Modeling, Simulation, and Optimal Initiation Planning For Needle Insertion Into the Liver
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study was constrained to planar (2D) cases, but can be extended to 3D insertions. To accommodate large and velocity-dependent deformations, a hyperviscoelastic model was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two interpolation-based models are introduced to approximate puncture times and to approximate the coordinates of FE model nodes interacting with the needle tip as a function of the needle initiation pose; the latter was also a function of postpuncture time. A real-time simulation framework is provided, and its computational benefit is highlighted by comparing its performance with the FE method. A planning algorithm for optimal needle initiation was designed, and its effectiveness was evaluated by analyzing its accuracy in reaching a random set of targets at different resolutions of sampled data using the FE model. The proposed simulation framework can easily surpass haptic rates (>500 Hz), even with a high pose resolution level ( approximately 30). The computational time required to update the coordinates of the node at the needle tip in the provided example was reduced from 177 s to 0.8069 ms. The planning accuracy was acceptable even with moderate resolution levels: root-mean-square and maximum errors were 1 mm and 1.2 mm, respectively, for a pose and PPT resolution levels of 17 and 20, respectively. The proposed interpolation-based models significantly improve the computational speed of needle insertion simulation and planning, based on the discretized (FE) model of the liver and can be utilized to establish a cost-effective planning platform. This modeling approach can also be extended for use in other surgical simulations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it