A method and system for segmenting diseased cells in cervical cytopathological slices

A technology of diseased cells and pathological slices, applied in the field of medical cytopathological image processing

Active Publication Date: 2021-05-11
怀光智能科技(武汉)有限公司
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Problems solved by technology

Artificially designed pathological cell feature engineering is effective but has great limitations

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  • A method and system for segmenting diseased cells in cervical cytopathological slices
  • A method and system for segmenting diseased cells in cervical cytopathological slices
  • A method and system for segmenting diseased cells in cervical cytopathological slices

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Embodiment Construction

[0041] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0042] Such as figure 1 As shown, the method and system for automatic segmentation of lesion cells in cervical cell pathology slices based on deep semantic segmentation network and deformation model provided by the present invention include the following steps:

[0043] Step 1) Offline establishment of a training sample set of lesion cells in cervical cytopathological slices, introduction of a se...

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Abstract

The invention discloses a method and system for segmenting cervical cell pathological slice lesion cells, specifically: establishing a training sample set of cervical cell pathological slice lesion cells offline, and introducing the semantics of multi-scale hole convolution structure on the basis of a deep residual network Segment the network and train the semantic segmentation model; extract the unit to be identified from the cervical pathological slice image, apply the trained semantic segmentation model to segment different types of diseased cells in the unit to be identified; combine the morphological features of pathological cells to establish a contour deformation model , to further optimize the semantic segmentation results; according to the number of cells and confidence levels of different lesion types segmented in the slice, the lesion category of the entire slice is predicted. The invention uses a semantic segmentation network model and a deformation variation model to accurately segment different types of pathological cells on the cytopathological slice image, and simultaneously improves recognition accuracy and recognition efficiency.

Description

technical field [0001] The invention belongs to the field of medical cytopathological image processing, and more specifically relates to a method and system for segmenting lesion cells in cervical cytopathological slices. Background technique [0002] Cervical cancer is a malignant tumor with high incidence in women. Cervical liquid-based cytopathology is currently the most important means of preventing and screening cervical cancer. Accurate interpretation of diseased cells in cytopathological slice images is an important basis for doctors to determine the patient's condition and formulate a treatment plan. At present, the manual interpretation of cytopathological images is not only time-consuming, but also the interpretation results are very dependent on the experience of doctors. Therefore, automatically interpreting diseased cells in pathological slides can not only improve the efficiency of diagnosis but also provide doctors with a more unified and objective basis for...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/12G06T7/149
CPCG06T2207/20081G06T2207/20084G06T2207/30096G06T7/12G06T7/149
Inventor 刘秀丽曾绍群余江胜田靓程胜华吕晓华
Owner 怀光智能科技(武汉)有限公司
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