Dr. Aidan D. Meade Profile

Dr. Aidan D. Meade

Lecturer at Technological Univ Dublin

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Publications (10)

Proceedings Article | 19 June 2024 Presentation

Bayesian information criterion for use within spectral unmixing with chemical imaging

Aidan Meade

Proceedings Volume PC13011, PC1301102 (2024) https://doi.org/10.1117/12.3022373

KEYWORDS: Data modeling, Statistical analysis, Signal processing, Statistical modeling, Spectral models, Reliability, Probability theory, Overfitting, Modal decomposition, Information fusion

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Proceedings Article | 18 June 2024 Paper

Using shapley additive explanations saliency for interpretation of multi-class classification of PDX spectral data with deep neural networks

Mohd Rifqi Rafsanjani, Alison Dooney, Rahul Suresh, Alice O'Farrell, Monika Jarzabek, Liam Shiels, Annette Byrne, Jochen H. Prehn, Aidan Meade

Proceedings Volume 13011, 130110F (2024) https://doi.org/10.1117/12.3022370

KEYWORDS: Data modeling, FT-IR spectroscopy, Neural networks, Network architectures, Imaging spectroscopy, Colorectal cancer, Cancer, Chemotherapy

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Proceedings Article | 18 June 2024 Paper

Entropy-based spatial heterogeneity analysis in pathological images for diagnostic applications

Rahul Suresh, Thi Nguyet Que Nguyen, Pascaline Bouzy, Nicholas Stone, Karin Jirstrom, Arman Rahman, William Gallagher, Aidan Meade

Proceedings Volume 13011, 130110E (2024) https://doi.org/10.1117/12.3022363

KEYWORDS: Tissues, FT-IR spectroscopy, Image information entropy, Diseases and disorders, Diagnostics, Cancer, Breast cancer, Imaging spectroscopy, Image analysis, Statistical analysis

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Proceedings Article | 18 June 2024 Paper

Preliminary evaluation of an automated autoencoder-UNet pipeline for chemical image segmentation and compression with reference to serial ground truth pathology

Mohd Rifqi Rafsanjani, Thomas O'Brien, Karin Jirstrom, Arman Rahman, Jochen H. Prehn, William Gallagher, Aidan Meade

Proceedings Volume 13011, 130110D (2024) https://doi.org/10.1117/12.3022279

KEYWORDS: Image segmentation, Image compression, Imaging spectroscopy, Pathology, FT-IR spectroscopy, Tissues, Deep learning, Data modeling

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Proceedings Article | 18 June 2024 Presentation + Paper

Fusion and integration pipelines for optical and chemical imaging data for clinical interpretation in ex vivo diagnosis

Mohd Rifqi Rafsanjani, Karin Jirstrom, Arman Rahman, Jochen H. Prehn, William Gallagher, Aidan Meade

Proceedings Volume 13011, 1301108 (2024) https://doi.org/10.1117/12.3022269

KEYWORDS: Image fusion, Image registration, Image segmentation, Corner detection, Imaging spectroscopy, Tissues, Image processing, FT-IR spectroscopy, Data fusion

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Proceedings Article | 30 August 2023 Paper

In-vitro screening of immune response with FTIR spectroscopy in a miRNA murine knock out model

Ryan Muddiman, Abigail Keogan, Daniel Cullen, Remsha Afzal, Frances Nally, Claire McCoy, Aidan Meade

Proceedings Volume 12627, 1262708 (2023) https://doi.org/10.1117/12.2670747

KEYWORDS: Spectroscopy, Spectral response, In vitro testing, FT-IR spectroscopy

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Proceedings Article | 30 August 2023 Paper

Data fusion strategies for multi-modal classification of auto-immune dysregulation with vibrational spectroscopy

Mohd Rifqi Rafsanjani, Ryan Muddiman, Daniel Cullen, Remsha Afzal, Frances Nally, Claire McCoy, Aidan Meade

Proceedings Volume 12627, 126270A (2023) https://doi.org/10.1117/12.2670990

KEYWORDS: Vibration, Spectroscopy, Data fusion

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Proceedings Article | 16 March 2023 Poster + Paper

Optimisation of Raman spectral processing for classification of radiotherapeutic toxicity

Isha Behl, Dinesh K. R. Medipally, Chris Talbot, Aidan Meade, Fiona Lyng

Proceedings Volume 12387, 123870I (2023) https://doi.org/10.1117/12.2647843

KEYWORDS: Glasses, Raman spectroscopy, Toxicity, Radiotherapy, Plasma, Biological samples, Prostate cancer, Cancer, Blood

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Proceedings Article | 9 June 2011 Paper

Collagen matrices as an improved model for in vitro study of live cells using Raman microspectroscopy

F. Bonnier, P. Knief, A. Meade, J. Dorney, K. Bhattacharya, F. Lyng, H. Byrne

Proceedings Volume 8087, 80870F (2011) https://doi.org/10.1117/12.889872

KEYWORDS: Raman spectroscopy, Collagen, In vitro testing, Confocal microscopy, Spectroscopy, Matrices, Imaging spectroscopy, 3D modeling, Molecular spectroscopy, Data modeling

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Due to its high lateral resolution, Raman microspectrsocopy is rapidly becoming an accepted technique for the subcellular imaging of single cells. Although the potential of the technique has frequently been demonstrated, many improvements have still to be realised to enhance the relevancy of the data collected. Although often employed, chemical fixation of cells can cause modifications to the molecular composition and therefore influence the observations made. However, the weak contribution of water to Raman spectra offers the potential to study live cells cultured in vitro using an immersion lens, giving the possibility to record highly specific spectra from cells in their original state. Unfortunately, in common 2-D culture models, the contribution of the substrates to the spectra recorded requires significant data pre-processing causing difficulties in developing automated methods for the correction of the spectra. Moreover, the 2-D in vitro cell model is not ideal and dissimilarities between different optical substrates within in vitro cell cultures results in morphological and functional changes to the cells. The interaction between the cells and their microenvironment is crucial to their behavior but also their response to different external agents such as radiation or anticancer drugs. In order to create an experimental model closer to the real conditions encountered by the cell in vivo, 3-D collagen gels have been evaluated as a substrate for the spectroscopic study of live cells. It is demonstrated that neither the medium used for cell culture nor the collagen gels themselves contribute to the spectra collected. Thus the background contributions are reduced to that of the water. Spectral measurements can be made in full cell culture medium, allowing prolonged measurement times. Optimizations made in the use of collagen gels for live cells analysis by Raman spectroscopy are encouraging and studying live cells within a collagenous microenvironment seems perfectly accessible.

Proceedings Article | 3 June 2005 Paper

Correlation of spectroscopic and biochemical assays post-ionising radiation exposure in human skin cell analogues

A. Meade, H. Byrne, F. Lyng

Proceedings Volume 5826, (2005) https://doi.org/10.1117/12.611450

KEYWORDS: Raman spectroscopy, Luminescence, Spectroscopy, Proteins, Skin, Mode conditioning cables, Ionizing radiation, Tissue optics, Tissues, Statistical analysis

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Showing 5 of 10 publications

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