing parasitic organism detection in microscopy images through deep learning and fine-tuned optimizer.

Scientific reports Mar 8, 2024
Parasitic organisms pose a major global health threat, mainly in regions that lack advanced medical facilities. Early and accurate detection of parasitic organisms is vital to saving lives. Deep learning models have uplifted the medical sector by pro...
Babesia Deep Learning Toxoplasma Animals Microscopy Parasites
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Automatic classification of acute lymphoblastic leukemia cells and lymphocyte subtypes based on a novel convolutional neural network.

Microscopy research and technique Mar 6, 2024
Acute lymphoblastic leukemia (ALL) is a life-threatening disease that commonly affects children and is classified into three subtypes: L1, L2, and L3. Traditionally, ALL is diagnosed through morphological analysis, involving the examination of blood ...
Neural Networks, Computer Algorithms Humans Microscopy Image Processing, Computer-Assisted Precursor Cell Lymphoblastic Leukemia-Lymphoma Lymphocytes
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Recent advances in label-free imaging and quantification techniques for the study of lipid droplets in cells.

Current opinion in cell biology Feb 29, 2024
Lipid droplets (LDs), once considered mere storage depots for lipids, have gained recognition for their intricate roles in cellular processes, including metabolism, membrane trafficking, and disease states like obesity and cancer. This review explore...
Microscopy Lipid Droplets Artificial Intelligence Lipid Metabolism
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A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.

Scientific data Feb 23, 2024
High-content image-based screening is widely used in Drug Discovery and Systems Biology. However, sample preparation artefacts may significantly deteriorate the quality of image-based screening assays. While detection and circumvention of such artefa...
Artifacts Microscopy Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Algorithms
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Validation of artificial intelligence-based digital microscopy for automated detection of Schistosoma haematobium eggs in urine in Gabon.

PLoS neglected tropical diseases Feb 23, 2024
INTRODUCTION: Schistosomiasis is a significant public health concern, especially in Sub-Saharan Africa. Conventional microscopy is the standard diagnostic method in resource-limited settings, but with limitations, such as the need for expert microsco...
Artificial Intelligence Retrospective Studies Sensitivity and Specificity Microscopy Humans Gabon Schistosoma haematobium Schistosomiasis haematobia
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