ArticleApplied optics2017
Diffuse optical localization of blood vessels and 3D printing for guiding oral surgery.
Article in Applied optics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 14 citations in OpenAlex.
- Localization of Fluorescent Targets in Deep Tissue With Expanded Beam Illumination for Studies of Cancer and the Brain.IEEE transactions on medical imaging · 2020Article
- Multiresolution Localization with Temporal Scanning for Super-Resolution Diffuse Optical Imaging of Fluorescence.IEEE transactions on image processing : a publication of the IEEE Signal Processing Society · 2019Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Diffuse optical imaging through centimeters of tissue has emerged as a powerful tool in biomedical research. However, applications in the operating theater have been limited in part due to data set requirements and computational burden. We present an approach that uses a small number of optical source-detector pairs that allows for the fast localization of arteries in the roof of the mouth and has the potential to reduce complications during oral surgery. The arteries are modeled as multiple-point absorbers, allowing localization of their complex shapes. The method is demonstrated using a printed tissue-simulating mouth phantom. Furthermore, we use the extracted position information to fabricate a custom surgical guide using 3D printing that could protect the arteries during surgery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.