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 …
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 …
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 …
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 …
Interpretable model-driven projected gradient descent network for high-quality fDOT reconstruction
Y Hua, Y Jiang, K Liu, Q Luo, Y Deng - Optics Letters, 2022 - opg.optica.org
In fluorescence diffuse optical tomography (fDOT), the quality of reconstruction is severely
limited by mismodeling and ill-posedness of inverse problems. Although data-driven deep …
limited by mismodeling and ill-posedness of inverse problems. Although data-driven deep …
Deep background-mismodeling-learned reconstruction for high-accuracy fluorescence diffuse optical tomography
Y Jiang, K Liu, W Li, Q Luo, Y Deng - Optics Letters, 2023 - opg.optica.org
We present a deep background-mismodeling-learned reconstruction framework for high-
accuracy fluorescence diffuse optical tomography (FDOT). A learnable regularizer …
accuracy fluorescence diffuse optical tomography (FDOT). A learnable regularizer …
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 …
Deep learning-enabled high-speed, multi-parameter diffuse optical tomography
R Dale, B Zheng, F Orihuela-Espina… - Journal of …, 2024 - spiedigitallibrary.org
Significance Frequency-domain diffuse optical tomography (FD-DOT) could enhance clinical
breast tumor characterization. However, conventional diffuse optical tomography (DOT) …
breast tumor characterization. However, conventional diffuse optical tomography (DOT) …
SIMBA: Scalable inversion in optical tomography using deep denoising priors
Two features desired in a three-dimensional (3D) optical tomographic image reconstruction
algorithm are the ability to reduce imaging artifacts and to do fast processing of large data …
algorithm are the ability to reduce imaging artifacts and to do fast processing of large data …
Regression-based neural network for improving image reconstruction in diffuse optical tomography
GM Balasubramaniam, S Arnon - Biomedical Optics Express, 2022 - opg.optica.org
Diffuse optical tomography (DOT) is a non-invasive imaging technique utilizing multi-
scattered light at visible and infrared wavelengths to detect anomalies in tissues. However …
scattered light at visible and infrared wavelengths to detect anomalies in tissues. However …