See-Through Type 3D Head-Mounted Display–Based Surgical Microscope System for Microsurgery: A Feasibility Study
Bibliographic record
Abstract
BACKGROUND: The surgical microscope is used primarily for microsurgeries, which are more complicated than other surgical procedures and require delicate tasks for a long time. Therefore, during these surgical procedures, surgeons experience back and neck pain. To solve this problem, new technology, such as wearable displays, is required to help surgeons maintain comfortable postures and enjoy advanced functionality during microsurgery. OBJECTIVE: The objective of this study was to develop a surgical microscope system that would work with wearable devices. It would include a head-mounted display (HMD) that can offer 3D surgical images and allow a flexible and comfortable posture instead of fixed eyepieces of surgical microscope and can also provide peripheral visual field with its optical see-through function. METHODS: We designed and fabricated a surgical microscope system that incorporates a see-through type 3D HMD, and we developed an image processing software to provide better image quality. The usability of the proposed system was confirmed with preclinical examination. Seven ENT (ear, nose, and throat) surgical specialists and 8 residents performed a mock surgery-axillary lymph node dissection on a rat. They alternated between looking through the eyepieces of the surgical microscope and viewing a 3D HMD screen connected to the surgical microscope. We examined the success of the surgery and asked the specialists and residents to grade eye fatigue on a scale of 0 (none) to 6 (severe) and posture discomfort on a scale of 1 (none) to 5 (severe). Furthermore, a statistical comparison was performed using 2-tailed paired t test, and P=.00083 was considered significant. RESULTS: Although 3D HMD case showed a slightly better result regarding visual discomfort (P=.097), the average eye fatigue was not significantly different between eyepiece and 3D HMD cases (P=.79). However, the average posture discomfort, especially in neck and shoulder, was lower with 3D HMD display use than with eyepiece use (P=.00083). CONCLUSIONS: We developed a see-through type 3D HMD-based surgical microscope system and showed through preclinical testing that the system could help reduce posture discomfort. The proposed system, with its advanced functions, could be a promising new technique for microsurgery.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".