Deep learning based image reconstruction for sparse-view diffuse optical tomography
MH Jalalimanesh, MA Ansari - Waves in Random and Complex …, 2021 - Taylor & Francis
Three critical problems, including high-cost instrumentations, time-consuming image
recovery, and low image quality, limit clinical applications of diffuse optical tomography …
recovery, and low image quality, limit clinical applications of diffuse optical tomography …
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 …
The pain and gain of DC-based diffuse optical tomography reconstruction—New insights into an old-like problem
For diffuse optical tomography reconstruction, DC-based method outperforms frequency-
domain method in background artifacts, at the known cost of increased coupling between …
domain method in background artifacts, at the known cost of increased coupling between …
Towards real-time functional human brain imaging with diffuse optical tomography
A framework for efficient formulation of the inverse model in diffuse optical tomography,
incorporating parallel computing is proposed. Based on 24 subjects, a tenfold speed …
incorporating parallel computing is proposed. Based on 24 subjects, a tenfold speed …
Solving heterogenous region for diffuse optical tomography with a convolutional forward calculation model and the inverse neural network
X Fang, C Gao, Y Li, T Li - Advanced Optical Imaging …, 2020 - spiedigitallibrary.org
Diffuse optical tomography (DOT) is a noninvasive biomedical imaging method to
reconstruct optical property distribution. Since the underdetermined characteristic of …
reconstruct optical property distribution. Since the underdetermined characteristic of …
Quantitative diffuse optical tomography using a mobile phone camera and automatic 3D photo stitching
Q Fang - Biomedical Optics, 2012 - opg.optica.org
We show proof-of-concept for using an ultra-portable mobile-phone-based imaging system
for quantitative 3D diffuse optical tomography. Phantom images were successfully recovered …
for quantitative 3D diffuse optical tomography. Phantom images were successfully recovered …
Monte Carlo-based data generation for efficient deep learning reconstruction of macroscopic diffuse optical tomography and topography applications
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 …
data to the image domain directly. However, DL methodologies are data-driven and require …
High resolution, deep imaging using confocal time-of-flight diffuse optical tomography
Light scattering by tissue severely limits how deep beneath the surface one can image, and
the spatial resolution one can obtain from these images. Diffuse optical tomography (DOT) is …
the spatial resolution one can obtain from these images. Diffuse optical tomography (DOT) is …
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 …
Spatial resolution in depth for time-resolved diffuse optical tomography using short source-detector separations
Diffuse optical tomography for medical applications can require probes with small
dimensions involving short source-detector separations. Even though this configuration is …
dimensions involving short source-detector separations. Even though this configuration is …