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Record W2343336496

Conception d'un module d'électrodes actives pour un système de tomographie d'impédance électrique bifréquence

2012· article· fr· W2343336496 on OpenAlexaboutno aff
Yannick Sigmen

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2012
Typearticle
Languagefr
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsnot available
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

RESUME La tomographie d'impedance electrique est une technique d'imagerie permettant de visualiser des changements dans les proprietes electriques des tissus d'une region du corps. L'obtention d'une image de TIE se realise en deux etapes : l'acquisition de mesures d'impedance et la reconstruction de la distribution de conductivite. Les mesures de TIE sont obtenues en placant de 16 a 64 electrodes a la surface de la region a imager. En TIE conventionnelle, les mesures d'impedance sont faites a une seule frequence, le plus souvent a 50 kHz. Les images sont reconstruites a partir de deux ensembles de mesures, obtenus a deux instants dierents, an d'observer un changement de conductivite plut^ot qu'une distribution de conductivite absolue. Les images representant un changement de conductivite dans le domaine du temps sont appelees images dierentielles. Un avantage de cette technique d'imagerie est qu'elle permet de minimiser l'eet des erreurs d'instrumentation puisqu'elles sont presentes dans les deux ensembles de mesures. Neanmoins, certains inconvenients sont associes a l'imagerie dierentielle. La stabilite de la reference n'est pas assuree pour des acquisitions de longue duree, a cause de sources d'erreur associees aux performances du systeme et a son ergonomie. Un autre inconvenient de l'imagerie dierentielle est qu'elle est limitee aux applications cliniques pour lesquelles un ensemble de mesures de reference est disponible. Par exemple, on ne pourrait utiliser l'imagerie dierentielle pour detecter une tumeur puisqu'aucun ensemble de mesures de reference n'est disponible avant que la tumeur ne se developpe. La TIE bifrequence (TIE-BF) consiste a acquerir deux ensembles de mesures simultanement a deux frequences dierentes. Cette methode repose sur le fait que les tissus biologiques ont des proprietes electriques, notamment l'admittivite complexe, qui varient en fonction de la frequence, de la structure cellulaire et de leur etat physiologique. En eectuant des mesures a deux frequences choisies pour maximiser les dierences entre deux types de tissus, nous pouvons mettre en evidence des anomalies dans leur structure cellulaire. La TIE-BF ore ainsi un avantage interessant par rapport a la TIE simple frequence du fait que l'utilisation simultanee de deux frequences minimise les erreurs d'instabilite de la reference. Toutefois, les systemes de TIE-BF doivent presenter des performances uniformes sur une grande plage de frequences. Sinon, il peut ^etre dicile de discerner si le changement d'admittivite observe est attribuable a un phenomene physiologique ou aux erreurs dues a la non-uniformite des performances du systeme. Le systeme de TIE du laboratoire d'instrumentation biomedicale de l'Ecole Polytechnique a ete concu pour evaluer la distribution regionale de la ventilation au chevet des patients.----------ABSTRACT Electrical impedance tomography is an imaging technique used to non-invasively monitor changes in the electrical properties of living tissues inside a body region. EIT images are obtained in two steps: impedance measurements are made with electrodes located on the body region of interest and a reconstruction algorithm is applied to obtain the electrical conductivity distribution within that region. In conventional EIT, tissue impedance is measured at a single frequency, typically 50 kHz. Images are reconstructed from two sets of data acquired at dierent times. This technique, called time-dierence imaging, produces images representing changes in tissue conductivity rather than the absolute conductivity distribution. Time-dierence imaging minimizes the eects of instrumentation imperfections, since these errors are present in both data sets used for image reconstruction. However, the technique is sensitive to the stability of the rst measurement set, which is normally used as the reference set. Applicability of time-dierence imaging is also limited to clinical situations where a reference set can be obtained. For instance, the technique cannot be used for detecting a tumour, since a reference data set is not available before the tumour develops. An alternate EIT technique, called frequency-dierence imaging, can overcome many limitations of time-dierence imaging. The technique is based on the fact that electrical properties of biological tissues, namely their complex admittivity, depend on measurement frequency, cellular-level structure of the tissues and physiological state. Frequency-dierence EIT images are reconstructed from two data sets that are acquired simultaneously at two frequencies. By selecting frequencies that maximize dierences in the complex admittance of the tissues of interest, it is possible to enhance their contrast in the images and eventually detect anomalies. However, frequency-dierence imaging requires a high level of uniformity in the EIT system characteristics. Otherwise, it may not be possible to distinguish changes in admittivity that are caused by the physiological process under study or by the frequencydependent variations in system performance. The EIT system developed by the biomedical instrumentation laboratory at Ecole Polytechnique de Montreal has been designed for monitoring lung function at the bedside of ventilated patients. The system provides time-dierence images in real time at a maximum rate of 24 frames per second. It has been optimized for operation at 50 kHz and cannot be used for frequency-dierence imaging since the disparity in channel characteristics at other frequencies would cause artefacts. To solve this problem, we have developed during this project a broadband active electrode module that enables our system to be used for both

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.538
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0010.002
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 head0.212
Teacher spread0.205 · 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 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

Citations2
Published2012
Admission routes1
Has abstractyes

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