Computed tomography (CT) has become very widely used in scientific and medical research and industry for its non-destructive and high-resolution means of detecting internal structure. Three-dimensional segmentation of computed tomography data sheds light on internal features of target objects. Three-dimensional segmentation of CT data is supported by various well-established software programs, but the powerful functionalities and capabilities of open-source software have not been fully revealed. Here, we present a new release of the open-source volume exploration, rendering and three-dimensional segmentation software, v. 2.7. We introduce a new tool for thresholding volume data (i.e. gradient thresholding) and a protocol for performing three-dimensional segmentation using the 3D Freeform Painter tool. These new tools and workflow enable more accurate and precise digital reconstruction, three-dimensional modelling and three-dimensional printing results. We use scan data of a fossil fish as a case study, but our procedure is widely applicable in biological, medical and industrial research.
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http://dx.doi.org/10.1098/rsos.201033 | DOI Listing |
J Colloid Interface Sci
April 2025
College of Physics, Qingdao University, Qingdao 266071, China. Electronic address:
Polyacrylonitrile (PAN)-based composite solid electrolytes (CSEs) hold great promise in the practical deployment of solid lithium batteries (SLBs) owing to their high voltage stability but suffer from poor stability against Li-metal. Herein, a poly(1,3-dioxolane) (PDOL)-graphitic CN (g-CN, i.e.
View Article and Find Full Text PDFJ Thorac Cardiovasc Surg
January 2025
Division of Cardiology, The Hospital for Sick Children, Toronto, ON, Canada; Center for Image Guided Innovation and Therapeutic Intervention, The Hospital for Sick Children, Toronto, ON, Canada.
Objectives: Mixed reality (MixR) is an innovative visualization tool that presents virtual elements in a real-world environment, enabling real-time interaction between the user and the combined digital/physical reality. We aimed to explore the feasibility of MixR in enhancing preoperative planning and intraoperative guidance for the correction of various complex congenital heart defects (CHDs).
Methods: Patients underwent cardiac computed tomography or cardiac magnetic resonance and segmentation of digital imaging and communications in medicine (DICOM) images was performed.
Clin Oral Investig
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, Sichuan, 610041, China.
Objectives: To develop a platform including a deep convolutional neural network (DCNN) for automatic segmentation of the maxillary sinus (MS) and adjacent structures, and automatic algorithms for measuring 3-dimensional (3D) clinical parameters.
Materials And Methods: 175 CBCTs containing 242 MS were used as the training, validating and testing datasets at the ratio of 7:1:2. The datasets contained healthy MS and MS with mild (2-4 mm), moderate (4-10 mm) and severe (10- mm) mucosal thickening.
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 PDFSensors (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.
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