Bibliographic record
Abstract
Bone cutting in surgery is currently done using un-intelligent tools that depend on the proficiency of the surgeon to prevent damage to underlying critical structures. As one can imagine, damage isn’t always prevented. Iatrogenic damage to dura and sub-dural neural structures during osteotomical procedures such as a craniotomy can result in increased patient morbidity. This dissertation proposes the development of a robot-guided laser osteotome (bone cutter) with the use of inline optical coherence tomography (OCT) to precisely control the cutting depth in real-time. The all-fiber system design integrates a high peak-power pulsed Yb-doped fiber laser (1064nm) coupled directly into the sample arm of a swept-source OCT system (λc = 1310nm) with a fourth-order power disparity between the OCT system and fiber laser. Sub-millimeter accuracy was achieved in percussion drilling of phantom and porcine bone. Through the use of optical topographic imaging (OTI), this work presents a novel method for the surgeon to identify arbitrary trajectories for desired cuts. A surgical pencil is used to demarcate cutting trajectories for the robot to follow directly onto the boney surface. OTI imaging combined with a novel algorithm developed through this work allows the penscribed line to be isolated and translated into spatial attitude information for the robot to guide the end effector-mounted laser along. Sub-millimeter trajectory following accuracy was achieved. This work also demonstrates the first use of OCT in continuous, real-time refocusing of the optical end-effector in order to maintain cut quality. The focus of the laser was able to be maintained within the Rayleigh length of the focused Gaussian beam for linear feed rates up to 1mm/s at a 45◦ surface incline. Finally, optimization of bone ablation is explored in this dissertation. The use of graphite as a high-absorption topical chromophore and the use of nitrogen as an assist gas in the form of a coaxial jet are both analyzed to determine how to achieve the highest etch rate in bone. The results in this dissertation show that the topical application of graphite was able to significantly reduce the mean and variance of etching performance; an improvement by at least two orders of magnitude in the time to 0.5mm etch depth is demonstrated. It is also demonstrated that etch rate during ablation can be optimized for coaxial nitrogen flow (30SCFH out of a nozzle with 3mm output diameter); higher and lower flow rates showed slower etch rates. It is hypothesized that a system such as the one developed in this dissertation will increase the precision of bone cutting, decrease the amount of time needed to make cuts into sensitive structures and also address certain issues of unsuccessful uptake of lasers in modern medicine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".