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Record W1795418637 · doi:10.1109/aps.2001.958840

Confocal microwave imaging for breast tumor detection: comparison of immersion liquids

2002· article· en· W1795418637 on OpenAlexaff
Elise Fear, M.A. Stuchly

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMicrowave imagingBreast cancerMicrowaveBreast tumorConfocalBreast imagingMammographyMaterials scienceBiomedical engineeringOpticsMedicineCancerComputer sciencePhysicsInternal medicine

Abstract

fetched live from OpenAlex

Microwave imaging for breast cancer has been proposed as an alternative or complementary breast imaging technique. The physical basis for tumor detection with microwave imaging is the contrast in dielectric properties of normal and malignant breast tissue. One approach to active microwave imaging of the breast is confocal microwave imaging (CMI). CMI locates tumors using energy reflected from the breast after illumination by an ultra-wideband signal. In one configuration for CMI, a woman lies on her stomach with the breast naturally extending through a hole in the examination table. The illuminating antenna is positioned at a distance from the skin, and physically scanned to a number of locations. Both the antenna and breast are immersed in a low loss liquid for better matching. Previously, our investigations focussed on detection and localization of tumors in a 2D cross section of a simple breast model. We now present 3D localization of tumors achieved with 2 different immersions liquids, one similar to breast tissue and the other similar to skin. For both systems, a 6 mm diameter tumor is reliably detected and localized in 3D. The results do not indicate a clear advantage to selecting either liquid.

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: Empirical · Consensus signal: none
Teacher disagreement score0.636
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.227
Teacher spread0.214 · 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
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

Citations6
Published2002
Admission routes1
Has abstractyes

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