Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks
| dc.centro | E.T.S.I. Informática | es_ES |
| dc.contributor.author | Palomo-Ferrer, Esteban José | |
| dc.contributor.author | Zafra-Santisteban, Miguel A. | |
| dc.contributor.author | Luque-Baena, Rafael Marcos | |
| dc.date.accessioned | 2022-11-10T11:21:20Z | |
| dc.date.available | 2022-11-10T11:21:20Z | |
| dc.date.created | 2022 | |
| dc.date.issued | 2022 | |
| dc.departamento | Lenguajes y Ciencias de la Computación | |
| dc.description.abstract | Pneumonia is an infectious and deadly disease which strikes over millions of people. Usually, chest X-rays are used by radiotherapist to diagnose pneumonia. In this paper, a Computer- Aided Diagnosis (CAD) system for pneumonia detection in chest X-ray images is proposed. This system is based on Convolutional Neural Networks (CNNs) which are able to classify the image into two classes (pneumonia or normal). Experimental results show that the proposed system obtained an accuracy rate of 98.59%. | es_ES |
| dc.description.sponsorship | Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. | es_ES |
| dc.identifier.uri | https://hdl.handle.net/10630/25393 | |
| dc.language.iso | eng | es_ES |
| dc.relation.eventdate | 26/10/2022 | es_ES |
| dc.relation.eventplace | Roma, Italia | es_ES |
| dc.relation.eventtitle | 2022 IEEE INTERNATIONAL CONFERENCE ON METROLOGY FOR EXTENDED REALITY, ARTIFICIAL INTELLIGENCE AND NEURAL ENGINEERING | es_ES |
| dc.rights.accessRights | open access | es_ES |
| dc.subject | Inteligencia artificial | es_ES |
| dc.subject | Redes neuronales (Informática) | es_ES |
| dc.subject | Tórax - Radiografía | es_ES |
| dc.subject | Neumonía | es_ES |
| dc.subject.other | pneumonia detection | es_ES |
| dc.subject.other | chest X-ray images | es_ES |
| dc.subject.other | convolutional neural networks | es_ES |
| dc.subject.other | computer-aided diagnosis | es_ES |
| dc.title | Pneumonia Detection in Chest X-ray Images using Convolutional Neural Networks | es_ES |
| dc.type | conference output | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | ee7a0035-e256-42bb-ac83-bc46a618cd04 | |
| relation.isAuthorOfPublication | 15881531-a431-477b-80d6-532058d8377c | |
| relation.isAuthorOfPublication.latestForDiscovery | ee7a0035-e256-42bb-ac83-bc46a618cd04 |
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