ArticleSensors (Basel, Switzerland)2021
Study on Reconstruction and Feature Tracking of Silicone Heart 3D Surface.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Correction: Zhang et al. Study on Reconstruction and Feature Tracking of Silicone Heart 3D Surface.Sensors (Basel, Switzerland) · 2026Article
- Low-Dose CT Image Post-Processing Based on Learn-Type Sparse Transform.Sensors (Basel, Switzerland) · 2022Article
- Improved Feature Point Pair Purification Algorithm Based on SIFT During Endoscope Image Stitching.Frontiers in neurorobotics · 2022Article
- Sparse Angle CBCT Reconstruction Based on Guided Image Filtering.Frontiers in oncology · 2022Article
- Control of Time Delay Force Feedback Teleoperation System With Finite Time Convergence.Frontiers in neurorobotics · 2022Article
- Adaptive control of time delay teleoperation system with uncertain dynamics.Frontiers in neurorobotics · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
At present, feature-based 3D reconstruction and tracking technology is widely applied in the medical field. In minimally invasive surgery, the surgeon can achieve three-dimensional reconstruction through the images obtained by the endoscope in the human body, restore the three-dimensional scene of the area to be operated on, and track the motion of the soft tissue surface. This enables doctors to have a clearer understanding of the location depth of the surgical area, greatly reducing the negative impact of 2D image defects and ensuring smooth operation. In this study, firstly, the 3D coordinates of each feature point are calculated by using the parameters of the parallel binocular endoscope and the spatial geometric constraints. At the same time, the discrete feature points are divided into multiple triangles using the Delaunay triangulation method. Then, the 3D coordinates of feature points and the division results of each triangle are combined to complete the 3D surface reconstruction. Combined with the feature matching method based on convolutional neural network, feature tracking is realized by calculating the three-dimensional coordinate changes of the same feature point in different frames. Finally, experiments are carried out on the endoscope image to complete the 3D surface reconstruction and feature tracking.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.