Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Automatically understanding the content of medical images and delivering accurate
descriptions is an emerging field of artificial intelligence that combines skills in both …

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 …

Recently, medical report generation, which aims to automatically generate a long and
coherent descriptive paragraph of a given medical image, has received growing research …

Radiology report writing in hospitals is a time-consuming task that also requires experience
from the involved radiologists. This paper proposes a deep learning model to automatically …

The proposed model for automatic clinical image caption generation combines the analysis
of radiological scans with structured patient information from the textual records. It uses two …

In clinics, a radiology report is crucial for guiding a patient's treatment. However, writing
radiology reports is a heavy burden for radiologists. To this end, we present an automatic …

Chest radiographs are one of the most common diagnostic modalities in clinical routine. It
can be done cheaply, requires minimal equipment, and the image can be diagnosed by …

Abstract Natural Image Captioning (NIC) is an interdisciplinary research area that lies within
the intersection of Computer Vision (CV) and Natural Language Processing (NLP). Several …

Image captioning, also called report generation in medical field, aims to describe visual
content of images in human language, which requires to model semantic relationship …