BENCHMARKING OF ALGORITHMS FOR 3D TISSUE RECONSTRUCTION

被引：0
|
作者：
Kartasalo, Kimmo [1 ,2 ,3 ]
Latonen, Leena [2 ,3 ,4 ]
Visakorpi, Tapio [2 ,3 ,4 ]
Nykter, Matti [1 ,2 ,3 ]
Ruusuvuori, Pekka [2 ,3 ,5 ]
机构：
[1] Tampere Univ Technol, BioMediTech, Dept Signal Proc, Tampere, Finland
[2] Tampere Univ, BioMediTech, Tampere, Finland
[3] Tampere Univ, Prostate Canc Res Ctr, Tampere, Finland
[4] Tampere Univ Hosp, Fimlab Labs, Tampere, Finland
[5] Tampere Univ Technol, Pori, Finland
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP) | 2016年
关键词：
Image registration; 3D reconstruction; histology; digital pathology; benchmark; IMAGE; REGISTRATION;
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：
Studying tissue structure in 3D is beneficial in many applications. Reconstructing the structure based on histological sections has the advantages of high resolution and compatibility with conventional staining and interpretation techniques. However, obtaining an accurate 3D reconstruction based on a sequence of 2D sections is a difficult task. Evaluating the accuracy of such reconstructions is also challenging and it is often performed based only on visual inspections or a single indirect numerical measure. Here, we present a benchmarking framework composed of a panel of complementary metrics for assessing the quality of 3D reconstructions. We then apply the framework to evaluate the performance of several popular image registration algorithms in this context.
引用
收藏
页码：2360 / 2364
页数：5
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