AIMC Topic: Endoscopy

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Machine Learning-Driven SERS Nanoendoscopy and Optophysiology.

Annual review of analytical chemistry (Palo Alto, Calif.) Jul 2, 2024
A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic ef...
Humans Spectrum Analysis, Raman Nanotechnology Animals Machine Learning Endoscopy
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Predicting Therapeutic Response to Hypoglossal Nerve Stimulation Using Deep Learning.

The Laryngoscope Jun 27, 2024
OBJECTIVES: To develop and validate machine learning (ML) and deep learning (DL) models using drug-induced sleep endoscopy (DISE) images to predict the therapeutic efficacy of hypoglossal nerve stimulator (HGNS) implantation.
Humans Adult Endoscopy Male Retrospective Studies Female Electric Stimulation Therapy Hypoglossal Nerve Middle Aged Treatment Outcome Deep Learning Sleep Apnea, Obstructive Tongue
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Reducing annotating load: Active learning with synthetic images in surgical instrument segmentation.

Medical image analysis Jun 22, 2024
Accurate instrument segmentation in the endoscopic vision of minimally invasive surgery is challenging due to complex instruments and environments. Deep learning techniques have shown competitive performance in recent years. However, deep learning us...
Minimally Invasive Surgical Procedures Surgical Instruments Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Endoscopy Humans
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Enhancing nasal endoscopy: Classification, detection, and segmentation of anatomic landmarks using a convolutional neural network.

International forum of allergy & rhinology Jun 10, 2024
A convolutional neural network (CNN)-based model can accurately localize and segment turbinates in images obtained during nasal endoscopy (NE). This model represents a starting point for algorithms that comprehensively interpret NE findings.
Nose Turbinates Endoscopy Anatomic Landmarks Neural Networks, Computer Humans Algorithms
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Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images.

BMC medical informatics and decision making May 29, 2024
BACKGROUND: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to distinguish the masses by endoscopic examination. Therefore, in this study, we aimed to develop a deep learning algorithm for computer-aided diagnosis...
Humans Adult Diagnosis, Differential Nasal Polyps Papilloma, Inverted Nose Neoplasms Middle Aged Endoscopy Nasal Cavity Diagnosis, Computer-Assisted Male Deep Learning
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Self-Supervised Lightweight Depth Estimation in Endoscopy Combining CNN and Transformer.

IEEE transactions on medical imaging May 2, 2024
In recent years, an increasing number of medical engineering tasks, such as surgical navigation, pre-operative registration, and surgical robotics, rely on 3D reconstruction techniques. Self-supervised depth estimation has attracted interest in endos...
Imaging, Three-Dimensional Image Processing, Computer-Assisted Algorithms Endoscopy Humans Neural Networks, Computer
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Endoscopic surgical field clarity index: An artificial intelligence-based measure of transnasal endoscopic surgical field quality.

International forum of allergy & rhinology Apr 22, 2024
Clear visualization during transnasal endoscopic surgery (TNES) is crucial for safe, efficient surgery. The endoscopic surgical field clarity index (ESFCI) is an artificial intelligence-enabled measure of surgical field quality. The ESFCI allows rese...
Humans Natural Orifice Endoscopic Surgery Nose Artificial Intelligence Endoscopy
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A Swin transformer encoder-based StyleGAN for unbalanced endoscopic image enhancement.

Computers in biology and medicine Apr 16, 2024
With the rapid development of artificial intelligence, automated endoscopy-assisted diagnostic systems have become an effective tool for reducing the diagnostic costs and shortening the treatment cycle of patients. Typically, the performance of these...
Image Interpretation, Computer-Assisted Image Enhancement Stomach Neoplasms Humans Endoscopy Deep Learning Image Processing, Computer-Assisted
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EndoViT: pretraining vision transformers on a large collection of endoscopic images.

International journal of computer assisted radiology and surgery Apr 3, 2024
PURPOSE: Automated endoscopy video analysis is essential for assisting surgeons during medical procedures, but it faces challenges due to complex surgical scenes and limited annotated data. Large-scale pretraining has shown great success in natural l...
Thoracic Surgery, Video-Assisted Automation Large Language Models Natural Language Processing Diagnostic Imaging Minimally Invasive Surgical Procedures Endoscopy Deep Learning Humans
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Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

PloS one Mar 13, 2024
Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a lack of studies on deep learning algorithms for discriminating a wide range of endoscopic nasal cavity mass lesions. Therefore, we aimed to develop an ...
Deep Learning Nasal Cavity Endoscopy Humans Neoplasms Algorithms
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