Emilie Péry

Monte Carlo modeling of multilayer phantoms with multiple fluorophores: simulation algorithm and experimental validation

This work is first a description of a statistical simulation algorithm developed for simulating the spectral absorption and emission of several fluorophores in an absorbing and diffusing multilayer model. Second, a detailed experimental validation of the simulation program is conducted on two sets of liquid and solid multilayer phantoms, containing one, two, or three fluorophores, within absorbing and scattering media. Experimental spatially resolved reflectance spectra are acquired in the wavelength band 400 to 800 nm and compared to corresponding simulated spectra. The degree of similarity between experimentation and simulation data is quantified. The results obtained underline good correlations with mean errors varying from 2 to 10%, depending on the number of layers and on the complexity of the phantoms composition.

Spectral Features Selection and Classification for Bimodal Optical Spectroscopy Applied to Bladder Cancer In Vivo Diagnosis

This paper describes an experimental study combining spatially resolved autofluorescence (AF) and diffuse reflectance (DR) fibred spectroscopies to discriminate in vivo between healthy and pathological tissues in a preclinical model of bladder cancer. Then, a detailed step-by-step analysis scheme is presented for the extraction and the selection of discriminative spectral features (correlation, linear discriminant, and logistic regression analysis), and for the spectroscopic data final classification algorithms (regularized discriminant analysis and support vector machines). Significant differences between healthy, inflammatory, and tumoral tissues were obtained by selecting a reasonable number of discriminant spectral features from AF, DR, and intrinsic fluorescence spectra, leading to improved sensitivity (87%) and specificity (77%) compared to monomodality (AF or DR alone).

Simultaneous Characterization of Optical and Rheological Properties of Carotid Arteries via Bimodal Spectroscopy: Experimental and Simulation Results

This study aimed at identifying potential correlations between rheological and optical properties of carotid artery rings before and after cryopreservation at different mechanical deformations using experimental and simulation results. Therefore, a uniaxial mechanical test bench was coupled to fibered optical spectroscopes measuring 410 nm excited autofluorescence and 650-850 nm elastically backscattered intensity spectra. Furthermore, we developed a statistical simulation program of light transport and fluorescence adapted to our specific experimental configuration. Both spectroscopies gave intensity spectra with higher amplitude for the cryopreserved samples. These observations are to be related to histological modifications affecting the arterial wall of postcryopreserved samples. We also observed significant spectral amplitude variations (increasing autofluorescence intensity and decreasing diffuse reflectance) as a function of the circumferential strains (0%-60%). Due to simulation, we identified values of absorption, diffusion, and anisotropy coefficients, and their variations as a function of state (fresh-cryopreserved), strains (0, 30%, 60%), and wavelengths (700, 740, 780 nm). The media and the adventice are, respectively, less and more absorbing for postcryopreserved rings, and it is the opposite for the fresh ones at higher wavelengths. Absorption and diffusion coefficients are slightly higher, whatever the wavelengths and strains, for the fresh than for the cryopreserved samples.

Contour segmentation of the intima, media, and adventitia layers in intracoronary OCT images application to fully automatic detection of healthy wall regions

PurposeQuantitative and automatic analysis of intracoronary optical coherence tomography images is useful and time-saving to assess cardiovascular risk in the clinical arena.MethodsFirst, the interfaces of the intima, media, and adventitia layers are segmented, by means of an original front propagation scheme, running in a 4D multi-parametric space, to simultaneously extract three non-crossing contours in the initial cross-sectional image. Second, information resulting from the tentative contours is exploited by a machine learning approach to identify healthy and diseased regions of the arterial wall. The framework is fully automatic.ResultsThe method was applied to 40 patients from two different medical centers. The framework was trained on 140 images and validated on 260 other images. For the contour segmentation method, the average segmentation errors were

Experimental comparison between autofluorescence spectra of constrained fresh and cryopreserved arteries

29 \pm 46~\upmu \text {m}

Diffuse reflectance spectroscopy's sensitivity to a melanic layer thickness variations: an in vitro study on skin phantoms

29±46μm for the intima–media interface,

Preliminary results for the supervised detection of lumen and stent from OCT pullbacks

30 \pm 50~\upmu \text {m}