Dr. Marien I. Ochoa Profile

Dr. Marien I. Ochoa

Research Assistant

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Author

Publications (18)

SPIE Journal Paper | 18 November 2024 Open Access

Combined dual-channel fluorescence depth sensing of indocyanine green and protoporphyrin IX kinetics in subcutaneous murine tumors

Madhusudan Kulkarni, Matthew Reed, Xu Cao, Héctor García, Marien Ochoa, Shudong Jiang, Tayyaba Hasan, Marvin Doyley, Brian Pogue

JBO, Vol. 30, Issue S1, S13709, (November 2024) https://doi.org/10.1117/12.10.1117/1.JBO.30.S1.S13709

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SignificanceFluorescence sensing within tissue is an effective tool for tissue characterization; however, the modality and geometry of the image acquisition can alter the observed signal.AimWe introduce a novel optical fiber-based system capable of measuring two fluorescent contrast agents through 2 cm of tissue with simple passive electronic switching between the excitation light, simultaneously acquiring fluorescence and excitation data. The goal was to quantify indocyanine green (ICG) and protoporphyrin IX (PpIX) within tissue, and the sampling method was compared with wide-field surface imaging to contrast the value of deep sensing versus surface imaging.ApproachThis was achieved by choosing filters for specific wavelengths that were mutually exclusive between ICG and PpIX and coupling these filters to two separate detectors, which allows for direct swapping of the excitation and emission channels by switching the on-time of each excitation laser between 780- and 633-nm wavelengths.ResultsThis system was compared with two non-contact surface imaging systems for both ICG and PpIX, which revealed that the fluorescence depth sensing system was superior in its ability to resolve kinetics differences in deeper tissues that would normally be dominated by strong signals from skin and other surface tissues. Specifically, the system was tested using pancreatic adenocarcinoma tumors injected into murine models, which were imaged at several time points throughout tumor growth to its ∼6-mm diameter. This demonstrated the system’s capability to track longitudinal changes in ICG and PpIX kinetics that result from tumor growth and development, with larger tumors showing sluggish uptake and clearance of ICG, which was not observable with surface imaging. Similarly, PpIX was quantified, which showed slower kinetics over different time points, and was further compared with the wide-filed imager. These results were further validated through depth measurements in tissue phantoms and model-based interpretation.ConclusionThis fluorescence depth sensing system can be used to sample the interior blood flow characteristics by ICG sensing of tissue as deep as 20 mm into the tissue with sensitivity to kinetics that are superior to surface imaging and may be combined with other imaging modalities such as ultrasound to provide guided deep fluorescence measurements.

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Proceedings Article | 13 March 2024 Presentation + Paper

Tunable phosphorescent hydrogels for Cherenkov-excited luminescence imaging (CELI) of oxygen

Simin Belali, Marien Iliza Ochoa Mendoza, Matthew Reed, Annemarie Lang, Joel Boerckel, Brian Pogue, Sergei Vinogradov

Proceedings Volume 12862, 1286204 (2024) https://doi.org/10.1117/12.3001102

KEYWORDS: Oxygen, Hydrogels, Dendrimers, Phosphorescence, Luminescence, Pulse signals, Tissues, Quenching, Medicine, Matrices

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Proceedings Article | 13 March 2024 Presentation

Pressure enhanced sensing of tissue oxygen: guided surgical resection by detection of hypoxic tissue

Arthur Pétusseau, M. Ochoa, M. Reed, P. Bruza, B. Pogue

Proceedings Volume PC12825, PC1282509 (2024) https://doi.org/10.1117/12.3004516

KEYWORDS: Tissues, Surgery, Resection, Fluorescence, Oxygen, Molecules, Contrast agents, Tumors, Plastics, Neck

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Proceedings Article | 13 March 2024 Presentation

Implementing a standardized method for assessment of open-field guided surgery systems

Marien Ochoa, Alberto Ruiz, Ethan LaRochelle, Matthew Reed, Eren Berber, George Poultsides, Brian Pogue

Proceedings Volume PC12825, PC128250U (2024) https://doi.org/10.1117/12.3003517

KEYWORDS: Surgery, Imaging systems, Standards development, Light sources and illumination, Fluorescence, Equipment, Spatial resolution, Manufacturing, In vitro testing, Image sharpness

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Proceedings Article | 13 March 2024 Presentation

PPIX delayed and prompt fluorescence for in vivo real time imaging of hypoxic response to burns

Marien Ochoa, Aiping Liu, Matthew Reed, Angela Gibson, Brian Pogue

Proceedings Volume PC12854, PC1285403 (2024) https://doi.org/10.1117/12.3003544

KEYWORDS: Fluorescence, In vivo imaging, Fluorescence imaging, Real time imaging, Injuries, Hypoxia, Wound healing, Visualization, Tissues, Quenching

