[1]刘元峰,刘立波,刘云.基于CT图像的颅内血肿检测与分割[J].中国医学物理学杂志,2021,38(9):1090-1096.[doi:10.3969/j.issn.1005-202X.2021.09.008]
　LIU Yuanfeng,LIU Libo,LIU Yun.Detection and segmentation of intracranial hematoma in CT image[J].Chinese Journal of Medical Physics,2021,38(9):1090-1096.[doi:10.3969/j.issn.1005-202X.2021.09.008]
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基于CT图像的颅内血肿检测与分割()
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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

卷:
38卷
期数:
2021年第9期
页码:
1090-1096
栏目:
医学人工智能
出版日期:
2021-09-26

文章信息/Info

Title:
Detection and segmentation of intracranial hematoma in CT image
文章编号:
1005-202X（2021）09-1090-07
作者:
刘元峰1; 刘立波1; 刘云2
1. 宁夏大学信息工程学院，宁夏银川750021；2. 宁夏医科大学总医院心脑血管病医院放射科，宁夏银川750002
Author(s):
LIU Yuanfeng1;  LIU Libo1;  LIU Yun2
1. School of Information Engineering, Ningxia University, Yinchuan 750021, China 2. Department of Radiology, Cardio- and Cerebrovascular Disease Hospital, General Hospital of Ningxia Medical University, Yinchuan 750002, China
关键词:
边缘检测; 遗传算法; 区域生长算法; 血肿检测与分割
Keywords:
edge detection genetic algorithm region-growing algorithm hematoma detection and segmentation
分类号:
R318；TP391
DOI:
10.3969/j.issn.1005-202X.2021.09.008
文献标志码:
A
摘要:
目的：为提高血肿分割精度，提出一种基于改进Canny算子的颅内类血肿噪声检测方法。方法：首先用区域生长算 法分割出颅脑组织，去掉颅骨等干扰信息。然后使用基于改进Canny边缘检测的方法检测颅脑边缘类血肿噪声，并与原 图像进行与运算消除该噪声。最后，通过使用OTSU适应度函数的遗传算法精准分割出颅内血肿。结果：该方法在随机 抽取的200例颅脑血肿图像中，血肿检测的准确率达到96.3%，Dice相似度达到93.5%。结论：该方法能准确、有效地检测 并分割出颅内血肿。
Abstract:
Objective To propose an intracranial hematoma-like noise detection method based on improved Canny operator for improving the accuracy of hematoma segmentation. Methods The brain tissues were firstly segmented by region-growing algorithm, and the interference information such as skull was removed. Then the hematoma-like noise at the edge of brain was detected by improved Canny edge detection, and the noise was eliminated by an and operation with the original image. Finally, the genetic algorithm based on OTSU fitness function was used to segment intracranial hematoma accurately. Results In 200 randomly selected brain hematoma images, the accuracy of hematoma detection was 96.3%, and Dice similarity reached 93.5%. Conclusion The proposed method can be used to detect and segment intracranial hematoma accurately and effectively.

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备注/Memo

备注/Memo:
【收稿日期】2021-04-19 【基金项目】国家自然科学基金（61862050）；宁夏自然科学基金 （2020AAC03031） 【作者简介】刘元峰，硕士，研究方向：医学图像处理、车辆目标检测， E-mail: 1251666248@qq.com 【通信作者】刘立波，博士，教授，研究方向：智能信息处理研究，Email: liulib@163.com
更新日期/Last Update: 2021-09-27