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Record W2902809607 · doi:10.22215/etd/2014-10460

Sensitivity and Distortion Studies of Positron Emission Trancking System (PeTrack)

2014· dissertation· en· W2902809607 on OpenAlexaff
Simin Razavi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsDistortion (music)Tracking (education)Sensitivity (control systems)DetectorScalingMonte Carlo methodPhysicsField of viewOpticsComputer scienceElectronic engineeringEngineeringMathematicsGeometryStatisticsOptoelectronics

Abstract

fetched live from OpenAlex

Positron Emission Tracking (PeTrack) is a new real-time 3D tracking technique.The project studied the sensitivity and distortion of the PeTrack system with four different detector field of view (FOV) configurations using Monte-Carlo simulation software (GATE).The simulation studies demonstrated the clear boundaries for FOV and also revealed a local distortion up to 1 mm for PeTrack.The simulation also showed that the detector misalignment could introduce the distortion to the system.The amplitude of the distortion is approximately the half of the misalignment at the center of the FOV.The results of simulations lead us to calibrate the PeTrack system to obtain the global scaling factors.However, since PeTrack has a nonuniform distortion across FOV, the global scaling factors were helpful to only some extent.The value of calculated average error after global scaling correction is less than 1 mm.The PeTrack system is also co-registered with an x-ray imaging C-arm to evaluate the tracking performance.iii I would like to dedicate this thesis to My true love Ahad, My supportive family, & My great supervisor

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.353
Teacher spread0.330 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2014
Admission routes1
Has abstractyes

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