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Record W2059492871 · doi:10.1109/icip.2011.6116309

3D microscopic imaging by synchrotron radiation micro/nano-CT

2011· preprint· en· W2059492871 on OpenAlexaff
Françoise Peyrin, Alexandra Pacureanu, Max Langer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicAdvanced X-ray Imaging Techniques
Canadian institutionsCanadian Nautical Research Society
Fundersnot available
KeywordsSynchrotron radiationContext (archaeology)Iterative reconstructionData acquisitionComputer scienceSynchrotronComputer visionSegmentationMaterials scienceImaging phantomProjection (relational algebra)Biomedical engineeringImage resolutionArtificial intelligenceOpticsPhysicsMedicineAlgorithm

Abstract

fetched live from OpenAlex

Biological microscopic imaging is receiving increasing interest with the development of new modalities. In this context Synchrotron Radiation (SR) Nano-CT demonstrates a high potential in opening new horizons. We recall the principle of SR micro-CT and its advantages over standard X-ray micro-CT in terms of accuracy and signal to noise ratio. We briefly present data acquisition and reconstruction in absorption and phase CT. While in the first case image reconstruction is based simply on the standard filtered back projection algorithm, in the later case it involves a preliminary step of phase retrieval. Applications of this technique in bone research in conjunction with specific image analysis developments are shown. At the micrometer scale, trabecular and cortical bone have been analyzed in human samples and mice. At the nanometer scale, we present recent data on the osteocyte network which has never before been investigated in 3D. Open problems for the segmentation and quantification of the complex canalicular network are highlighted.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.007
GPT teacher head0.264
Teacher spread0.257 · 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
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

Citations2
Published2011
Admission routes1
Has abstractyes

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