Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220200063-10.doi: 10.11896/jsjkx.220200063

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Study on Phased Target Detection in CT Image

WANG Xiaotian1, LI Bo2, KANG Xiaodong1, LIU Hanqing1, HAN Junling1, YANG Jingyi1   

  1. 1 School of Medical Image,Tianjin Medical University,Tianjin 300202,China;
    2 The Third Central Clinical College of Tianjin Medical University,Tianjin 300170,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:WANG Xiaotian,born in 1998,undergraduate.His main research interests include medical image processing and so on. KANG Xiaodong,born in 1964,Ph.D,professor.His main research interests include medical image processing and medical information system integration.
  • Supported by:
    Beijing-Tianjin-Hebei Collaborative Innovation Proejct(17YEXTZC00020).

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Abstract: CT is one of the most commonly used imaging examinations in clinic,and the computer-aided diagnosis of CT images has important clinical significance.In order to optimize target detection in CT images,eight different target detection algorithms are used to detect hepatic hemangioma enhanced CT images,cerebral artery stenosis CTA images and colonic polyp CT images,and the applicability of different algorithms are compared.Firstly,the enhanced CT images of hepatic hemangioma,CTA images of cerebral artery stenosis and CT images of colonic polyps are labeled and datasets are made.Secondly,different parameter optimization algorithms are used,and AP-epoch and AP-FPS curves are drawn to compare the detection performance of different algorithms.Experimental results show that the AP,AP50,AP75 and Recall of PPYOLOv2 are optimal in different data sets,the prediction boundary box is close to the target to be tested,the prediction confidence is high,and it has good generalization ability and robustness.

Key words: Target detection, Deep learning algorithm, CT, CTA

CLC Number: 

  • TP391
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