阈值分割源码matlab-abd-skin-segmentation:在新颖的腹部数据集上进行皮肤分割的深度学习技术。作为自主机器人超声系统开

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阈值分割源码matlab 用于新型腹部数据集的皮肤分割的深度学习技术 介绍 该存储库提供了[]中研究的皮肤分割方法的代码,主要是Mask-RCNN,U-Net,全连接网络和用于阈值化的MATLAB脚本。 该算法主要是为了使用RGB图像对创伤患者进行腹部皮肤分割而开发的,这是正在进行的研究工作的一部分,该研究工作旨在开发用于创伤评估的自主机器人[] []。 机器人腹部超声系统具有摄像头查看的腹部区域,以及相应的分段式皮肤面罩。 腹部皮肤数据集的信息 该数据集包含从Google图像搜索在线检索的1,400幅腹部图像,这些图像随后进行了手动分段。 选择图像以保留不同种族的多样性,从而防止分割算法中的间接种族偏见; 700张图像代表肤色较深的人,其中包括非洲,印度和西班牙裔群体,而700张图像代表肤色较浅的人,例如高加索人和亚洲裔群体。 总共选择了400张图像来代表体重指数较高的人,在明亮和黑暗类别之间平均分配。 在数据集准备中,还考虑了个人之间的差异,例如头发和纹身的覆盖范围,以及阴影等外部差异。 图片尺寸为227x227像素。 皮肤像素占整个像素数据的66%,每个单个图像的平均值为54.4

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