Evidence map›Paper›PMID 41003351›Full record

ArticleJournal of imaging2025

Compton Camera X-Ray Fluorescence Imaging Design and Image Reconstruction Algorithm Optimization.

Shunmei Lu, Kexin Peng, Peng Feng, Cheng Lin, Qingqing Geng, Junrui Zhang

Abstract read
In one paragraph

Article in Journal of imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Shunmei LuCollege of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China.
Kexin PengCollege of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China.ORCID 0009-0004-8443-0290
Peng FengThe Key Laboratory of Optoelectronic Technology and Systems, Ministry of Education, Chongqing University, Chongqing 400044, China.ORCID 0000-0002-7420-2161
Cheng LinCollege of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China.
Qingqing GengCollege of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China.
Junrui ZhangCollege of Nuclear Technology and Automation Engineering, Chengdu University of Technology, Chengdu 610059, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional X-ray fluorescence computed tomography (XFCT) suffers from issues such as low photon collection efficiency, slow data acquisition, severe noise interference, and poor imaging quality due to the limitations of mechanical collimation. This study proposes to design an X-ray fluorescence imaging system based on bilateral Compton cameras and to develop an optimized reconstruction algorithm to achieve high-quality 2D/3D imaging of low-concentration samples (0.2% gold nanoparticles). A system equipped with bilateral Compton cameras was designed, replacing mechanical collimation with "electronic collimation". The traditional LM-MLEM algorithm was optimized through improvements in data preprocessing, system matrix construction, iterative processes, and post-processing, integrating methods such as Total Variation (TV) regularization (anisotropic TV included), filtering, wavelet-domain constraints, and isosurface rendering. Successful 2D and 3D reconstruction of 0.2% gold nanoparticles was achieved. Compared with traditional algorithms, improvements were observed in convergence, stability, speed, quality, and accuracy. The system exhibited high detection efficiency, angular resolution, and energy resolution. The Compton camera-based XFCT overcomes the limitations of traditional methods; the optimized algorithm enables low-noise imaging at ultra-low concentrations and has potential applications in early cancer diagnosis and material analysis.

Indexed as

Compton cameraimage reconstructionMLEMthree-dimensional reconstructionX-ray fluorescence

Identifiers

PMID41003351
PMCPMC12470824

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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.