Effects of attenuation in single slow rotation dynamic SPECT
Bibliographic record
Abstract
Dynamic imaging using SPECT has been a topic of research interest for many years. Several proposed approaches have considered the reconstruction of dynamic images from SPECT data acquired with a conventional single slow rotation of the camera, which results in an extremely underdetermined reconstruction problem. Accurate attenuation correction (AC) is particularly important in this context, in order to distinguish the actual dynamic behavior of the tracer within a region from the effects of attenuation on the projection data as the camera rotates around the patient. In this paper, we demonstrate that the standard approach to AC used in conventional SPECT imaging is not sufficient to account for the effects of attenuation in dynamic imaging of this type. As a result, artifacts may be created in the reconstructed images. Using realistic dynamic 3D phantom simulations, as well as real-life dynamic renal SPECT data, we assess the severity of these artifacts and investigate a method to eliminate them. The proposed method is shown to substantially improve the accuracy of the reconstructed image.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".