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GitHub topics: diffuse-optical-tomography

rbd079/multiparameter_DOT_dataset

Simulated frequency-domain diffuse optical tomography dataset

Size: 538 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

yyiz/Unrolled-DOT

Official Implementation for Unrolled-DOT: an unrolled network for solving (time-of-flight) diffuse optical tomography inverse problems.

Language: Jupyter Notebook - Size: 736 KB - Last synced at: 8 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 1

sfu-mial/DOTNet

Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.

Language: Python - Size: 26 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

haneneby/DOTNet

Addresses the problem of reconstructing images acquired by diffuse optical tomography using deep learning.

Language: Python - Size: 26 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

sfu-mial/MultiNet

Repository for our deep multitask paper in DOT imaging.

Language: Python - Size: 25.5 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 1 - Forks: 0

haneneby/LADOTNet

Repository for our limited angle deep learning based DOT image reconstruction.

Language: Python - Size: 24.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

haneneby/MultiNet

Repository for our deep multitask paper in DOT imaging.

Language: Python - Size: 25.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

sfu-mial/LADOTNet

Repository for our limited angle deep learning based DOT image reconstruction

Language: Python - Size: 24.4 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

sfu-mial/FuseNet

Repository for our deep multi-frequency fusion paper in DOT imaging.

Language: Python - Size: 30.7 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 1 - Forks: 0

wanying4/Steepest-Descent-Method-and-DOT-Imaging

Diffuse Optical Tomography (DOT) is an non-invasive optical imaging technique that measures the optical properties of physiological tissue using near infrared spectrum light. Optical properties are extracted from the measurement using reconstruction algorithm. This project uses the steepest descent method for reconstruction of optical data.

Language: MATLAB - Size: 1.04 MB - Last synced at: over 1 year ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

ez77/Diffuse-Optical-Tomography

Simulation of the detection of a perturbation in homogeneous media via diffuse optical tomography.

Language: Jupyter Notebook - Size: 1.68 MB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 3 - Forks: 0