A 178-clinical-center experiment of integrating AI solutions for lung pathology diagnosis

Autor: Bulat Ibragimov, Kirill Arzamasov, Bulat Maksudov, Semen Kiselev, Alexander Mongolin, Tamerlan Mustafaev, Dilyara Ibragimova, Ksenia Evteeva, Anna Andreychenko, Sergey Morozov

Publikováno v: Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)

Abstract In 2020, an experiment testing AI solutions for lung X-ray analysis on a multi-hospital network was conducted. The multi-hospital network linked 178 Moscow state healthcare centers, where all chest X-rays from the network were redirected to

Externí odkaz: https://doaj.org/article/97a405c86d6f4705984b55bde6076b92

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification

Autor: Imad Eddine Ibrahim Bekkouch, Bulat Maksudov, Semen Kiselev, Tamerlan Mustafaev, Tomaž Vrtovec, Bulat Ibragimov

Publikováno v: Bekkouch, I E I, Maksudov, B, Kiselev, S, Mustafaev, T, Vrtovec, T & Ibragimov, B 2022, ' Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification ', Medical Image Analysis, vol. 78, 102417 . https://doi.org/10.1016/j.media.2022.102417

Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landma

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26416117be6e1236a7474f74a601fccb
https://curis.ku.dk/portal/da/publications/multilandmark-environment-analysis-with-reinforcement-learning-for-pelvic-abnormality-detection-and-quantification(2b29131c-9edb-4d52-88a4-c4430277894d).html

Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest Radiography

Autor: Semen Kiselev, Bulat Ibragimov, Konstantin Kubrak, Ilyas Sirazitdinov, Maksym Kholiavchenko, Alexey Tolkachev

Publikováno v: Artificial Neural Networks and Machine Learning – ICANN 2020 ISBN: 9783030616083
ICANN (1)

Bone suppression in chest x-rays is an important processing step that can often improve visual detection of lung pathologies hidden under ribs or clavicle shadows. Current diagnostic imaging protocol does not include hardware-based bone suppression,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e15d059ca65c40e30e65416fe303fead
https://doi.org/10.1007/978-3-030-61609-0_20