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Record W2540127540 · doi:10.1109/iembs.2004.1403893

An Indexed Atlas for Content-based Retrieval and Analysis of Mammograms

2005· article· en· W2540127540 on OpenAlexaff
Harold Lau, Kin Y. Mok, Derek So, Chi K. Tse, Rangaraj M. Rangayyan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicImage Retrieval and Classification Techniques
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAtlas (anatomy)Computer scienceCADComputer-aided diagnosisBreast cancerMammographyImage retrievalInformation retrievalContent-based image retrievalMedicineArtificial intelligenceRadiologyMedical physicsCancerInternal medicineEngineering drawing

Abstract

fetched live from OpenAlex

We describe the development of an indexed atlas of digital mammograms to facilitate content-based retrieval and comparative analysis of mammograms for computer-aided diagnosis (CAD) of breast cancer. Specifically, the requirements and the design of the components of the indexed archival and retrieval system are examined. In order to facilitate search by categories, the mammograms in the atlas are indexed by case number, year of acquisition, category (normal, benign disease, and malignant disease that could be screen-detected or interval cancer), and the presence of signs of disease such as masses, calcifications, bilateral asymmetry, and architectural distortion. In the initial phase of the project, mammograms with masses have been indexed with objective diagnostic features related to their shape, edge definition, and texture. Interfaces to the atlas provide tools for selection and retrieval of cases by text-based or content-based indices. The system should assist radiologists and clinical specialists in CAD of breast cancer.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.745
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.040
GPT teacher head0.294
Teacher spread0.254 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations0
Published2005
Admission routes1
Has abstractyes

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