An automated procedure to properly handle digital images in large scale Tissue Microarray experiments

被引:13
作者
Dell'Anna, R
Demichelis, F
Barbareschi, M
Sboner, A
机构
[1] ITC Irst, SRA Div, Bioinformat Grp, I-38050 Trento, Italy
[2] Santa Chiara Hosp, Dept Surg Pathol, I-38100 Trento, Italy
[3] Univ Trent, Dept Informat & Commun Technol, I-38050 Trento, Italy
关键词
automation; image processing; Tissue Microarray;
D O I
10.1016/j.cmpb.2005.04.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Tissue Microarray (TMA) methodology has been recently developed to enable "genome-scale" molecular pathology studies. To enable high-throughput screening of TMAs automation is mandatory, both to speed up the process and to improve data quality. In particular, in acquiring digital images of single tissues (core sections) a crucial step is the correct recognition of each tissue position in the array. In fact, further reliable data analysis is based on the exact assignment of each tissue to the corresponding tumor. As most of the times tissue alignment in the microarray grid is far from being perfect, simple strategies to perform proper acquisition do not fit well. The present paper describes a new solution to automatically perform grid location assignment. We developed an ad hoc image processing procedure and a robust algorithm for object recognition. Algorithm accuracy tests and assessment of working constraints are discussed. Our approach speeds up TMA data collection and enables large scale investigation. (c) 2005 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:197 / 208
页数:12
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