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. 2021 Oct 20:2021:1141619.
doi: 10.1155/2021/1141619. eCollection 2021.

Tumor Region Location and Classification Based on Fuzzy Logic and Region Merging Image Segmentation Algorithm

Tianyu Zhao  1 , Hang Dai  2
Affiliations

Tumor Region Location and Classification Based on Fuzzy Logic and Region Merging Image Segmentation Algorithm

Tianyu Zhao et al. J Healthc Eng. .

Retraction in

Abstract

Early diagnosis of tumor plays an important role in the improvement of treatment and survival rate of patients. However, breast tumors are difficult to be diagnosed by invasive examination, so medical imaging has become the most intuitive auxiliary method for breast tumor diagnosis. Although there is no universal perfect method for image segmentation so far, the consensus on the general law of image segmentation has produced considerable research results and methods. In this context, this paper focuses on the breast tumor image segmentation method based on CNN and proposes an improved DCNN method combined with CRF. This method can obtain the information of multiscale and pixels better. The experimental results show that, compared with DCNN without these methods, the segmentation accuracy is significantly improved.

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Conflict of interest statement

The authors declare no conflicts of interest in this article.

Figures

Figure 1
Figure 1
PPV comparison of various methods.
Figure 2
Figure 2
Sensitivity comparison of various methods.
Figure 3
Figure 3
Accuracy of tumor classification based on this method.
See this image and copyright information in PMC

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