Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 7
2220-2224,2230

Window optimization technology of CT images for automatic liver and tumor segmentation

Rong Mengling
Wang Chaoli
Sun Zhanquan
College of Optoelectronic Information & Computer Engineering, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0261

Abstract

Remapping the pixel intensity range of the high data depth computed tomography(CT) image to an observable range for window technology will lose image information, and the method of automatic segmentation after only one preprocessing of CT images is not well adapted to the tumor segmentation. This paper presented a two-step optimized intensity windowing preprocessing method for segmented CT values. It used the histogram of CT value and window technology of liver and its tumors to preprocess the original and liver image respectively, improved the contrast of the area of interest. Compared the automatic segmentation accuracy of liver and tumor with different intensity windows in the cascaded convolutional neural network(CNN), obtained the optimal CT range of liver and tumor, which were [-40, 190] HU and [-25, 145] HU, respectively. This method was tested on the 3DIRCADb dataset with three mainstream segmentation networks, UNet, ResNet, and FCN. It proves that the influence of different CT value ranges on liver segmentation accuracy can reach 6.75%, and the segmentation accuracy of different networks can be improved by about 2%.

Foundation Support

上海市自然科学基金资助项目(19ZR1436000)
国防基础研究项目(JCKY2019413D001)
国家自然科学基金资助项目(61374040)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0261
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 7
Section: Technology of Graphic & Image
Pages: 2220-2224,2230
Serial Number: 1001-3695(2021)07-057-2220-05

Publish History

[2021-07-05] Printed Article

Cite This Article

荣梦玲, 王朝立, 孙占全. 基于窗口优化技术的肝和肿瘤CT图像的自动分割 [J]. 计算机应用研究, 2021, 38 (7): 2220-2224,2230. (Rong Mengling, Wang Chaoli, Sun Zhanquan. Window optimization technology of CT images for automatic liver and tumor segmentation [J]. Application Research of Computers, 2021, 38 (7): 2220-2224,2230. )

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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