Using Computer Vision and Deep Learning for Cells Recognition

Vitalii Yu Kudinov, Mikhail Yu Mashukov, Ekaterina A. Maslova, Konstantin E. Orishchenko, Aleksey G. Okunev, Andrey V. Matveev

Результат исследования: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Аннотация

The task of the objects identification, counting, and measurement is a huge part of scientific investigations and technological applications. Automated methods using traditional processing such as segmentation, edge detection, and so on represented by available software (e.g. CellProfiler) are not flexible, can be used only with images of high-quality, and in addition require setting a part of parameters by hand. This contribution presents the applying the deep learning method for recognition of HeLa cells expressing green fluorescent protein (EGFP) automatically. We used Cascade Mask R-CNN neural networks which has a ResNeXt backbone and deformable convolutional networks layers. Training dataset contained seven pictures with 5754 labeled cells. Three images with 2469 labeled cells were used as test-dataset. The trained neural network showed mAP=0.4.

Язык оригиналаанглийский
Название основной публикацииProceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы17-20
Число страниц4
ISBN (электронное издание)9780738131115
DOI
СостояниеОпубликовано - 14 ноя 2020
Событие2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020 - Virtual, Novosibirsk, Российская Федерация
Продолжительность: 14 ноя 202015 ноя 2020

Серия публикаций

НазваниеProceedings - 2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020

Конференция

Конференция2020 Science and Artificial Intelligence Conference, S.A.I.ence 2020
СтранаРоссийская Федерация
ГородVirtual, Novosibirsk
Период14.11.202015.11.2020

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