WE‐DE‐207B‐05: Measuring Spatial Resolution in Digital Breast Tomosynthesis: Update of AAPM Task Group 245
Bibliographic record
Abstract
Purpose: Spatial resolution in digital breast tomosynthesis (DBT) is affected by inherent/binned detector resolution, oblique entry of x‐rays, and focal spot size/motion; the limited angular range further limits spatial resolution in the depth‐direction. While DBT is being widely adopted clinically, imaging performance metrics and quality control protocols have not been standardized. AAPM Task Group 245 on Tomosynthesis Quality Control has been formed to address this deficiency. Methods: Methods of measuring spatial resolution are evaluated using two prototype quality control phantoms for DBT. Spatial resolution in the detector plane is measured in projection and reconstruction domains using edge‐spread function (ESF), point‐spread function (PSF) and modulation transfer function (MTF). Spatial resolution in the depth‐direction and effective slice thickness are measured in the reconstruction domain using slice sensitivity profile (SSP) and artifact spread function (ASF). An oversampled PSF in the depth‐direction is measured using a 50 µm angulated tungsten wire, from which the MTF is computed. Object‐dependent PSF is derived and compared with ASF. Sensitivity of these measurements to phantom positioning, imaging conditions and reconstruction algorithms is evaluated. Results are compared from systems of varying acquisition geometry (9–25 projections over 15–60°). Dependence of measurements on feature size is investigated. Results: Measurements of spatial resolution using PSF and LSF are shown to depend on feature size; depth‐direction spatial resolution measurements are shown to similarly depend on feature size for ASF, though deconvolution with an object function removes feature size‐dependence. A slanted wire may be used to measure oversampled PSFs, from which MTFs may be computed for both in‐plane and depth‐direction resolution. Conclusion: Spatial resolution measured using PSF is object‐independent with sufficiently small object; MTF is object‐independent. Depth‐direction spatial resolution may be measured directly using MTF or indirectly using ASF or SSP as surrogate measurements. While MTF is object‐independent, it is invalid for nonlinear reconstructions.
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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".