Tumor segmentation method based on homogeneous pieces and fuzzy measure of breast ultrasound image

Abstract

The invention discloses a tumor segmentation method based on homogeneous pieces and fuzzy measure a breast ultrasound image, which comprises the following steps: (1), inputting the breast ultrasound image to be segmented; (2), margin detection for the image to be segmented; (3), defining the homogeneous piece; (4), defining a weighting function, considering the homogeneous pieces of each image pixel point as a fuzzy set, defining the fuzzy measure for measuring the diversity of the fuzzy set based on the margin information, the texture information and the space information, and defining the weighting function; and (5), achieving tumor segmentation. The invention has the advantages that (1), through defining the homogeneous pieces, the problem of selecting among the neighborhood windows in a traditional method is solved, the accuracy of the area statistics information is ensured, and the segmentation precision is improved; and (2), through the fuzzy measure and the homogeneous pieces, the weighting function is defined, the partial image misclassification is basically eliminated, the precision of the breast tumor segmentation is improved, and the favorable robustness is demonstrated at the same time.

Description

technical field [0001] The invention relates to the technical field of medical ultrasound image processing, in particular to a method for tumor segmentation of breast ultrasound images based on homogeneous slices and fuzzy measures. Background technique [0002] Breast cancer is one of the most common malignant tumors in women, and its morbidity and mortality rank first among women's diseases. Early diagnosis and treatment are the key to improve the postoperative survival rate of breast cancer. Ultrasonography is widely used in the auxiliary detection of breast tumors due to its characteristics of non-invasiveness, no special contraindications, strong reproducibility, and low cost. However, its accuracy often depends on the doctor's clinical experience and has strong subjectivity. In order to improve the objectivity of doctors' diagnosis, it is urgent to develop computer-aided diagnosis system in clinical application. [0003] Ultrasound image segmentation is an important...

AI Technical Summary

Problems solved by technology

However, the NCut method for the segmentation of breast ultrasound images is rarely reported.

At the same time, there are mainly the following problems in directly applying the above method to the poor quality ultrasound image segmentation: (1) How to select a suitable neighborhood, even if the size of the neighborhood window is selected appropriately, the fixed neighborhood may span different tissue regions, Therefore, it is difficult to ensure the homogeneity of the pixel neighborhood, which eventually leads to the wrong division of pixels

(2) How to define better weights for ultrasound image segmentation performance has not yet been resolved

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