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Efficiency of Real-time Computer-aided Polyp Detection during Surveillance Colonoscopy: A Pilot Study.
J Anus Rectum Colon
January 2025
Department of Gastroenterology, Hiroshima University Hospital, Hiroshima, Japan.
Objectives: Studies have suggested that computer-aided polyp detection using artificial intelligence improves adenoma identification during colonoscopy. However, its real-world effectiveness remains unclear. Therefore, this study evaluated the usefulness of computer-aided detection during regular surveillance colonoscopy.
View Article and Find Full Text PDFEvaluation of Artificial Intelligence: Computer-aided Detection of Colorectal Polyps.
J Anus Rectum Colon
January 2025
Department of Endoscopy, Fukuoka University Chikushi Hospital, Chikushino, Japan.
Objectives: Colonoscopy is the gold standard for screening cancer and precancerous lesions in the large intestine. Recently, remarkable advances in artificial intelligence (AI) have led to the development of various computer-aided detection (CADe) systems for colonoscopy. This study aimed to evaluate the usefulness of AI for colonoscopy using CAD-EYE (Fujifilm, Tokyo, Japan) to calculate the adenoma miss rate (AMR).
View Article and Find Full Text PDF3D Segmentation of Whole Lung and Metastatic Lung Nodules Using Adaptive Region Growing and Shape-based Morphology.
J Comput Assist Tomogr
January 2025
Centre for Biomedical Engineering, Indian Institute of Technology Delhi.
Objective: Early diagnosis of primary and metastatic lung nodules is critical for effective therapeutic planning. Manual delineation of lung nodules is not time-efficient and is prone to human error as well as interobserver and intraobserver variability. This study aimed to address the unmet need for an open-source computer-aided detection (CAD) system for 3D segmentation of lung and metastatic lung nodules along with radiomic feature extraction.
View Article and Find Full Text PDFLaser-based 3D printing and optical characterization of optical micro-nanostructures inspired by nocturnal insects compound eyes.
Sci Rep
January 2025
Center for Advanced Laser Technologies (CETAL), National Institute for Lasers, Plasma and Radiation Physics, Magurele-Ilfov, 077125, Romania.
Nature offers unique examples that help humans produce artificial systems which mimic specific functions of living organisms and provide solutions to complex technical problems of the modern world. For example, the development of 3D micro-nanostructures that mimic nocturnal insect eyes (optimized for night vision), emerges as promising technology for detection in IR spectral region. Here, we report a proof of principle concerning the design and laser 3D printing of all ultrastructural details of nocturnal moth Grapholita Funebrana eyes, for potential use as microlens arrays for IR detection systems.
View Article and Find Full Text PDFBackground: Investigators and funding organizations desire knowledge on topics and trends in publicly funded research but current efforts for manual categorization have been limited in breadth and depth of understanding.
Purpose: We present a semi-automated analysis of 21 years of R-type National Cancer Institute (NCI) grants to departments of radiation oncology and radiology using natural language processing (NLP).
Methods: We selected all non-education R-type NCI grants from 2000 to 2020 awarded to departments of radiation oncology/radiology with affiliated schools of medicine.
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