[HTML][HTML] Deep learning for chest X-ray analysis: A survey

E Çallı, E Sogancioglu, B van Ginneken… - Medical Image …, 2021 - Elsevier
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 …

[HTML][HTML] Automatic captioning for medical imaging (MIC): a rapid review of literature

DR Beddiar, M Oussalah, T Seppänen - Artificial intelligence review, 2023 - Springer
Automatically understanding the content of medical images and delivering accurate
descriptions is an emerging field of artificial intelligence that combines skills in both …

Contrastive attention for automatic chest x-ray report generation

F Liu, C Yin, X Wu, S Ge, Y Zou, P Zhang… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

Aligntransformer: Hierarchical alignment of visual regions and disease tags for medical report generation

D You, F Liu, S Ge, X Xie, J Zhang, X Wu - … 1, 2021, Proceedings, Part III 24, 2021 - Springer
Recently, medical report generation, which aims to automatically generate a long and
coherent descriptive paragraph of a given medical image, has received growing research …

[HTML][HTML] Automated radiology report generation using conditioned transformers

O Alfarghaly, R Khaled, A Elkorany, M Helal… - Informatics in Medicine …, 2021 - Elsevier
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 …

[HTML][HTML] Medical image captioning via generative pretrained transformers

A Selivanov, OY Rogov, D Chesakov, A Shelmanov… - Scientific Reports, 2023 - nature.com
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 …

[HTML][HTML] Radiology report generation with a learned knowledge base and multi-modal alignment

S Yang, X Wu, S Ge, Z Zheng, SK Zhou, L Xiao - Medical Image Analysis, 2023 - Elsevier
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 …

Ratchet: Medical transformer for chest x-ray diagnosis and reporting

B Hou, G Kaissis, RM Summers, B Kainz - Medical Image Computing and …, 2021 - Springer
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 …

Deep image captioning: A review of methods, trends and future challenges

L Xu, Q Tang, J Lv, B Zheng, X Zeng, W Li - Neurocomputing, 2023 - Elsevier
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 …

DeltaNet: Conditional medical report generation for COVID-19 diagnosis

X Wu, S Yang, Z Qiu, S Ge, Y Yan, X Wu… - arXiv preprint arXiv …, 2022 - arxiv.org
Fast screening and diagnosis are critical in COVID-19 patient treatment. In addition to the
gold standard RT-PCR, radiological imaging like X-ray and CT also works as an important …