Large-scale automated identification of mouse brain cells in confocal light sheet microscopy images

被引：53

作者：

Frasconi, Paolo ^{[1
]}

Silvestri, Ludovico ^{[2
]}

Soda, Paolo ^{[3
]}

Cortini, Roberto ^{[1
]}

Pavone, Francesco S. ^{[2
]}

Iannello, Giulio ^{[3
]}

机构：

[1] Univ Florence, Dept Informat Engn DINFO, I-50139 Florence, Italy

[2] Univ Florence, LENS, I-50019 Sesto Fiorentino, Italy

[3] Univ Campus Biomed Roma, Integrated Res Ctr, I-00128 Rome, Italy

来源：

BIOINFORMATICS | 2014年 / 30卷 / 17期

关键词：

ELECTRON-MICROSCOPY; VISUALIZATION; ROBUST; MICE; RECONSTRUCTION; TOMOGRAPHY;

D O I：

10.1093/bioinformatics/btu469

中图分类号：

Q5 [生物化学];

学科分类号：

070307 [化学生物学];

摘要：

Motivation: Recently, confocal light sheet microscopy has enabled high-throughput acquisition of whole mouse brain 3D images at the micron scale resolution. This poses the unprecedented challenge of creating accurate digital maps of the whole set of cells in a brain. Results: We introduce a fast and scalable algorithm for fully automated cell identification. We obtained the whole digital map of Purkinje cells in mouse cerebellum consisting of a set of 3D cell center coordinates. The method is accurate and we estimated an F-1 measure of 0.96 using 56 representative volumes, totaling 1.09 GVoxel and containing 4138 manually annotated soma centers.

引用

页码：I587 / I593

页数：7

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