Evidence map›Paper›PMID 38594238›Full record

ArticleNature communications2024

Tetris-inspired detector with neural network for radiation mapping.

Ryotaro Okabe, Shangjie Xue, Jayson R Vavrek, Jiankai Yu, Ryan Pavlovsky, Victor Negut, Brian J Quiter, Joshua W Cates, Tongtong Liu, Benoit Forget and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Ryotaro Okabe *Quantum Measurement Group, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. rokabe@mit.edu.ORCID http://orcid.org/0000-0002-5095-5951
Shangjie Xue *Quantum Measurement Group, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Jayson R Vavrek *Applied Nuclear Physics Program, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Jiankai YuDepartment of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0001-8029-9847
Ryan PavlovskyApplied Nuclear Physics Program, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Victor NegutApplied Nuclear Physics Program, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Brian J QuiterApplied Nuclear Physics Program, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Joshua W CatesApplied Nuclear Physics Program, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA.
Tongtong LiuQuantum Measurement Group, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Benoit ForgetDepartment of Nuclear Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Stefanie JegelkaDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0002-6121-9474
Gordon KohseNuclear Reactor Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
Lin-Wen HuNuclear Reactor Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. lwhu@mit.edu.ORCID http://orcid.org/0000-0003-3126-2225
Mingda LiQuantum Measurement Group, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. mingda@mit.edu.ORCID http://orcid.org/0000-0002-7055-6368

Funding

U.S. Department of Energy (DOE) DE-AC02-05CH11231U.S. Department of Energy (DOE) DE-SC0021940
6 · The paper itself

Abstract

Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

Identifiers

PMID38594238
PMCPMC11004156

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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.