Prostate cancer diagnosis using quantitative phase imaging and machine learning

被引：4

作者：

Nguyen, Tan H. ^{[1
,2
]}

Sridharan, Shamira ^{[1
]}

Marcias, Virgilia ^{[3
]}

Balla, Andre K. ^{[3
]}

Do, Minh N. ^{[2
]}

Popescu, Gabriel ^{[1
]}

机构：

[1] Univ Illinois, Dept Elect & Comp Engn, Beckman Inst Adv Sci & Technol, Quantitat Phase Imaging Lab, Urbana, IL 61801 USA

[2] Univ Illinois, Dept Elect & Comp Engn, Coordinated Sci Lab, Computat Imaging Grp, Urbana, IL 61801 USA

[3] Univ Chicago, Dept Pathol, Chicago, IL 60637 USA

来源：

QUANTITATIVE PHASE IMAGING | 2015年 / 9336卷

关键词：

automatic diagnosis; Quantitative Phase Imaging; texton analysis; prostate cancer; MICROSCOPY;

D O I：

10.1117/12.2080321

中图分类号：

TH742 [显微镜];

学科分类号：

摘要：

We report, for the first time, the use of Quantitative Phase Imaging (QPI) images to perform automatic prostate cancer diagnosis. A machine learning algorithm is implemented to learn textural behaviors of prostate samples imaged under QPI and produce labeled maps of different regions for testing biopsies (e.g. gland, stroma, lumen etc.). From these maps, morphological and textural features are calculated to predict outcomes of the testing samples. Current performance is reported on a dataset of more than 300 cores of various diagnosis results.

引用

页数：10

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