Chest X-ray Image Based Report Generation Using Deep Learning

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.

Chest X-ray (CXR), Deep Learning, Convolutional Neural, Network (CNN),, Radiology, Automated Report Generation, Medical Imaging, Image Analysis, Artificial Intelligence (AI), Neural Networks, Computer-Aided Diagnosis (CAD)

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