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Proceedings Article | 13 March 2024 Presentation + Paper

Variation in second-window ICG retention is independent of initial vascular permeability in experimental pancreatic adenocarcinoma tumors

Matthew Reed, Marien Ochoa, Marvin Doyley, Brian Pogue

Proceedings Volume 12825, 128250A (2024) https://doi.org/10.1117/12.3003535

KEYWORDS: Tumors, Tissues, Permeability, Biological imaging, Lymphatic system, Imaging systems, Fluorescence imaging, Capillaries, Cameras, Muscles

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SPIE Journal Paper | 21 September 2023 Open Access

Assessment of open-field fluorescence guided surgery systems: implementing a standardized method for characterization and comparison

Marien Ochoa, Alberto Ruiz, Ethan LaRochelle, Matthew Reed, Eren Berber, George Poultsides, Brian Pogue

JBO, Vol. 28, Issue 09, 096007, (September 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.9.096007

KEYWORDS: Imaging systems, Surgery, Fluorescence, Tissues, Light sources and illumination, Spatial resolution, Distortion, Contrast agents, Image processing, Visualization

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SPIE Journal Paper | 13 July 2023 Open Access

Mapping estimates of vascular permeability with a clinical indocyanine green fluorescence imaging system in experimental pancreatic adenocarcinoma tumors

Matthew Reed, Marien Ochoa, Kenneth Tichauer, Ashley Weichmann, Marvin Doyley, Brian Pogue

JBO, Vol. 28, Issue 07, 076001, (July 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.7.076001

KEYWORDS: Tumors, Tissues, Imaging systems, Permeability, Capillaries, Fluorescence imaging, Muscles, Data modeling, Biological imaging, Skin

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Proceedings Article | 17 March 2023 Poster

PPIX delayed fluorescence imaging as a tool for in vivo assessment of hypoxia

Marien Ochoa, Matthew Reed, Arthur Petusseau, Brian Pogue

Proceedings Volume PC12361, PC123610T (2023) https://doi.org/10.1117/12.2668696

KEYWORDS: Hypoxia, In vivo imaging, Fluorescence imaging, Tumors, Tissues, Oxygenation, Oxygen, Mode conditioning cables, Surgery, Quenching

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Proceedings Article | 6 March 2023 Presentation + Paper

Micro-CT guided deep neural network for 3D reconstructions in widefield diffuse optical tomography

Navid Ibtehaj Nizam, Marien Ochoa, Jason Smith, Xavier Intes

Proceedings Volume 12371, 1237105 (2023) https://doi.org/10.1117/12.2650090

KEYWORDS: 3D modeling, Diffuse optical tomography, Neural networks, Light sources and illumination, Inverse problems, Spatial resolution, Optical properties, Optical phantoms

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SPIE Journal Paper | 28 April 2022 Open Access

Monte Carlo-based data generation for efficient deep learning reconstruction of macroscopic diffuse optical tomography and topography applications

Navid Ibtehaj Nizam, Marien Ochoa, Jason T. Smith, Shan Gao, Xavier Intes

JBO, Vol. 27, Issue 08, 083016, (April 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.8.083016

KEYWORDS: Monte Carlo methods, Data modeling, Luminescence, Computer simulations, Reflectivity, Sensors, In vivo imaging, Absorption, Diffuse optical tomography, 3D modeling

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Significance: Deep learning (DL) models are being increasingly developed to map sensor data to the image domain directly. However, DL methodologies are data-driven and require large and diverse data sets to provide robust and accurate image formation performances. For research modalities such as 2D/3D diffuse optical imaging, the lack of large publicly available data sets and the wide variety of instrumentation designs, data types, and applications leads to unique challenges in obtaining well-controlled data sets for training and validation. Meanwhile, great efforts over the last four decades have focused on developing accurate and computationally efficient light propagation models that are flexible enough to simulate a wide variety of experimental conditions. Aim: Recent developments in Monte Carlo (MC)-based modeling offer the unique advantage of simulating accurately light propagation spatially, temporally, and over an extensive range of optical parameters, including minimally to highly scattering tissue within a computationally efficient platform. Herein, we demonstrate how such MC platforms, namely “Monte Carlo eXtreme” and “Mesh-based Monte Carlo,” can be leveraged to generate large and representative data sets for training the DL model efficiently. Approach: We propose data generator pipeline strategies using these platforms and demonstrate their potential in fluorescence optical topography, fluorescence optical tomography, and single-pixel diffuse optical tomography. These applications represent a large variety in instrumentation design, sample properties, and contrast function. Results: DL models trained using the MC-based in silico datasets, validated further with experimental data not used during training, show accurate and promising results. Conclusion: Overall, these MC-based data generation pipelines are expected to support the development of DL models for rapid, robust, and user-friendly image formation in a wide variety of applications.

