AIMC Topic: Optical Imaging

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UNET-FLIM: A Deep Learning-Based Lifetime Determination Method Facilitating Real-Time Monitoring of Rapid Lysosomal pH Variations in Living Cells.

Analytical chemistry Feb 4, 2025
Lifetime determination plays a crucial role in fluorescence lifetime imaging microscopy (FLIM). We introduce UNET-FLIM, a deep learning architecture based on a one-dimensional U-net, specifically designed for lifetime determination. UNET-FLIM focuses...
HeLa Cells Optical Imaging Lysosomes Microscopy, Fluorescence Hydrogen-Ion Concentration Humans Deep Learning
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CTCNet: a fine-grained classification network for fluorescence images of circulating tumor cells.

Medical & biological engineering & computing Jan 22, 2025
The identification and categorization of circulating tumor cells (CTCs) in peripheral blood are imperative for advancing cancer diagnostics and prognostics. The intricacy of various CTCs subtypes, coupled with the difficulty in developing exhaustive ...
Humans Image Processing, Computer-Assisted Neoplastic Cells, Circulating Optical Imaging Neural Networks, Computer Algorithms Deep Learning
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Fluorescence Lifetime Endoscopy with a Nanosecond Time-Gated CAPS Camera with IRF-Free Deep Learning Method.

Sensors (Basel, Switzerland) Jan 14, 2025
Fluorescence imaging has been widely used in fields like (pre)clinical imaging and other domains. With advancements in imaging technology and new fluorescent labels, fluorescence lifetime imaging is gradually gaining recognition. Our research departm...
Fluorescence Deep Learning Image Processing, Computer-Assisted Humans Endoscopy Optical Imaging Phantoms, Imaging
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Deep Equilibrium Unfolding Learning for Noise Estimation and Removal in Optical Molecular Imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Jan 8, 2025
In clinical optical molecular imaging, the need for real-time high frame rates and low excitation doses to ensure patient safety inherently increases susceptibility to detection noise. Faced with the challenge of image degradation caused by severe no...
Image Processing, Computer-Assisted Molecular Imaging Signal-To-Noise Ratio Optical Imaging Humans Algorithms Deep Learning
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Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks.

Photodiagnosis and photodynamic therapy Dec 28, 2024
In recent years, interest in applying deep learning (DL) to medical diagnosis has rapidly increased, driven primarily by the development of Convolutional Neural Networks and Transformers. Despite advancements in DL, the automated diagnosis of skin ca...
Smartphone Optical Imaging Skin Neoplasms Humans Deep Learning Neural Networks, Computer Convolutional Neural Networks
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Machine learning-assisted pattern recognition and imaging of multiplexed cancer cells a porphyrin-embedded dendrimer array.

Journal of materials chemistry. B Dec 18, 2024
Early cancer detection plays a vital role in improving the survival rate of cancer patients, underscoring the importance of developing cancer detection methods. However, it is a great challenge to achieve simple, rapid, and accurate methods for simul...
Microscopy, Confocal Porphyrins Dendrimers Cell Line, Tumor Mice Optical Imaging Humans Machine Learning Animals Neoplasms
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Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.

International journal of oral and maxillofacial surgery Dec 12, 2024
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...
Image Processing, Computer-Assisted Mouth Neoplasms Humans Female Optical Imaging Neural Networks, Computer Fluorescence Sensitivity and Specificity Prospective Studies Aged Convolutional Neural Networks Adult Male Middle Aged
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Let it shine: Autofluorescence of Papanicolaou-stain improves AI-based cytological oral cancer detection.

Computers in biology and medicine Dec 10, 2024
BACKGROUND AND OBJECTIVES: Oral cancer is a global health challenge. The disease can be successfully treated if detected early, but the survival rate drops significantly for late stage cases. There is a growing interest in a shift from the current st...
Optical Imaging Mouth Mucosa Microscopy Image Interpretation, Computer-Assisted Datasets as Topic Humans Adult Biopsy Deep Learning Papanicolaou Test Mouth Neoplasms Early Detection of Cancer Multimodal Imaging
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In Vivo Time-Resolved Fluorescence Detection of Liver Cancer Supported by Machine Learning.

Lasers in surgery and medicine Nov 17, 2024
OBJECTIVES: One of the widely used optical biopsy methods for monitoring cellular and tissue metabolism is time-resolved fluorescence. The use of this method in optical liver biopsy has a high potential for studying the shift in energy-type productio...
Liver Neoplasms Spectrometry, Fluorescence Optical Imaging Humans Machine Learning
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Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Journal of biomedical optics Nov 11, 2024
SIGNIFICANCE: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.
Breast Image Interpretation, Computer-Assisted Humans Breast Neoplasms Optical Imaging ROC Curve Support Vector Machine Machine Learning Transillumination Image Processing, Computer-Assisted Female Area Under Curve
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