Every year physicians face an increasing demand of image-based diagnosis from patients, a
problem that can be addressed with recent artificial intelligence methods. In this context, we …

The automatic generation of radiology reports has the potential to assist radiologists in the
time-consuming task of report writing. Existing methods generate the full report from image …

Automatically generating radiology reports can improve current clinical practice in diagnostic
radiology. On one hand, it can relieve radiologists from the heavy burden of report writing; …

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 …

Medical imaging plays a significant role in clinical practice of medical diagnosis, where the
text reports of the images are essential in understanding them and facilitating later …

Radiology report generation (RRG) aims to automatically generate free-text descriptions
from clinical radiographs, eg, chest X-Ray images. RRG plays an essential role in promoting …

The limited availability of annotated data often hinders real-world applications of machine
learning. To efficiently learn from small quantities of multimodal data, we leverage the …

Medical report generation task, which targets to produce long and coherent descriptions of
medical images, has attracted growing research interests recently. Different from the general …

Medical report generation, which aims to automatically generate a long and coherent report
of a given medical image, has been receiving growing research interests. Existing …

Recently, chest X-ray report generation, which aims to automatically generate descriptions
of given chest X-ray images, has received growing research interests. The key challenge of …