Abstract
AbstractAutomatically understanding the content of medical images and delivering accurate descriptions is an emerging field of artificial intelligence that combines skills in both computer vision and natural language processing fields. Medical image captioning is involved in various applications related to diagnosis, treatment, report generation and computer-aided diagnosis to facilitate the decision making and clinical workflows. Unlike generic image captioning, medical image captioning highlights the relationships between image objects and clinical findings, which makes it a very challenging task. Although few review papers have already been published in this field, their coverage is still quite limited and only particular problems are addressed. This motivates the current paper where a rapid review protocol was adopted to review the latest achievements in automatic medical image captioning from the medical domain perspective. We aim through this review to provide the reader with an up-to-date literature in this field by summarizing the key findings and approaches in this field, including the related datasets, applications and limitations as well as highlighting the main competitions, challenges and future directions.
Funder
Academy of Finland Profi5 DigiHealth project
European Young-sters Resilience through Serious Games
University of Oulu including Oulu University Hospital
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics
Reference111 articles.
1. Al-Dhabyani W, Gomaa M, Khaled H et al (2020) Dataset of breast ultrasound images. Data Brief 28(104):863
2. Allaouzi I, Ben Ahmed M, Benamrou B et al (2018) Automatic caption generation for medical images. In: Proceedings of the 3rd international conference on smart city applications (SCA’18)
3. Alsharid M, El-Bouri R, Sharma H et al (2020) A curriculum learning based approach to captioning ultrasound images. In: Medical ultrasound, and preterm, perinatal and paediatric image analysis 12437
4. Alsharid M, Sharma H, Drukker L et al (2019) Captioning ultrasound images automatically. In: Medical image computing and computer-assisted intervention: MICCAI and international conference on medical image computing and computer-assisted intervention 22
5. Ambati R, Reddy Dudyala C (2018) A sequence-to-sequence model approach for imageclef 2018 medical domain visual question answering. In: 15th IEEE India council international conference, INDICON 2018 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082568963&doi=10.1109%2fINDICON45594.2018.8987108&partnerID=40&md5=4d51ca7d51f6ee653a37a36515c85a8b
Cited by
27 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献