TY - JOUR

T1 - DLgram cloud service for deep-learning analysis of microscopy images

AU - Matveev, Andrey V.

AU - Nartova, Anna V.

AU - Sankova, Natalya N.

AU - Okunev, Alexey G.

N1 - This work was conducted with the financial support of the Russian Science Foundation (project No. 22‐23‐00951). Публикация для корректировки.

PY - 2024/5

Y1 - 2024/5

N2 - To analyze images in various fields of science and technology, it is often necessary to count observed objects and determine their parameters. This can be quite labor-intensive and time-consuming. This article presents DLgram, a universal, user-friendly cloud service that is developed for this purpose. It is based on deep learning technologies and does not require programming skills. The user labels several objects in the image and uploads it to the cloud where the neural network is trained to recognize the objects being studied. The user receives recognition results, which if necessary, can be corrected, errors removed, or missing objects added. In addition, it is possible to carry out mathematical processing of the data obtained to get information about the sizes, areas, and coordinates of the observed objects. The article describes the service features and discusses examples of its application. The DLgram service allows to reduce significantly the time spent on quantitative image analysis, reduce subjective factor influence, and increase the accuracy of analysis. Research Highlights: DLgram automatically recognizes and counts the number of objects in images and their parameters. DLgram is a universal service, which was created on the basis of the latest deep learning developments and does not require programming skills.

AB - To analyze images in various fields of science and technology, it is often necessary to count observed objects and determine their parameters. This can be quite labor-intensive and time-consuming. This article presents DLgram, a universal, user-friendly cloud service that is developed for this purpose. It is based on deep learning technologies and does not require programming skills. The user labels several objects in the image and uploads it to the cloud where the neural network is trained to recognize the objects being studied. The user receives recognition results, which if necessary, can be corrected, errors removed, or missing objects added. In addition, it is possible to carry out mathematical processing of the data obtained to get information about the sizes, areas, and coordinates of the observed objects. The article describes the service features and discusses examples of its application. The DLgram service allows to reduce significantly the time spent on quantitative image analysis, reduce subjective factor influence, and increase the accuracy of analysis. Research Highlights: DLgram automatically recognizes and counts the number of objects in images and their parameters. DLgram is a universal service, which was created on the basis of the latest deep learning developments and does not require programming skills.

KW - automation

KW - deep learning

KW - image processing

KW - microscopy

KW - recognition

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85181485920&origin=inward&txGid=6b0be025f8b39efc1e77e346cc42b55f

UR - https://www.mendeley.com/catalogue/31ad4120-0c1d-3a1e-98e5-6aab14d05ee6/

U2 - 10.1002/jemt.24480

DO - 10.1002/jemt.24480

M3 - Article

C2 - 38186233

VL - 87

SP - 991

EP - 998

JO - Microscopy Research and Technique

JF - Microscopy Research and Technique

SN - 1097-0029

IS - 5

ER -