A novel framework for three-dimensional electrical impedance tomography reconstruction of maize ear via feature reconfiguration and residual networks.

Hai-Ying Zheng, Yang Li, Nan Wang, Yang Xiang, Jin-Hang Liu, Liu-Deng Zhang, Lan Huang, Zhong-Yi Wang

Abstract read

In one paragraph

Article in PeerJ. Computer science, 2024. 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

–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

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

8 authors.

Hai-Ying ZhengCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.ORCID 0000-0001-5014-4799

Yang LiCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Nan WangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Yang XiangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Jin-Hang LiuCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Liu-Deng ZhangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Lan HuangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Zhong-Yi WangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrical impedance tomography (EIT) provides an indirect measure of the physiological state and growth of the maize ear by reconstructing the distribution of electrical impedance. However, the two-dimensional (2D) EIT within the electrode plane finds it challenging to comprehensively represent the spatial distribution of conductivity of the intact maize ear, including the husk, kernels, and cob. Therefore, an effective method for 3D conductivity reconstruction is necessary. In practical applications, fluctuations in the contact impedance of the maize ear occur, particularly with the increase in the number of grids and computational workload during the reconstruction of 3D spatial conductivity. These fluctuations may accentuate the ill-conditioning and nonlinearity of the EIT. To address these challenges, we introduce RFNetEIT, a novel computational framework specifically tailored for the absolute imaging of the three-dimensional electrical impedance of maize ear. This strategy transforms the reconstruction of 3D electrical conductivity into a regression process. Initially, a feature map is extracted from measured boundary voltage

Indexed as

3D conductivity distributionElectrical impedance tomography (EIT)Feature reconfigurationMaize earResidual networks

Identifiers

PMID38660147

DOI10.7717/peerj-cs.1944

PMCPMC11042020

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

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.