Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Smart Mobile Microscopy : Towards Fully-Automated Digitization. / Kornilova, Anastasiia; Kirilenko, Iakov; Iarosh, Dmitrii; Kutuev, Vladimir; Strutovsky, Maxim.
Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2. ed. / Kohei Arai. Vol. 2 Springer Nature, 2022. p. 617-635 (Lecture Notes in Networks and Systems; Vol. 359 LNNS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
}
TY - GEN
T1 - Smart Mobile Microscopy
T2 - 6th Future Technologies Conference, FTC 2021
AU - Kornilova, Anastasiia
AU - Kirilenko, Iakov
AU - Iarosh, Dmitrii
AU - Kutuev, Vladimir
AU - Strutovsky, Maxim
N1 - Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Mobile microscopy is a newly formed field that emerged from a combination of optical microscopy capabilities and spread, functionality, and ever-increasing computing resources of mobile devices. Despite the idea of creating a system that would successfully merge a microscope, numerous computer vision methods, and a mobile device is regularly examined, the resulting implementations still require the presence of a qualified operator to control specimen digitization. In this paper, we address the task of surpassing this constraint and present a “smart” mobile microscope concept aimed at automatic digitization of the most valuable visual information about the specimen. We perform this through combining automated microscope setup control and classic techniques such as auto-focusing, in-focus filtering, and focus-stacking—adapted and optimized as parts of a mobile cross-platform library.
AB - Mobile microscopy is a newly formed field that emerged from a combination of optical microscopy capabilities and spread, functionality, and ever-increasing computing resources of mobile devices. Despite the idea of creating a system that would successfully merge a microscope, numerous computer vision methods, and a mobile device is regularly examined, the resulting implementations still require the presence of a qualified operator to control specimen digitization. In this paper, we address the task of surpassing this constraint and present a “smart” mobile microscope concept aimed at automatic digitization of the most valuable visual information about the specimen. We perform this through combining automated microscope setup control and classic techniques such as auto-focusing, in-focus filtering, and focus-stacking—adapted and optimized as parts of a mobile cross-platform library.
KW - Algorithms comparison
KW - Biomedical imaging
KW - Digital microscopy
KW - Dust removal
KW - Field diagnostics
KW - Focus stacking
KW - Image acquiring
KW - Mobile computing
KW - Mobile microscopy
UR - http://www.scopus.com/inward/record.url?scp=85119893297&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/11bc4de7-2732-3e26-9a85-7768fbfde377/
U2 - 10.1007/978-3-030-89880-9_46
DO - 10.1007/978-3-030-89880-9_46
M3 - Conference contribution
AN - SCOPUS:85119893297
SN - 9783030898793
VL - 2
T3 - Lecture Notes in Networks and Systems
SP - 617
EP - 635
BT - Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2
A2 - Arai, Kohei
PB - Springer Nature
Y2 - 28 October 2021 through 29 October 2021
ER -
ID: 88205952