AIMC Topic: Optical Imaging

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Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.

Photodiagnosis and photodynamic therapy Jun 27, 2024
Diabetes, characterized by heightened blood sugar levels, can lead to a condition called Diabetic Retinopathy (DR), which adversely impacts the eyes due to elevated blood sugar affecting the retinal blood vessels. The most common cause of blindness i...
Optical Imaging Diabetic Retinopathy Humans Neural Networks, Computer Algorithms Deep Learning
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Fluorescence excitation-scanning hyperspectral imaging with scalable 2D-3D deep learning framework for colorectal cancer detection.

Scientific reports Jun 26, 2024
Colorectal cancer is one of the top contributors to cancer-related deaths in the United States, with over 100,000 estimated cases in 2020 and over 50,000 deaths. The most common screening technique is minimally invasive colonoscopy using either refle...
Colorectal Neoplasms Colonoscopy Humans Early Detection of Cancer Deep Learning Hyperspectral Imaging Optical Imaging Image Processing, Computer-Assisted
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Machine-Learning-Assisted Rational Design of Si─Rhodamine as Cathepsin-pH-Activated Probe for Accurate Fluorescence Navigation.

Advanced materials (Deerfield Beach, Fla.) May 31, 2024
High-performance fluorescent probes stand as indispensable tools in fluorescence-guided imaging, and are crucial for precise delineation of focal tissue while minimizing unnecessary removal of healthy tissue. Herein, machine-learning-assisted strateg...
Carcinoma, Hepatocellular Fluorescent Dyes Machine Learning Liver Neoplasms Optical Imaging Rhodamines Cathepsins Hydrogen-Ion Concentration Silicon Humans
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Knowledge, attitudes and practices of using Indocyanine Green (ICG) fluorescence in emergency surgery: an international web-based survey in the ARtificial Intelligence in Emergency and trauma Surgery (ARIES)-WSES project.

Updates in surgery May 27, 2024
Fluorescence imaging is a real-time intraoperative navigation modality to enhance surgical vision and it can guide emergency surgeons while performing difficult, high-risk surgical procedures. The aim of this study is to assess current knowledge, att...
Indocyanine Green Optical Imaging Acute Care Surgery Health Knowledge, Attitudes, Practice Internet Fluorescence Surveys and Questionnaires Humans Surgeons Emergencies Artificial Intelligence
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Integrating optical and electrical sensing with machine learning for advanced particle characterization.

Biomedical microdevices May 23, 2024
Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires ac...
Optical Imaging Machine Learning Algorithms
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Tumor Segmentation in Intraoperative Fluorescence Images Based on Transfer Learning and Convolutional Neural Networks.

Surgical innovation Apr 15, 2024
OBJECTIVE: To propose a transfer learning based method of tumor segmentation in intraoperative fluorescence images, which will assist surgeons to efficiently and accurately identify the boundary of tumors of interest.
Optical Imaging Image Processing, Computer-Assisted Surgery, Computer-Assisted Humans Neoplasms Neural Networks, Computer Deep Learning
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Novel navigation for laparoscopic cholecystectomy fusing artificial intelligence and indocyanine green fluorescent imaging.

Journal of hepato-biliary-pancreatic sciences Apr 1, 2024
This preliminary study is the first to demonstrate that AI can precisely identify loose connective tissue during laparoscopic cholecystectomy and ICG fluorescent cholangiography. Tashiro and colleagues conclude that this novel real-time navigation mo...
Humans Artificial Intelligence Surgery, Computer-Assisted Cholangiography Cholecystectomy, Laparoscopic Coloring Agents Optical Imaging Indocyanine Green
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Highly robust reconstruction framework for three-dimensional optical imaging based on physical model constrained neural networks.

Physics in medicine and biology Mar 21, 2024
. The reconstruction of three-dimensional optical imaging that can quantitatively acquire the target distribution from surface measurements is a serious ill-posed problem. Traditional regularization-based reconstruction can solve such ill-posed probl...
Algorithms Deep Learning Neural Networks, Computer Optical Imaging Imaging, Three-Dimensional Image Processing, Computer-Assisted
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Image2InChI: Automated Molecular Optical Image Recognition.

Journal of chemical information and modeling Feb 15, 2024
The accurate identification and analysis of chemical structures in molecular images are prerequisites of artificial intelligence for drug discovery. It is important to efficiently and automatically convert molecular images into machine-readable repre...
Image Processing, Computer-Assisted Drug Discovery Optical Imaging Deep Learning
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Applications of machine learning in time-domain fluorescence lifetime imaging: a review.

Methods and applications in fluorescence Feb 8, 2024
Many medical imaging modalities have benefited from recent advances in Machine Learning (ML), specifically in deep learning, such as neural networks. Computers can be trained to investigate and enhance medical imaging methods without using valuable h...
Optical Imaging Humans Machine Learning Image Processing, Computer-Assisted Microscopy, Fluorescence
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