An Exploratory Study of Multimodality in Medical Imaging and Natural Language Processing
Purpose/Significance Achieving automatic generation of medical imaging reports is important for reducing the workload of radiologists and promoting the standardization of clinical workflow.Method/Process Focusing on finding the chest report generation mod-els with open source code in recent years,the paper develops an automatic medical image report generation method based on the CDGPT2 model.Result/Conclusion The advantages of the model in report generation are still to be explored,the quality of reports generated after modifications to the decoder inputs of the model is not high.Future research could improve the performance of the model by using large datasets and incorporating more clinical information.
chest radiographmultimodalautomatic report generationattention mechanismnatural language processing
万方数据
维普
