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 …
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 …
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 …
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 …
Machine learning model with physical constraints for diffuse optical tomography
A machine learning model with physical constraints (ML-PC) is introduced to perform diffuse
optical tomography (DOT) reconstruction. DOT reconstruction is an ill-posed and under …
optical tomography (DOT) reconstruction. DOT reconstruction is an ill-posed and under …
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 …
Difference imaging from single measurements in diffuse optical tomography: a deep learning approach
Significance:“Difference imaging,” which reconstructs target optical properties using
measurements with and without target information, is often used in diffuse optical …
measurements with and without target information, is often used in diffuse optical …
Deep learning-based fusion of widefield diffuse optical tomography and micro-CT structural priors for accurate 3D reconstructions
Widefield illumination and detection strategies leveraging structured light have enabled fast
and robust probing of tissue properties over large surface areas and volumes. However …
and robust probing of tissue properties over large surface areas and volumes. However …
FDU-net: deep learning-based three-dimensional diffuse optical image reconstruction
Near-infrared diffuse optical tomography (DOT) is a promising functional modality for breast
cancer imaging; however, the clinical translation of DOT is hampered by technical …
cancer imaging; however, the clinical translation of DOT is hampered by technical …