dorsal/arxiv
View Schema3D Reconstruction Using Optical Images
| Authors | Edward N. Tsyganov, Pietro P. Antich, Ralph P. Mason, Robert W. Parkey, Serguei Y. Seliounine, Nikolai V. Slavine, Alexander I. Zinchenko |
|---|---|
| Categories | |
| ArXiv ID | physics/0406148 |
| URL | https://arxiv.org/abs/physics/0406148 |
Abstract
Various imaging methods for small animals are rapidly gaining acceptance in biology and medical research. Optical imaging is a very fast and convenient method of biological interrogation, but suffers from significant disadvantages, such as the absence of 3D image reconstruction algorithms. This have up until now impeded progress to a quantitative stage. Here we propose a 3D reconstruction algorithm for imaging light emitted at depths in small living animals. We believe the methods discussed here are novel and lead to a novel imaging paradigm, which we call Light Emission Tomography.
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"date_created": "2026-03-02T18:00:49.528000Z",
"date_modified": "2026-03-02T18:00:49.528000Z",
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"abstract": "Various imaging methods for small animals are rapidly gaining acceptance in\nbiology and medical research. Optical imaging is a very fast and convenient\nmethod of biological interrogation, but suffers from significant disadvantages,\nsuch as the absence of 3D image reconstruction algorithms. This have up until\nnow impeded progress to a quantitative stage. Here we propose a 3D\nreconstruction algorithm for imaging light emitted at depths in small living\nanimals. We believe the methods discussed here are novel and lead to a novel\nimaging paradigm, which we call Light Emission Tomography.",
"arxiv_id": "physics/0406148",
"authors": [
"Edward N. Tsyganov",
"Pietro P. Antich",
"Ralph P. Mason",
"Robert W. Parkey",
"Serguei Y. Seliounine",
"Nikolai V. Slavine",
"Alexander I. Zinchenko"
],
"categories": [
"physics.med-ph",
"physics.bio-ph"
],
"title": "3D Reconstruction Using Optical Images",
"url": "https://arxiv.org/abs/physics/0406148"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "62de998c-a9c5-4b5c-b2b9-dff296903e0d",
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"variant": "snapshot-2026-03-01",
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