乳腺超声图像疑似病灶筛选算法数据集

该数据集可应用于乳腺超声智能分析、病灶检测与分类、算法性能评估等场景。通过对疑似病灶的空间位置和形态参数进行分析，可有效过滤掉不符合特征模式的假阳性区域，提高病灶检测的准确率；同时为后续的病灶良恶性分类、辅助诊断及影像质控提供可靠数据支撑。

This dataset can be applied to scenarios including intelligent analysis of breast ultrasound images, lesion detection and classification, and algorithm performance evaluation. By analyzing the spatial location and morphological parameters of suspected lesions, it can effectively filter out false-positive regions that do not match the characteristic patterns, thereby improving the accuracy of lesion detection. Meanwhile, it provides reliable data support for subsequent benign and malignant classification of lesions, auxiliary diagnosis, and imaging quality control.