Evidence map›Paper›PMID 35669543›Full record

ArticleHeliyon2022

Automatic computation of bone defective volume from tomographic images.

M Ezzahmouly, A Essakhi, A El Ouahli, H El Byad, M Ed-Dhahraouy, S Hakim, E Gourri, A ELmoutaouakkil, Z Hatim

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Article in Heliyon, 2022. 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

9 authors.

M EzzahmoulyResearch Laboratory in Optimization, Emerging Systems, Networks and Imaging, LAROSERI, Computer Science Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
A EssakhiLaboratory of Renewable Energy and Systems Dynamics, Faculty of Sciences Ain Chok, Casablanca, Morocco.
A El OuahliEnergy, Materials and Environment Team, Chemistry Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
H El ByadResearch Laboratory in Optimization, Emerging Systems, Networks and Imaging, LAROSERI, Computer Science Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
M Ed-DhahraouyResearch Laboratory in Optimization, Emerging Systems, Networks and Imaging, LAROSERI, Computer Science Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
S HakimResearch Laboratory in Optimization, Emerging Systems, Networks and Imaging, LAROSERI, Computer Science Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
E GourriEnergy, Materials and Environment Team, Chemistry Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
A ELmoutaouakkilResearch Laboratory in Optimization, Emerging Systems, Networks and Imaging, LAROSERI, Computer Science Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.
Z HatimEnergy, Materials and Environment Team, Chemistry Department, Faculty of Sciences, University Chouaib Doukkali, El Jadida, Morocco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the most difficult aims of modern biomaterial science is predicting the shape and volume of a bone defect and adjusting the implementation of a bone substitute. Prior to implantation, practitioners must carefully identify the architecture and volume of the defective bone to be filled. This information is often accessed via imaging techniques. The defective bone is frequently confused with its surroundings and the image background. The use of conventional segmentation for the selection and isolation of the cavity to be filled proves to be difficult. In this work, a defect in a dead bone is created and then imaged with the microtomography technique (343 cuts generated). The goal is to separate the defect's shape and volume from both the bone and the background image. An adaptive morphological operation technique was employed to complete these tasks. The proposed method allows for exact segmentation and calculation of the volume of the cavity to be filled. Using several calculated phantoms, the approach is subjectively and quantitatively evaluated: Compared to the high error value of the conventional method, the error value of the proposed one has no bearing on the overall data. The method's accuracy was also confirmed by comparing the calculated volume of the bone defect (0.91 cm

Indexed as

Biomaterial cementBone defectMicrotomographyMorphological operationSegmentation

Identifiers

PMID35669543
PMCPMC9163512

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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.