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Updated: Jan 10, 2026

Morphology-Based Distinction Between Healthy and Pathological Cells Utilizing Fourier Transforms and Self-Organizing Maps
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基于深度学习的预测个体细胞的散容量从形态特征

Tae Young Kang1, Soojung Kim2, Yoon-Hwae Hwang3

  • 1Institute for Future Earth, Pusan National University (PNU), Busan 46241, Republic of Korea.

Biosensors
|November 26, 2025
PubMed
概括

这项研究开发了一种深度学习方法,以纠正影响电气测量的细胞形状变化. 这提高了癌症诊断的准确性,因为它可以从测量器件中分离出真正的生物信号.

关键词:
细胞形态细胞形态学深度学习是一种深度学习.非侵入性的细胞表征.一个单细胞的单细胞.α-分散电容度的扩散能力.

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Flow Cytometry01:23

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The development of flow cytometry techniques began in 1934 with initial attempts by Andrew Moldavan, a bacteriologist who counted the cells in a flowing capillary system. Moldavan pumped cells through a capillary tube focused under a microscope for visualization. The invention of photometry allowed the measurement of differentially-stained cells, and Louis Kamentsky developed the first multiparameter flow cytometer in 1965 to identify and count the cancer cells in cervical tissue specimens.
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