AIMC Topic: Optical Imaging

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Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Journal of medical systems
Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cancer cells is mainly studied by two-dimensional light scattering technology. Firstly, a single-cell two...

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks.

International journal of computer assisted radiology and surgery
PURPOSE: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to address the inverse problem of converting pixel-wise multispectral reflectan...

Diagnosis of early gastric cancer based on fluorescence hyperspectral imaging technology combined with partial-least-square discriminant analysis and support vector machine.

Journal of biophotonics
This study investigated the feasibility of using fluorescence hyperspectral imaging technology to diagnose of early-stage gastric cancer. Fluorescence spectral images of 76 patients who were pathologically diagnosed as non-atrophic gastritis, premali...

Predicting Hemodynamic Shock from Thermal Images using Machine Learning.

Scientific reports
Proactive detection of hemodynamic shock can prevent organ failure and save lives. Thermal imaging is a non-invasive, non-contact modality to capture body surface temperature with the potential to reveal underlying perfusion disturbance in shock. In ...

Near-infrared mito-specific fluorescent probe for ratiometric detection and imaging of alkaline phosphatase activity with high sensitivity.

Journal of materials chemistry. B
Fluorescent probe-based analytical methods for biological species have gained increasing attention for their powerful detection and imaging capabilities. However, it is still occasionally problematic for accurate analyses due to the influence of the ...

Hyperspectral Tissue Image Segmentation Using Semi-Supervised NMF and Hierarchical Clustering.

IEEE transactions on medical imaging
Hyperspectral imaging (HSI) of tissue samples in the mid-infrared (mid-IR) range provides spectro-chemical and tissue structure information at sub-cellular spatial resolution. Disease states can be directly assessed by analyzing the mid-IR spectra of...

Supervised Segmentation of Un-Annotated Retinal Fundus Images by Synthesis.

IEEE transactions on medical imaging
We focus on the practical challenge of segmenting new retinal fundus images that are dissimilar to existing well-annotated data sets. It is addressed in this paper by a supervised learning pipeline, with its core being the construction of a synthetic...

A method for optical imaging and monitoring of the excretion of fluorescent nanocomposites from the body using artificial neural networks.

Nanomedicine : nanotechnology, biology, and medicine
In this study, a new approach to the implementation of optical imaging of fluorescent nanoparticles in a biological medium using artificial neural networks is proposed. The studies were carried out using new synthesized nanocomposites - nanometer gra...

Prediction analysis and quality assessment of microwell array images.

Electrophoresis
Microwell arrays are widely used for the analysis of fluorescent-labelled biomaterials. For rapid detection and automated analysis of microwell arrays, the computational image analysis is required. Support Vector Machines (SVM) can be used for this t...

WorMachine: machine learning-based phenotypic analysis tool for worms.

BMC biology
BACKGROUND: Caenorhabditis elegans nematodes are powerful model organisms, yet quantification of visible phenotypes is still often labor-intensive, biased, and error-prone. We developed WorMachine, a three-step MATLAB-based image analysis software th...