Comparison of Mutual Information with a Standard Method for Alignment of Histological Serial Sections
The purpose of the study was to compare the ability of a mutual information algorithm with that of a standard algorithm to align images of histological serial sections. The two align algorithms were implemented in C running on a Linux based PC. Both algorithms used the same gradient-based optimizer, but different cost functions standard (57), and mutual information (MI) respectively. The object of the test was to align 4557 serial sections originating from a rat kidney. The alignment of kidney sections is difficult as these sections contain many nearly identical tubules, representing a high degree of translation symmetry. As a consequence there is a non-negligible chance of misalignment into a local minimum, making serial kidney sections good real life test objects for image alignment We showed that images, which were difficult to align by the ST were easy to align with MI. We found that the most efficient strategy was first to align all 4557 images using the ST function and then to align the misaligned 54 images using the MI function.
Alignment mutual information PET registration serial sections transformation values.
Ying Yu Joergen Erik Assentoft Jesper Skovhus Thomsen Erik Ils(o) Christensen Arne Andreasen
Department of Biomedical Engineering China Medical University Shenyang, China Department of Nuclear Medicine & Department of Medical Physics Aalborg University Hospital Aalborg, Institute of Anatomy Aarhus University Aarhus, Denmark
国际会议
上海
英文
198-202
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）