Cervical cancer pathological cell classification system of microscope pathological photograph

A diseased cell and classification system technology, applied in instruments, character and pattern recognition, computer components, etc., can solve the problems of irregular cells, overlapping staining, unevenness, etc.

Pending Publication Date: 2019-10-15
江苏迪赛特医疗科技有限公司
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Problems solved by technology

Despite recent advances in cell segmentation algorithms, accurate segmentation remains a challenge due to irregularities, overlaps, and uneven staining of cells in m...

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  • Cervical cancer pathological cell classification system of microscope pathological photograph

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Embodiment Construction

[0016] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0017] Embodiments of the present invention relate to a system for classifying cervical cancer lesion cells from microscope pathological photos, a detection network model and a classification network model. The cells in the photo are detected; the classification network model is trained according to the incomplete cell classification and labeling data, and after the training is completed, it is used to classify the detected cel...

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Abstract

The invention relates to a cervical cancer pathological cell classification system of a microscope pathological photograph. The system comprises a detection network model and a classification networkmodel. The detection network model is trained by using incompletely classified cell labeling data, and is used for detecting cells in the microscope photograph after the training is completed. The classification network model is trained according to the incomplete cell classification annotation data, and is used for classifying the detected cells and predicting the specific types of the cells after the training is completed. According to the system, the pathological cell detection/classification model can be obtained by training incompletely labeled samples.

Description

technical field [0001] The invention relates to the technical field of cervical cancer lesion cell classification, in particular to a cervical cancer lesion cell classification system based on microscope pathological photos. Background technique [0002] Cervical cancer is the fourth leading cause of cancer death in women. Therefore, cervical cancer screening is very important for the treatment of cervical cancer. A Pap smear is a physical examination technique that is widely used to prevent cervical cancer and to find cells that are potentially cancerous. However, the diagnosis process relies heavily on the experience of doctors, which is very time-consuming on the one hand and prone to human misjudgment on the other hand. Due to the latest development of computer technology, computer-aided cell detection technology can play an important role in cytology screening. It can not only screen accurately, reduce labor intensity and workload, but also eliminate the psychological...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/695G06V20/698
Inventor 李文勇王乾张立箎
Owner 江苏迪赛特医疗科技有限公司
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