PROSTATIC CELLS CLASSIFICATION USING DEEP LEARNING

被引：0

作者：

Majercik, Jakub ^{[1
]}

Spacek, Michal ^{[1
]}

机构：

[1] FEEC BUT, Bachelor Degree Programme 2, Brno, Czech Republic

来源：

PROCEEDINGS II OF THE 26TH CONFERENCE STUDENT EEICT 2020 | 2020年

关键词：

cell classification; deep learning; neural network; quantitative phase imaging; microscopy;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Human prostate cancer PC-3 cell line is widely used in cancer research. Previously, Zinc-Resistant variant was described characteristically by higher dry cellular mass determined by quantitative phase imaging. This work aims to classify these 2 cell types into corresponding categories using machine learning methods. We have achieved 97.5% accuracy with the correct preprocessing using Res-Net network.

引用

页码：28 / 31

页数：4

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