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Record W2137498254

Problems created in attenuation-corrected SPECT images by artifacts in attenuation maps: a simulation study.

2005· article· en· W2137498254 on OpenAlexaff
A. Ćeller, Katherine Dixon, Zheng Chang, Stephan Blinder, John Powe, R. Harrop

Bibliographic record

VenuePubMed · 2005
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsVancouver Hospital and Health Sciences Centre
Fundersnot available
KeywordsAttenuationCorrection for attenuationComputer scienceVisibilityTransmission (telecommunications)Image qualityTruncation (statistics)Monte Carlo methodComputer visionSample (material)Artificial intelligenceGround truthMedical physicsOpticsMathematicsPhysicsStatisticsImage (mathematics)Machine learningTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

UNLABELLED: The importance of accurate attenuation correction, especially for imaging of the thorax region, is widely acknowledged. Appropriate compensation methods have been developed and introduced into clinical practice. Most of these methods use attenuation maps obtained using various transmission scanning systems. However, when maps are inaccurate, the correction procedure may introduce artifacts into the final images that can be difficult to identify and might inadvertently alter diagnosis and study outcome. As a result, attenuation correction is often avoided in clinical practice. Our objective was to examine issues related to the quality of attenuation maps and the effects that map artifacts may have on attenuation-corrected emission images. METHODS: The topics that are investigated include the problem of low transmission counts, cross-talk contributions from the emission isotope, truncation of the transmission data, and methods of map reconstruction and segmentation. Examples of patient studies displaying specific problems guided our investigations, but, because truth in these studies is seldom known, analytic and Monte Carlo-simulated data were used in the analysis. Attenuation maps and final emission images were visually checked for artifacts and for the presence of perfusion defects. In addition, quantitative evaluation of map uniformity, defect visibility, and size variation was performed. RESULTS: The statistical paired-sample t test showed significant (P < 0.05) improvement of relative SD for attenuation maps reconstructed with iterative methods as compared with filtered backprojection and for maps created with higher photon fluxes. When maps with artifacts were used to correct emission data, an increase in myocardial infarct size and creation of false heart defects were observed. CONCLUSION: Our study strongly recommends that at least a visual inspection of the quality of attenuation maps be performed before their use in compensation procedures. To improve image quality, remove artifacts, and increase diagnostic confidence, attenuation maps used in the correction procedure must be accurate and free of artifacts.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.406
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.300
Teacher spread0.266 · 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 teacher head, 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

Citations36
Published2005
Admission routes1
Has abstractyes

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