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SPIE Journal Paper | 25 February 2022 Open Access

Deep learning in macroscopic diffuse optical imaging

Jason Smith, Marien Ochoa, Denzel Faulkner, Grant Haskins, Xavier Intes

JBO, Vol. 27, Issue 02, 020901, (February 2022) https://doi.org/10.1117/12.10.1117/1.JBO.27.2.020901

KEYWORDS: Diffuse optical imaging, Luminescence, Data modeling, Neural networks, Tissue optics, Network architectures, Monte Carlo methods, Tissues, Photons, Tumors

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Proceedings Article | 5 March 2021 Presentation

K-space fluorescence tomography in reflectance: a comparison between deep learning and iterative solvers

Navid Ibtehaj Nizam, Marien Ochoa, Jason Smith, Xavier Intes

Proceedings Volume 11634, 116340D (2021) https://doi.org/10.1117/12.2578613

KEYWORDS: Fluorescence tomography, Reflectivity, Diffuse optical tomography, Tumors, Tomography, Resolution enhancement technologies, Reconstruction algorithms, Optical tomography, Monte Carlo methods, Luminescence

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Proceedings Article | 5 March 2021 Presentation

Single-pixel hyperspectral macroscopic autofluorescence lifetime imaging and unmixing with deep learning

Marien Ochoa Mendoza, Jason Smith, Xavier Intes

Proceedings Volume 11655, 1165505 (2021) https://doi.org/10.1117/12.2577898

KEYWORDS: In vivo imaging, Auto-fluorescence imaging, Tissues, In vitro testing, Visible radiation, Structured light, Spectrophotometry, Single photon, Sensors, Near infrared

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Proceedings Article | 19 February 2020 Presentation + Paper

Quantification of anti-HER2 drug uptake into human breast cancer cells using fluorescence lifetime FRET imaging

Alena Rudkouskaya, Jason Smith, Marien Ochoa, Xavier Intes, Margarida Barroso

Proceedings Volume 11219, 112190C (2020) https://doi.org/10.1117/12.2544429

KEYWORDS: Fluorescence resonance energy transfer, Luminescence, Breast cancer, Fluorescence lifetime imaging, Confocal microscopy, Cancer, Near infrared, Microscopy, Plasma, Tumors

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Proceedings Article | 7 March 2019 Presentation + Paper

Handling negative patterns for fast single-pixel lifetime imaging

Antonio Lorente Mur, Marien Ochoa, Jérémy Cohen, Xavier Intes, Nicolas Ducros

Proceedings Volume 10862, 108620A (2019) https://doi.org/10.1117/12.2511123

KEYWORDS: Spatial light modulators, Matrices, Image compression, Wavelets, Cameras, Sensors, Reconstruction algorithms, Time metrology, Hyperspectral imaging

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Proceedings Article | 4 March 2019 Presentation

IRDye QC-1 as a near-infrared dark acceptor for fluorescence lifetime FRET measurements in cells and in live intact animals (Conference Presentation)

Sez-Jade Chen, Alena Rudkouskaya, Joseph Mazurkiewicz, Marien Ochoa Mendoza, Nattawut Sinsuebphon, Margarida Barroso, Xavier Intes

Proceedings Volume 10882, 108820N (2019) https://doi.org/10.1117/12.2508056

KEYWORDS: Fluorescence resonance energy transfer, Luminescence, Near infrared, In vivo imaging, Multiplexing, Confocal microscopy, Fluorescence lifetime imaging, Resonance energy transfer, Organisms, Absorbance

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SPIE Journal Paper | 14 September 2018 Open Access

Review of structured light in diffuse optical imaging

Joseph Angelo, Sez-Jade Chen, Marien Ochoa, Ulas Sunar, Sylvain Gioux, Xavier Intes

JBO, Vol. 24, Issue 07, 071602, (September 2018) https://doi.org/10.1117/12.10.1117/1.JBO.24.7.071602

KEYWORDS: Imaging systems, Tomography, Structured light, Diffuse optical imaging, Sensors, Tissue optics, Luminescence, Scattering, Spatial frequencies, Photons

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Showing 5 of 18 publications

Conference Committee Involvement (1)

Multimodal Biomedical Imaging XX

25 January 2025 | San Francisco, California, United States

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