Evidence map›Paper›PMID 39199722›Full record

ArticleBioengineering (Basel, Switzerland)2024

An Innovative Thermal Imaging Prototype for Precise Breast Cancer Detection: Integrating Compression Techniques and Classification Methods.

Khaled S Ahmed, Fayroz F Sherif, Mohamed S Abdallah, Young-Im Cho, Shereen M ElMetwally

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 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

5 authors.

Khaled S AhmedBio-Medical Department, Benha University, Benha 13518, Egypt.ORCID 0000-0002-5696-2263
Fayroz F SherifComputers and Systems Department, Electronics Research Institute (ERI), Cairo 11843, Egypt.ORCID 0000-0002-5543-0978
Mohamed S AbdallahInformatics Department, Electronics Research Institute (ERI), Cairo 11843, Egypt.ORCID 0000-0001-7351-625X
Young-Im ChoDepartment of Computer Engineering, Gachon University, Seongnam 13415, Republic of Korea.ORCID 0000-0003-0184-7599
Shereen M ElMetwallySystems and Biomedical Engineering Department, Cairo University, Giza 12613, Egypt.ORCID 0009-0003-4956-2020

Funding

Gachon University 1415181629(20022340
6 · The paper itself

Abstract

Breast cancer detection at an early stage is crucial for improving patient survival rates. This work introduces an innovative thermal imaging prototype that incorporates compression techniques inspired by mammography equipment. The prototype offers a radiation-free and precise cancer diagnosis. By integrating compression and illumination methods, thermal picture quality has increased, and the accuracy of classification has improved. Essential components of the suggested thermography device include an equipment body, plates, motors, pressure sensors, light sources, and a thermal camera. We created a 3D model of the gadget using the SolidWorks software 2020 package. Furthermore, the classification research employed both cancer and normal images from the experimental results to validate the efficacy of the suggested system. We employed preprocessing and segmentation methods on the obtained dataset. We successfully categorized the thermal pictures using various classifiers and examined their performance. The logistic regression model showed excellent performance, achieving an accuracy of 0.976, F1 score of 0.977, precision of 1.000, and recall of 0.995. This indicates a high level of accuracy in correctly classifying thermal abnormalities associated with breast cancer. The proposed prototype serves as a highly effective tool for conducting initial investigations into breast cancer detection, offering potential advancements in early-stage diagnosis, and improving patient survival rates.

Indexed as

breast cancer detectionclassificationthermal imagingthermography device

Identifiers

PMID39199722
PMCPMC11352007

What OpenQuestion holds

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Registered trials

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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.