Virtual and Augmented Medical Imaging Environments: Enabling Technology for Minimally Invasive Cardiac Interventional Guidance
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
Virtual and augmented reality environments have been adopted in medicine as a means to enhance the clinician's view of the anatomy and facilitate the performance of minimally invasive procedures. Their value is truly appreciated during interventions where the surgeon cannot directly visualize the targets to be treated, such as during cardiac procedures performed on the beating heart. These environments must accurately represent the real surgical field and require seamless integration of pre- and intra-operative imaging, surgical tracking, and visualization technology in a common framework centered around the patient. This review begins with an overview of minimally invasive cardiac interventions, describes the architecture of a typical surgical guidance platform including imaging, tracking, registration and visualization, highlights both clinical and engineering accuracy limitations in cardiac image guidance, and discusses the translation of the work from the laboratory into the operating room together with typically encountered challenges.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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