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Geometric Ultrasound Localization Microscopy
Contrast-Enhanced Ultra-Sound (CEUS) has become a viable method for non-invasive, dynamic visualization in medical diagnostics, yet Ultrasound... -
Automated Segmentation of Patterned Cells in Micropatterning Microscopy Images
Micropatterning in living cells is used for the analysis of protein-protein interactions. The quantitative analysis of images produced within this... -
Deep localization of subcellular protein structures from fluorescence microscopy images
Accurate localization of proteins from fluorescence microscopy images is challenging due to the inter-class similarities and intra-class disparities...
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VMAC: overlap** cervical cell segmentation from label-free quantitative microscopy images
Cervical cancer is one of the most common cancers in women. Non-invasive cytopathological methods are becoming increasingly important in the routine...
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Inverse Problems of Single Molecule Localization Microscopy
Single molecule localization microscopy is a recently developed superresolution imaging technique to visualize structural properties of single cells.... -
Colocalization for super-resolution microscopy via optimal transport
Super-resolution fluorescence microscopy is a widely used technique in cell biology. Stimulated emission depletion (STED) microscopy enables the...
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Fiber laser technologies for photoacoustic microscopy
Fiber laser technology has experienced a rapid growth over the past decade owing to increased applications in precision measurement and optical...
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High-speed high-resolution laser diode-based photoacoustic microscopy for in vivo microvasculature imaging
Laser diodes (LDs) have been considered as cost-effective and compact excitation sources to overcome the requirement of costly and bulky pulsed laser...
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Towards Automatic Embryo Staging in 3D+t Microscopy Images Using Convolutional Neural Networks and PointNets
Automatic analyses and comparisons of different stages of embryonic development largely depend on a highly accurate spatiotemporal alignment of the... -
Forecasting Model for the Annual Growth of Cryogenic Electron Microscopy Data
In this paper, we develop a forecasting model for the growth of Cryogenic Electron Microscopy (Cryo-EM) experimental data time series using... -
Resolution-Improvement of Confocal Fluorescence Microscopy via Two Different Point Spread Functions
In this paper, we propose a new method to obtain the improvement of lateral axial resolution of confocal fluorescence microscopy. In this method, we... -
A global sensitivity analysis of a mechanistic model of neoadjuvant chemotherapy for triple negative breast cancer constrained by in vitro and in vivo imaging data
Neoadjuvant chemotherapy (NAC) is a standard-of-care treatment for locally advanced triple negative breast cancer (TNBC) before surgery. The early...
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Machine intelligence-driven classification of cancer patients-derived extracellular vesicles using fluorescence correlation spectroscopy: results from a pilot study
Patient-derived extracellular vesicles (EVs) that contains a complex biological cargo is a valuable source of liquid-biopsy diagnostics to aid in...
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Simulation Modelling and Machine Learning Platform for Processing Fluorescence Spectroscopy Data
A digital computational platform is proposed for processing fluorescence spectroscopy data, which implements complex analysis of experimental... -
Super-Focus: Domain Adaptation for Embryo Imaging via Self-supervised Focal Plane Regression
In recent years, the field of embryo imaging has seen an influx of work using machine learning. These works take advantage of large microscopy... -
Navigating with chemometrics and machine learning in chemistry
Chemometrics and machine learning are artificial intelligence-based methods stirring a transformative change in chemistry. Organic synthesis, drug...
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Freely switching between ferroelectric and resistive switching in Hf0.5Zr0.5O2 films and its application on high accuracy on-chip deep neural networks
The Hf 0.5 Zr 0.5 O 2 (HZO)-based ferroelectric field-effect transistor (FeFET) synapse is a promising candidate for at-scale deep neural network (DNN)...
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Enhanced Cellular Detection Using Convolutional Neural Networks and Sliding Window Super-Resolution Inference
Histopathology currently serves as the standard for breast cancer diagnosis, but its manual execution demands time and expertise from pathologists.... -
Spatial redundancy transformer for self-supervised fluorescence image denoising
Fluorescence imaging with high signal-to-noise ratios has become the foundation of accurate visualization and analysis of biological phenomena....
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Learning Guided Electron Microscopy with Active Acquisition
Single-beam scanning electron microscopes (SEM) are widely used to acquire massive datasets for biomedical study, material analysis, and fabrication...