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Speckle-illumination spatial frequency domain imaging with a stereo laparoscope for profile-corrected optical property mapping.
J Biomed Opt
January 2025
The Johns Hopkins University, Department of Biomedical Engineering, Baltimore, Maryland, United States.
Significance: Laparoscopic surgery presents challenges in localizing oncological margins due to poor contrast between healthy and malignant tissues. Optical properties can uniquely identify various tissue types and disease states with high sensitivity and specificity, making it a promising tool for surgical guidance. Although spatial frequency domain imaging (SFDI) effectively measures quantitative optical properties, its deployment in laparoscopy is challenging due to the constrained imaging environment.
View Article and Find Full Text PDFNeural Radiance Fields for High-Fidelity Soft Tissue Reconstruction in Endoscopy.
Sensors (Basel)
January 2025
Shanghai Film Academy, Shanghai University, Shanghai 200072, China.
The advancement of neural radiance fields (NeRFs) has facilitated the high-quality 3D reconstruction of complex scenes. However, for most NeRFs, reconstructing 3D tissues from endoscopy images poses significant challenges due to the occlusion of soft tissue regions by invalid pixels, deformations in soft tissue, and poor image quality, which severely limits their application in endoscopic scenarios. To address the above issues, we propose a novel framework to reconstruct high-fidelity soft tissue scenes from low-quality endoscopic images.
View Article and Find Full Text PDFSegment Any Leaf 3D: A Zero-Shot 3D Leaf Instance Segmentation Method Based on Multi-View Images.
Sensors (Basel)
January 2025
School of Electronic and Communication Engineering, Sun Yat-sen University, Shenzhen 518000, China.
Exploring the relationships between plant phenotypes and genetic information requires advanced phenotypic analysis techniques for precise characterization. However, the diversity and variability of plant morphology challenge existing methods, which often fail to generalize across species and require extensive annotated data, especially for 3D datasets. This paper proposes a zero-shot 3D leaf instance segmentation method using RGB sensors.
View Article and Find Full Text PDFClinically oriented automatic three-dimensional enamel segmentation via deep learning.
BMC Oral Health
January 2025
Center of Digital Dentistry, Peking University School and Hospital of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices, No.22, Zhongguancun South Avenue, Haidian District, Beijing, 100081, PR China.
Background: Establishing accurate, reliable, and convenient methods for enamel segmentation and analysis is crucial for effectively planning endodontic, orthodontic, and restorative treatments, as well as exploring the evolutionary patterns of mammals. However, no mature, non-destructive method currently exists in clinical dentistry to quickly, accurately, and comprehensively assess the integrity and thickness of enamel chair-side. This study aims to develop a deep learning work, 2.
View Article and Find Full Text PDF[Accuracy of dynamic navigation system for immediate dental implant placement].
Beijing Da Xue Xue Bao Yi Xue Ban
February 2025
First Clinical Division, Peking University School and Hospital of Stomatology & National Center of Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology, Beijing 100081, China.
Objective: Dynamic navigation approaches are widely employed in the context of implant placement surgery. Implant surgery can be divided into immediate and delayed surgery according to the time of implantation. This retrospective study was developed to compare the accuracy of dynamic navigation system for immediate and delayed implantations.
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