Evaluation of features for automatic detection of cell nuclei in fluorescence microscopy images

被引：0

作者：

Fabris, Paolo ^{[1
]}

Vanzella, Walter ^{[1
]}

Pellegrino, Felice Andrea ^{[2
]}

机构：

[1] Glance Vis Technol Srl, Area Sci Pk,Edificio Q1,Str Statale 14,Km 163 5, I-34012 Trieste, Italy

[2] Univ Trieste, Dipartimento Ingn & Architettura, I-34127 Trieste, Italy

来源：

2013 8TH INTERNATIONAL SYMPOSIUM ON IMAGE AND SIGNAL PROCESSING AND ANALYSIS (ISPA) | 2013年

关键词：

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：

The problem of detecting cell nuclei in fluorescence images may be faced by means of a segmentation step, to get the neighbourhood of candidate nuclei, followed by a binary classification step. Important for the latter step is the choice of the descriptors (features) to be extracted from the neighbourhood and used by the classifier. In the present paper, based on a large set of manually labelled samples, we evaluate several of such descriptors combined with some common type of support vector machines. We show that equipping the detection algorithm with the best combination of features/classifier leads to a performance comparable to human labelling by experts.

引用

页码：683 / +

页数：2

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