Subcutaneous tissue structural feature identification using unsupervised machine learning

doi:10.1016/j.compbiomed.2026.111553

2026-02-24

PRE

Adrián Buganza Tepole

Pavlos P. Vlachos *

DOI：10.1016/j.compbiomed.2026.111553

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摘要

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• 极坐标下的2D近场强度映射以捕捉结构细节。 • K-means聚类用于分割和特征识别。 • 通过极坐标下的邻域分析处理旋转不变性。 • 数据降维技术以提高特征向量的可分性和聚类精度。 • 在染色组织学图像中已验证的应用，实现了对皮下组织结构特征的识别。

Keyword:

2D proximal intensity mapping

K-means clustering

polar coordinates

rotational invariance

histology images

期刊

Computers in Biology and Medicine

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6.3

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8.3K

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purdue university

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biomedical engineering

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484

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Pennsylvania State University

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