Results 201 to 210 of about 79,319 (254)

Generative Artificial Intelligence for Computer Vision in Endodontics: A Review of Current State and Future Potential

International Endodontic Journal, EarlyView.
ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi, Sanyam Jain, Khuram Naveed, Sepanta Hosseinpour, Lise‐Lotte Kirkevang, Ali Nosrat, Ruben Pauwels   +6 more
wiley   +1 more source

Automated segmentation and source prediction of bone tumors using ConvNeXtv2 Fusion based Mask R-CNN to identify lung cancer metastasis. [PDF]

J Bone Oncol
Zhao K, Dai P, Xiao P, Pan Y, Liao L, Liu J, Yang X, Li Z, Ma Y, Liu J, Zhang Z, Li S, Zhang H, Chen S, Cai F, Tan Z.   +15 more
europepmc   +1 more source

Deep learning assisted high‐resolution microscopy image processing for phase segmentation in functional composite materials

Journal of Microscopy, EarlyView.
Abstract In the domain of battery research, the processing of high‐resolution microscopy images is a challenging task, as it involves dealing with complex images and requires a prior understanding of the components involved. The utilisation of deep learning methodologies for image analysis has attracted considerable interest in recent years, with ...
Ganesh Raghavendran, Bing Han, Fortune Adekogbe, Shuang Bai, Bingyu Lu, William Wu, Minghao Zhang, Ying Shirley Meng   +7 more
wiley   +1 more source

Lumen segmentation using a Mask R-CNN in carotid arteries with stenotic atherosclerotic plaque. [PDF]

Ultrasonics
Kiernan MJ, Al Mukaddim R, Mitchell CC, Maybock J, Wilbrand SM, Dempsey RJ, Varghese T.   +6 more
europepmc   +1 more source

Application of Noise2Inverse and adaptation (Noise2Phase) to single‐mask x‐ray phase contrast micro‐computed tomography

Journal of Microscopy, EarlyView.
Abstract X‐ray phase contrast imaging (XPCI), when implemented in micro‐computed tomography (micro‐CT) mode, offers high‐contrast 3D imaging of weakly‐attenuating material samples. In the so‐called single‐mask edge illumination approach, a mask with periodically spaced transmitting apertures is used to split the x‐ray beam into narrow beamlets; when ...
Khushal Shah, Grammatiki Lioliou, Dai Chen, Alexander Denker, Peter Munro, Marco Endrizzi, Alberto Astolfo, Alessandro Olivo, Charlotte K. Hagen   +8 more
wiley   +1 more source

3SD: Rotational symmetry single‐shot denoising in fluorescence microscopy

Journal of Microscopy, EarlyView.
Abstract Image noise is a fundamental problem in fluorescence microscopy analysis, especially in live cell imaging applications where the number of detected photons is limited due to low power of excitation lasers to prevent phototoxicity during extended imaging experiments.
Tijmen H. de Wolf, Pleun Engbers, Justine Perrin, Julie Nonnekens, Ihor Smal   +4 more
wiley   +1 more source

Artificial Intelligence in Periodontology: A Systematic Review

Journal of Periodontal Research, EarlyView.
AI shows promise across periodontology, with deep learning achieving strong performance for image‐based diagnosis of periodontitis. However, limited data diversity, inconsistent metrics, and scarce external validation raise concerns about generalizability and clinical applicability.
Antonin Tichy, Nils Werner, Helena Dujic, Charlotte Wetzel, Vinay Pitchika, Caspar Victor Bumm, Matthias Folwaczny, Falk Schwendicke   +7 more
wiley   +1 more source

The promise of digital herbarium specimens in large‐scale phenology research

New Phytologist, EarlyView.
Summary The online mobilization of herbaria has made tens of millions of specimens digitally available, revolutionizing investigations of phenology and plant responses to climate change. We identify two main themes associated with this growing body of research and highlight a selection of recent publications exemplifying: investigating phenology at ...
Natalie Iwanycki Ahlstrand, Richard B. Primack, Matthew W. Austin, Zoe A. Panchen, Christine Römermann, Abraham J. Miller‐Rushing   +5 more
wiley   +1 more source

OralSegNet: An Approach to Early Detection of Oral Disease Using Transfer Learning

Oral Diseases, EarlyView.
ABSTRACT Objective Deep learning‐based segmentation system is proposed that exploits three variants of YOLOv11 architecture, namely YOLOv11n‐seg, YOLOv11s‐seg, and YOLOv11m‐seg for automated detection and localization of the oral disease conditions from photographic intraoral images.
Pranta Barua, Md Rakibul Islam, Mahmud Uz Zaman, Adel Alenazi, Fawaz Alqahtani, Huda Abutayyem, Maher Al Shayeb, Ruba Odeh, Nesrine A. Elsahn, Mohammad Khursheed Alam   +9 more
wiley   +1 more source