3D‐Recontruction of CNS Structures Derived From MRI Scans: New Teaching Tools for Neuroanatomy
Bibliographic record
Abstract
Neuroanatomy requires an understanding of 3D relationships of structures within the brain. This is often a challenge for students who try to visualize these structures from cross‐sectional anatomy or selected pro‐sections. The purpose of this project was to facilitate the 3D understanding of CNS structures through 3D reconstructions from brain MRI scans. 3D reconstructions of various CNS structures were made and posted as edited movies on www.neuroanatomy.ca . 3D reconstructions were based on MRI data sets obtained from a volunteer and from the Visible Human Project (NIH, National Library of Medicine). Structures were manually traced in coronal, sagittal, and transverse planes using AMIRA 4.1 software. The results of this project are available on a website designed for the neuroanatomy laboratory component. The following structures were completed: entire CNS structure, brain vasculature, limbic mamothalamic tracts, optic tracts, eye muscles, subcortical fibers, corpus callosum, thalami and basal ganglia, internal capsule, dentorubrothalamic tract, and spinal tracts. These new additions will allow students to study specific areas and structures of the CNS in 3D. We believe that these tools used in addition with traditional CNS models and specimens, will greatly enhance the spatial understanding of CNS structures for students.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".