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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 8
2543-2548

Chest X-ray images and diagnostic reports for twin-towers cross-modal retrieval

Zhang Jiachenga
Ou Weihuaa,b
Chen Yingjieb
Zhang Wenchuanb
Xiong Jiahaob
a. School of Mathematical Sciences, b. School of Big Data & Computer Science, Guizhou Normal University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2022.12.0786

Abstract

In order to solve the problem that the existing cross-modal methods of chest X-ray images and diagnostic reports focus on global information alignment, which ignore the fine-grained semantic association between chest X-ray images and diagnostic reports, resulting in low retrieval accuracy and poor matching degree, this paper proposed a method named CDTCR(chest X-ray images and diagnostic reports for twin-towers cross-modal retrieval). Specifically, for fine-grained semantic representation, it proposed an image encoder composed of residual network to learn the fine-grained features of the image and a BERT model composed of Transformer to learn the fine-grained semantic features of the diagnostic report. In order to solve the problem of fine-grained semantic association, it also designed an information alignment strategy of two different granularity modes for the global image to sentence and local region to phrase, which solved the problem of insufficient fine-grained semantic association between different modes. The experimental results on a large-scale medical dataset MIMIC-CXR show that CDTCR has higher retrieval accuracy and better interpretation than the existing cross-modal retrieval methods.

Foundation Support

国家自然科学基金资助项目(62262005,61962010)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.12.0786
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 8
Section: Technology of Graphic & Image
Pages: 2543-2548
Serial Number: 1001-3695(2023)08-048-2543-06

Publish History

[2023-02-27] Accepted Paper
[2023-08-05] Printed Article

Cite This Article

张嘉诚, 欧卫华, 陈英杰, 等. 胸部X线影像和诊断报告的双塔跨模态检索 [J]. 计算机应用研究, 2023, 40 (8): 2543-2548. (Zhang Jiacheng, Ou Weihua, Chen Yingjie, et al. Chest X-ray images and diagnostic reports for twin-towers cross-modal retrieval [J]. Application Research of Computers, 2023, 40 (8): 2543-2548. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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