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Progress of artificial intelligence-based pathology in tumor diagnosis and treatment
TIAN Dawei  WANG Xiaochun  ZHANG Hui  TAN Yan 

Cite this article as: Tian DW, Wang XC, Zhang H, et al. Progress of artificial intelligence-based pathology in tumor diagnosis and treatment[J]. Chin J Magn Reson Imaging, 2021, 12(2): 117-120. DOI:10.12015/issn.1674-8034.2021.02.029.


[Abstract] Early detection and accurate diagnosis of tumors are crucial to the choice of treatment and the improvement of survival rate. As the gold standard of early diagnosis of tumor, pathology is a highly subjective, tedious, and non-repeatable process that histopathologists make a diagnosis by visually analyzing the tissue structure and cytopathic characteristics of the sample. With the development of artificial intelligence technology in recent years, especially radiomics can extract quantitative features from MRI images with high throughput, and convert images into high-dimensional and extractable data which show great advantages in tumor diagnosis, classification, prognosis. Quantitative analysis of pathological images based on artificial intelligence also has unique value in tumor diagnosis and treatment. It not only improves the accuracy and objectivity of tumor diagnosis, but also reduces the work of pathologists. Under certain circumstances, the ability to recognize slides exceeds that of professional pathologists. The combination of radiomics and pathological data is a new research trend. This paper reviews the application of artificial intelligence-based pathology in tumors, the role of pathology information in MRI and future prospects.
[Keywords] artificial intelligence；deep learning；pathology；magnetic resonance imaging；tumour

TIAN Dawei1   WANG Xiaochun2   ZHANG Hui2   TAN Yan2*  

1 Department of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China

2 Department of Radiology, the First Hospital of Shanxi Medical University, Taiyuan 030001, China

Tan Y, E-mail: tanyan123456@sina.com

Conflicts of interest   None.

ACKNOWLEDGENTS This work was part of National Natural Science Foundation of China (No.81701681).
Received  2020-06-27
Accepted  2020-08-21
DOI: 10.12015/issn.1674-8034.2021.02.029
Cite this article as: Tian DW, Wang XC, Zhang H, et al. Progress of artificial intelligence-based pathology in tumor diagnosis and treatment[J]. Chin J Magn Reson Imaging, 2021, 12(2): 117-120. DOI:10.12015/issn.1674-8034.2021.02.029.

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