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 …
Deep learning based image reconstruction for diffuse optical tomography
Diffuse optical tomography (DOT) is a relatively new imaging modality that has
demonstrated its clinical potential of probing tumors in a non-invasive and affordable way …
demonstrated its clinical potential of probing tumors in a non-invasive and affordable way …
A learned-SVD approach for regularization in diffuse optical tomography
A Benfenati, G Bisazza, P Causin - arXiv preprint arXiv:2111.13401, 2021 - arxiv.org
Diffuse Optical Tomography (DOT) is an emerging technology in medical imaging which
employs light in the NIR spectrum to estimate the distribution of optical coefficients in …
employs light in the NIR spectrum to estimate the distribution of optical coefficients in …
Limited-angle diffuse optical tomography image reconstruction using deep learning
Diffuse optical tomography (DOT) leverages near-infrared light propagation through in vivo
tissue to assess its optical properties and identify abnormalities such as cancerous lesions …
tissue to assess its optical properties and identify abnormalities such as cancerous lesions …
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 …
A model-based iterative learning approach for diffuse optical tomography
Diffuse optical tomography (DOT) utilises near-infrared light for imaging spatially distributed
optical parameters, typically the absorption and scattering coefficients. The image …
optical parameters, typically the absorption and scattering coefficients. The image …
[PDF][PDF] A Learned SVD approach for Inverse Problem Regularization in Diffuse Optical Tomography
A Benfenati, G Bisazza, P Causin - arXiv preprint arXiv:2111.13401, 2021 - academia.edu
Abstract Diffuse Optical Tomography (DOT) is an emerging technology in medical imaging
which employs near–infra–red light to estimate the distribution of optical coefficients in …
which employs near–infra–red light to estimate the distribution of optical coefficients in …
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 …
Diffusion equation engine deep learning for diffuse optical tomography
C Wei, Z Li, Z Sun, K Jia, J Feng - … Biomedical Imaging XVII, 2022 - spiedigitallibrary.org
Diffuse optical tomography (DOT) is a promising non-invasive optical imaging technique that
can provide functional information of biological tissues. Since diffuse light undergoes …
can provide functional information of biological tissues. Since diffuse light undergoes …
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 …