Multi-stained whole slide image alignment in digital pathology

Oscar Déniz; David Toomey; Catherine Conway; Gloria Bueno

doi:10.1117/12.2082256

19 March 2015 Multi-stained whole slide image alignment in digital pathology

Oscar Déniz, David Toomey, Catherine Conway, Gloria Bueno

Proceedings Volume 9420, Medical Imaging 2015: Digital Pathology; 94200Z (2015) https://doi.org/10.1117/12.2082256
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

In Digital Pathology, one of the most simple and yet most useful feature is the ability to view serial sections of tissue simultaneously on a computer monitor. This enables the pathologist to evaluate the histology and expression of multiple markers for a patient in a single review. However, the rate limiting step in this process is the time taken for the pathologist to open each individual image, align the sections within the viewer, with a maximum of four slides at a time, and then manually move around the section. In addition, due to tissue processing and pre-analytical steps, sections with different stains have non-linear variations between the two acquisitions, that is, they will stretch and change shape from section to section. To date, no solution has come close to a workable solution to automatically align the serial sections into one composite image. This research work address this problem to obtain an automated serial section alignment tool enabling the pathologists to simply scroll through the various sections in a single viewer. To this aim a multi-resolution intensity-based registration method using mutual information as a similarity metric, an optimizer based on an evolutionary process and a bilinear transformation has been used. To characterize the performance of the algorithm 40 cases x 5 different serial sections stained with hematoxiline-eosine (HE), estrogen receptor (ER), progesterone receptor (PR), Ki67 and human epidermal growth factor receptor 2 (Her2), have been considered. The qualitative results obtained are promising, with average computation time of 26.4s for up to 14660x5799 images running interpreted code.

Citation Download Citation

Oscar Déniz, David Toomey, Catherine Conway, and Gloria Bueno "Multi-stained whole slide image alignment in digital pathology", Proc. SPIE 9420, Medical Imaging 2015: Digital Pathology, 94200Z (19 March 2015); https://doi.org/10.1117/12.2082256

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