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Record W2093500112 · doi:10.1118/1.3694105

Visibility of microcalcification clusters and masses in breast tomosynthesis image volumes and digital mammography: A 4AFC human observer study

2012· article· en· W2093500112 on OpenAlexaff
Pontus Timberg, Magnus Båth, Ingvar Andersson, S. Mattsson, Anders Tingberg, Mark Ruschin

Bibliographic record

VenueMedical Physics · 2012
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersMalmö Högskola
KeywordsMicrocalcificationMammographyImage qualityNuclear medicineVisibilityDigital mammographyContrast (vision)Observer (physics)Digital Breast TomosynthesisTomosynthesisComputer visionArtificial intelligenceMathematicsMedicineComputer sciencePhysicsOpticsImage (mathematics)

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the visibility of simulated lesions in digital breast tomosynthesis (BT) image volumes compared with 2D digital mammography (DM). METHODS: Simulated lesions (masses and microcalcifications) were added to images of the same women acquired on a DM system (Mammomat Novation, Siemens) and a BT prototype. The same beam quality was used for the DM and BT acquisitions. The total absorbed dose resulting from a 25-projection BT acquisition and reconstruction (BT(25)) was approximately twice that of a single DM view. By excluding every other projection image from the reconstruction (BT(13)), approximately the same dose as in DM was effected. Simulated microcalcifications were digitally added with varying contrast to the DM and BT images. Simulated masses with 8 mm diameter were also added to BT images. A series of 4-alternative forced choice (4AFC) human observer experiments were conducted. Four medical physicists participated in all experiments, each consisting of 60 trials per experimental condition. The observers interpreted the BT image volumes in cine-mode at a fixed image sequence speed. The required threshold contrast (S(t)) to achieve a detectability index (d') of 2.5 (i.e., 92.5% correct decisions) was determined. RESULTS: The S(t) for mass detection in DM was approximately a factor of 2 higher than required in BT indicating that the detection of masses was improved under BT conditions compared to DM. S(t) for microcalcification detection was higher for BT than for DM at both BT dose levels (BT(25) and BT(13)), with a statistically significant difference in S(t) between DM and BT(13). These results indicate a dose-dependent decrease in detection performance in BT for detection of microcalcifications. CONCLUSIONS: In agreement with previous investigations, masses of size 8 mm can be detected with less contrast in BT than in DM indicating improved detection performance for BT. However, for the investigated microcalcifications, the results of this study indicate potentially worse performance for BT than for DM at the same dose level.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.029
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.277
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations57
Published2012
Admission routes1
Has abstractyes

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