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Record W4391827310 · doi:10.1109/jsen.2024.3364088

UWB Microwave Breast Screening With Self- Mixed Baseband Analog Signal Processing

2024· article· en· W4391827310 on OpenAlexaff
Mohammad Taherzadeh‐Sani, Maryam Tabatabaei, Maryam Ghamati, Amin Pourvali Kakhki, Leonardo Fortaleza, Frédéric Nabki, Milica Popović

Bibliographic record

VenueIEEE Sensors Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcGill UniversityÉcole de Technologie Supérieure
Fundersnot available
KeywordsBasebandOscilloscopeMicrowave imagingElectronic engineeringBandwidth (computing)AmplifierSIGNAL (programming language)Signal processingCMOSMicrowaveComputer scienceElectrical engineeringEngineeringDigital signal processingTelecommunicationsDetector

Abstract

fetched live from OpenAlex

This article proposes an affordable and fast microwave imaging prototype using a time-domain baseband imaging technique with ultrawideband (UWB) impulse signals. Unlike traditional methods that sample the signal at radio frequency (RF), the signal of the proposed device is self-mixed to be downconverted to baseband, and then sampled using a real-time oscilloscope with a sub-GHz bandwidth. This noticeably simplifies the receiver (RX) and speeds up the signal acquisition. The required RF section of the RX, including the low-noise amplifier (LNA) and self-mixer, is fabricated using a 65-nm CMOS integrated-circuit (IC) technology. Due to the low-frequency content of the received signals, traditional confocal imaging techniques cannot be directly used, and hence an energy-based imaging technique is also proposed. Experiments using a 3-D phantom with a skin layer show 0.5–1.8-cm localization accuracy in the detection of a 1-cm diameter tumor.

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 score0.589
Threshold uncertainty score1.000

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.200
Teacher spread0.193 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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