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Found 6 papers, 2 papers with code
DeltaNet: Conditional Medical Report Generation for COVID-19 Diagnosis
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
DeltaNet:Conditional Medical Report Generation for COVID-19 Diagnosis
To reduce the workload of radiologists, we propose DeltaNet to generate medical reports automatically.
Universal Segmentation of 33 Anatomies
Firstly, while it is ideal to learn such a model from a large-scale, fully-annotated dataset, it is practically hard to curate such a dataset.
Radiology Report Generation with a Learned Knowledge Base and Multi-modal Alignment
In clinics, a radiology report is crucial for guiding a patient's treatment.
Knowledge Matters: Radiology Report Generation with General and Specific Knowledge
In this paper, we propose a knowledge-enhanced radiology report generation approach introduces two types of medical knowledge: 1) General knowledge, which is input independent and provides the broad knowledge for report generation; 2) Specific knowledge, which is input dependent and provides the fine-grained knowledge for report generation.
CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography
Spine-related diseases have high morbidity and cause a huge burden of social cost.
