| Autor: |
Bartłomiej Pyciński, Ann E. Walts, Arkadiusz Gertych, Yukako Yagi |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Advances in Intelligent Systems and Computing ISBN: 9783030496654 |
| DOI: |
10.1007/978-3-030-49666-1_5 |
| Popis: |
3-D histology has become an attractive technique providing insights into morphology of histologic specimens. However, existing techniques in generating 3-D views from a stack of whole slide images are scarce or suffer from poor co-registration performance when displaying diagnostically important areas at sub-cellular resolution. Our team developed a new scale-invariant feature transform (SIFT)-based workflow to co-register histology images and facilitate 3-D visualization of micro-structures important in histopathology of lung adenocarcinoma. The co-registration accuracy and visualization capacity of the workflow were tested by digitally perturbing the staining coloration seven times. The perturbation slightly affected the co-registration but overall the co-registration errors remained very small when compared to those published to date. The workflow yielded accurate visualizations of expert-selected regions permitting confident 3-D evaluation of the clusters. Our workflow could support the evaluation of histologically complex tumors such as lung adenocarcinomas that are currently routinely viewed by pathologists in 2-D on slides, but could benefit from 3-D visualization. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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