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Record W7067693091

Multi-modal, mobile microscopy for visualization of biological agents

2021· dissertation· en· W7067693091 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueeScholarship@McGill (McGill) · 2021
Typedissertation
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaAdvanced Research Projects AgencyDefense Advanced Research Projects AgencyMcGill University
KeywordsVisualizationMobile phoneLens (geology)Biological imagingMicroscopyMicrofluidicsResolution (logic)PhoneInterface (matter)Biological specimen
DOInot available

Abstract

fetched live from OpenAlex

Biological and biomedical research is often contingent upon microscopy techniques for observation and studying of biological features and processes, and subsequent analysis.For many applications, it is necessary that the selected imaging system provide high spatial resolution and large field-of-view, in order to be able to visualize individual biological structures or agents within the sample, while capturing an area large enough, where meaningful analysis, such as particle tracking, could be performed within a single frame.Various lens-based and lens-free imaging platforms, each with their own sets of advantages and disadvantages, offer different imaging modalities suitable for different specimens and applications, but they all suffer from a main limitation: the trade-off between spatial resolution and field-of-view.This competition cannot be eliminated but could be optimized, based on the chosen imaging system specifications.This work addresses the restrictive trade-off, and introduces a mobile phone-based illumination-imaging platform that maximizes the attainable field-of-view at high resolution, and expands the use of phone screen illumination to a lens-free platform.The thesis transitions from a broad introduction to microscopy in the biological and biomedical fields into a general protocol for identification of imaging system requirements for a targeted application, modelled after a specific example for imaging of a biocomputational microfluidic device that utilizes microorganisms as exploratory problem-solving agents.The following chapters introduce the aforementioned dual-phone system, which uses a phone camera with an external lens for imaging, to achieve a spatial resolution of at least 2 m, and a large field-of-view of 3.6 2.7 mm.For illumination, it uses the screen of another phone to project multi-modal illumination patterns, including but not limited to brightfield, dark-field, Rheinberg illumination, point illumination, fluorescence, and differential phase contrast.Put together, this illumination-imaging system forms a novel, inexpensive, compact, portable, and versatile microscope for use in low-resource environments.It could be used in research, medical, educational, and environmental settings for both qualitative and quantitative imaging of cells, microorganisms, and other micron-sized objects.The adaptability of phone screen illumination allows it to be further integrated into lens-free imaging platforms, as well as conventional microscopes.V. Nicolau, for providing me with this great opportunity to learn, grow, and prove to them and to myself how fulfilling the fruit of perseverance and hard work can be.When days were rough, you helped guide me back onto the right path and regain my discipline.For that, and for your invaluable mentorship, I thank you.Additionally, I would also like to thank my co-supervisor, Sylvain Martel, and my Ph.D. committee members for their precious guidance on my work and future steps.Lastly, I would like to express my gratitude towards the Faculty of

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.038
GPT teacher head0.331
Teacher spread0.293 · 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