A cervical cell pathological slice pathological cell segmentation method and system

A technology of diseased cells and pathological slices, applied in the field of medical cytopathological image processing, to achieve the effect of optimizing the recognition results and the method is reasonable

Active Publication Date: 2018-12-18
怀光智能科技(武汉)有限公司
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Artificially designed pathological cell feature e

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  • A cervical cell pathological slice pathological cell segmentation method and system
  • A cervical cell pathological slice pathological cell segmentation method and system
  • A cervical cell pathological slice pathological cell segmentation method and system

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[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 cervical cell pathological slice pathological cell segmentation method and system, in particular, an off-line training sample set of cervical cell pathological slice pathological cell is established, a multi-scale cavity convolution structure semantic segmentation network is introduced on the basis of a depth residual network, and the semantic segmentation model is trained. The unit to be identified is extracted from the cervical pathological slice image, and different types of pathological cells are segmented in the unit to be identified by using the trained semanticsegmentation model. Based on the morphological features of pathological cells, a contour deformation model is established to further optimize the semantic segmentation results. According to the cellnumber and confidence level of different pathological types, the pathological types of the whole slice are predicted. The invention utilizes semantic segmentation network model and deformation variational model to accurately segment different types of pathological cells on the cell pathological slice image, and simultaneously improves the recognition accuracy and the 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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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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