FREEnet: a dynamic deep-learning model for freehand diffuse optical tomography
R Dale, T O'Sullivan, H Dehghani - Optics and the Brain, 2024 - opg.optica.org
FREEnet: a dynamic deep-learning model for freehand diffuse optical tomography Page 1
FREEnet: a dynamic deep-learning model for freehand diffuse optical tomography Robin …
FREEnet: a dynamic deep-learning model for freehand diffuse optical tomography Robin …
Wide-field diffuse optical tomography using deep learning
Wide-field Diffuse Optical Tomography Using Deep Learning Page 1 Wide-field Diffuse Optical
Tomography Using Deep Learning Navid Ibtehaj Nizam †, * , Marien Ochoa † , Jason T. Smith …
Tomography Using Deep Learning Navid Ibtehaj Nizam †, * , Marien Ochoa † , Jason T. Smith …
High-Speed Time-Domain Diffuse Optical Tomography With a Sensitivity Equation-Based Neural Network
Steady progress in time-domain diffuse optical tomography (TD-DOT) technology is allowing
for the first time the design of low-cost, compact, and high-performance systems, thus …
for the first time the design of low-cost, compact, and high-performance systems, thus …
A Modular Deep Learning-based Approach for Diffuse Optical Tomography Reconstruction
A Benfenati, P Causin, M Quinteri - arXiv preprint arXiv:2402.09277, 2024 - arxiv.org
Medical imaging is nowadays a pillar in diagnostics and therapeutic follow-up. Current
research tries to integrate established-but ionizing-tomographic techniques with …
research tries to integrate established-but ionizing-tomographic techniques with …
Micro-CT guided deep neural network for 3D reconstructions in widefield diffuse optical tomography
Reconstructions in 3D widefield Diffuse Optical Tomography (DOT) suffer from poor spatial
resolution. Therefore, widefield DOT techniques benefit from incorporating structural priors …
resolution. Therefore, widefield DOT techniques benefit from incorporating structural priors …
A self-supervised learning approach for high-resolution diffuse optical tomography using neural fields
Diffuse optical tomography (DOT) has shown promise in biomedical research, such as
breast cancer diagnostics and brain imaging, by reconstructing hidden objects within …
breast cancer diagnostics and brain imaging, by reconstructing hidden objects within …
[HTML][HTML] Tutorial on the use of deep learning in diffuse optical tomography
GM Balasubramaniam, B Wiesel, N Biton, R Kumar… - Electronics, 2022 - mdpi.com
Diffuse optical tomography using deep learning is an emerging technology that has found
impressive medical diagnostic applications. However, creating an optical imaging system …
impressive medical diagnostic applications. However, creating an optical imaging system …
Unrolled-DOT: an interpretable deep network for diffuse optical tomography
Significance Imaging through scattering media is critical in many biomedical imaging
applications, such as breast tumor detection and functional neuroimaging. Time-of-flight …
applications, such as breast tumor detection and functional neuroimaging. Time-of-flight …
Convolutional deep network for light propagation in heterogeneous bio-tissues
X Fang, T Li - Optical Interactions with Tissue and Cells XXX, 2019 - spiedigitallibrary.org
To calculate the light propagation through heterogeneous bio-tissues, we propose a
convolutional deep network with specified convolutional kernels and calculation rules. The …
convolutional deep network with specified convolutional kernels and calculation rules. The …
Multitask deep learning reconstruction and localization of lesions in limited angle diffuse optical tomography
Diffuse optical tomography (DOT) leverages near-infrared light propagation through tissue to
assess its optical properties and identify abnormalities. DOT image reconstruction is an ill …
assess its optical properties and identify abnormalities. DOT image reconstruction is an ill …