KFU. Card publication. Automation of bone tissue histology

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

AUTOMATION OF BONE TISSUE HISTOLOGY

Form of presentation

International monographs

Year of publication

2019

Authors, employees of KFU

Gerasimov Oleg Vladimirovich, author

Sachenkov Oskar Aleksandrovich, author

Authors, students KFU

Yaikova Viktoriya Vladimirovna, author

Bibliographic description in the original language

In abstract methods of automation of histology of bone structure are considered. Possible inputs are 13 snapshots of quantitative phase imaging or scanning electron microscope or computed tomography slices. An algorithm is proposed that differentiates object according to their color (or gray scale) and recover morphology topology. Algorithm to separate morphological objects by their dimensions and color parameters was built. Measured parameters are bone surface, bone area, porosity cortical thickness, canal number, canal area and etc. Additionally was measured the anisotropy properties of the bone tissue: distribution of porosity direction and degree of porosity elongation. Bone example was scanned by computed tomography. All data was measured by proposed method and results presented. Some analyze of data for different measurements was done.

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=212440&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Gerasimov Oleg Vladimirovich	ru_RU
dc.contributor.author	Sachenkov Oskar Aleksandrovich	ru_RU
dc.contributor.author	Yaikova Viktoriya Vladimirovna	ru_RU
dc.date.accessioned	2019-01-01T00:00:00Z	ru_RU
dc.date.available	2019-01-01T00:00:00Z	ru_RU
dc.date.issued	2019	ru_RU
dc.identifier.citation	In abstract methods of automation of histology of bone structure are considered. Possible inputs are 13 snapshots of quantitative phase imaging or scanning electron microscope or computed tomography slices. An algorithm is proposed that differentiates object according to their color (or gray scale) and recover morphology topology. Algorithm to separate morphological objects by their dimensions and color parameters was built. Measured parameters are bone surface, bone area, porosity cortical thickness, canal number, canal area and etc. Additionally was measured the anisotropy properties of the bone tissue: distribution of porosity direction and degree of porosity elongation. Bone example was scanned by computed tomography. All data was measured by proposed method and results presented. Some analyze of data for different measurements was done.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=212440&p_lang=2	ru_RU
dc.language.iso	ru	ru_RU
dc.title	Automation of bone tissue histology	ru_RU
dc.type	International monographs	ru_RU