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3D Quantitative Microwave Breast Imaging: Insights from Scans of Patients Undergoing Treatment

2025· article· W4417132813 on OpenAlexaff
Pedram Mojabi, Jeremie Bourqui, Roger Y. Tsang, Elise Fear

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMicrowave imagingBreast cancerMicrowavePermittivityBreast imagingMammographyHigh resolution

Abstract

fetched live from OpenAlex

Microwave imaging has recently attracted interest as a safe and comfortable method for breast imaging. Most previous experimental studies on breast imaging with microwave technology have used radar based approaches to produce qualitative images or two dimensional quantitative reconstructions. This paper presents a fast method for three-dimensional quantitative reconstruction of the breast using a planar high resolution transmission microwave system. In the previous work, we demonstrated the effectiveness of this approach using graphite phantoms and scans of healthy volunteers. In this study, results are presented for two breast cancer patients with different breast density categories prior to the initiation of chemotherapy. The 3D permittivity of both the healthy and cancerous breasts of these patients was reconstructed and compared with their mammograms. For the patient with extremely dense breast tissue, a significant difference was observed between the healthy and cancerous breast based on the permittivity images. Additionally, for one of the patients, the 3D permittivity of the cancerous breast was reconstructed both before and after chemotherapy. The results demonstrate that microwave imaging has the potential to effectively monitor changes in breast tissue during treatment.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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.

Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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