Progressive Transformer-Based Generation of Radiology Reports
Inspired by Curriculum Learning, we propose a consecutive (i.e., image-to-text-to-text) generation framework where we divide the problem of radiology report generation into two steps. Contrary to generating the full radiology report from the image at once, the model generates global concepts from the image in the first step and then reforms them into finer and coherent texts using a transformer architecture. We follow the transformer-based sequence-to-sequence paradigm at each step. We improve upon the state-of-the-art on two benchmark datasets.
Code (1)
Tasks
Image to textText GenerationSimilar Papers 제목 키워드 기반
Generating Radiology Reports via Memory-driven Transformer
Medical imaging is frequently used in clinical practice and trials for diagnosis and treatment. Writing imaging reports is time-consuming and can be error-prone for inexperienced radiologists. Therefore, automatically ge…
DecoderText GenerationLearning to Generate Clinically Coherent Chest X-Ray Reports
Automated radiology report generation has the potential to reduce the time clinicians spend manually reviewing radiographs and streamline clinical care. However, past work has shown that typical abstractive methods tend …
Text GenerationVision-Language Models for Automated Chest X-ray Interpretation: Leveraging ViT and GPT-2
Radiology plays a pivotal role in modern medicine due to its non-invasive diagnostic capabilities. However, the manual generation of unstructured medical reports is time consuming and prone to errors. It creates a signif…
DiagnosticPrior-RadGraphFormer: A Prior-Knowledge-Enhanced Transformer for Generating Radiology Graphs from X-Rays
The extraction of structured clinical information from free-text radiology reports in the form of radiology graphs has been demonstrated to be a valuable approach for evaluating the clinical correctness of report-generat…
Decision MakingMedical Image AnalysisMulti-Label ClassificationMUlTI-LABEL-ClASSIFICATION+1Clinical Context-aware Radiology Report Generation from Medical Images using Transformers
Recent developments in the field of Natural Language Processing, especially language models such as the transformer have brought state-of-the-art results in language understanding and language generation. In this work, w…
DecoderDiagnosticText Generation