Sci‐Fri PM Imaging‐07: The feasibility of using FBP to reconstruct electron densities from attenuation corrected scatter sinograms
Bibliographic record
Abstract
Breast CT is an emerging modality which aims to generate high quality 3D images. At these energies a large number of the incident x‐ray photons are scattered, resulting in a reduced contrast to noise ratio. As the reduction of dose and the detection of blurred calcifications and other poorly visible lesions are diagnostically important, we have developed an approach which uses both the primary and scattered photons to obtain low‐dose conventional CT and electron density (ρ e ) images. In the absence of attenuation and for a spherical detector, electron densities can be reconstructed using a mono‐energetic pencil beam and conventional Filtered Back Projection (FBP). In place of a spherical detector we have simulated a more practical detector ring with an angular width of 5 degrees and capable of measuring both scattered and primary photons. In practice, attenuation cannot be neglected and Attenuation Correction Factors (ACF) were calculated for each detector using an initial estimate of the electron density based on reconstructed linear attenuation coefficients. The corrected measurements were summed at each rotation and translation of the x‐ray beam to yield a scatter sinogram. This sinogram was processed using FBP to yield an image which provides, in an iterative manner, a new estimate of the electron density. This approach has shown that we are capable of reconstructing electron densities in simple geometries with errors ranging from 2 to 4%. Polyenergetic beam hardening and multiple scattering corrections are being investigated, for future incorporation into the algorithm.
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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 | 0.000 |
| 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".