Chest X-ray Image Based Report Generation Using Deep Learning

Mr. N. Samba Siva Rao and Dr. J. Suresh Babu
Additional contact information
Mr. N. Samba Siva Rao: PG Scholar, Department of MCA, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India
Dr. J. Suresh Babu: PG Scholar, Department of MCA, Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College (Autonomous), Tirupati, Andhra Pradesh, India

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 4, 501-506

Abstract: The diagnostic procedure of Chest X-ray (CXR) relies on subjective manual report generation which takes an excessive amount of time. The combination of CNNs for feature extraction together with NLP for text generation through deep learning techniques demonstrates effective potential in solving this problem. The automated report generation allows the radiological report process to become more efficient and maintain higher consistent standards. Integration of NLP and CNNs in the system enables image analysis through CXR images which results in the production of thorough and reliable radiological reports. The automated system provides both fast reporting capabilities with enhanced detection precision and improved treatment services. Deep learning used for CXR image-based report generation represents a transformative opportunity for radiology which produces more effective diagnostics while benefiting both medical professionals and their patient subjects.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue4/501-506.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-4/501-506.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:4:p:501-506

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().