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Inverse kinematic problem in 2d medical acoustic travel-time tomography Научная публикация

Журнал Computational Mathematics and Modeling
ISSN: 1046-283X
Вых. Данные Год: 2026, DOI: 10.1007/s10598-026-09724-5
Ключевые слова Inverse problem · Eikonal equation · Kinematic · Travel-time tomography · Optimization · Accelerated gradient method · Adaptive relaxation of steps
Авторы Dudar Maxim 1,2 , Shishlenin Maxim 1,2
Организации
1 Institute of Computational Mathematics and Mathematical Geophysics, Lavrentieva Street, 6, 630090, Novosibirsk, Russian Federation
2 Sobolev Institute of Mathematics, pr. ac. Koptyuga, 4, 630090, Novosibirsk, Russian Federation

Информация о финансировании (1)

1 Российский научный фонд 25-61-00027

Реферат: In this work, the inverse problem of reconstructing the squared slowness function in the two-dimensional eikonal equation has been developed and numerically investigated. The inverse problem is reduced to the minimization of a travel-time misfit functional by gradient method and employs the Fast Marching Method for an efficient solution of the direct eikonal problem. A gradient of the functional is calculated by direct and adjoint problems, enabling the computational cost of the gradient comparable to that of a single direct solve. Numerical experiments on synthetic models which parameters are close to the human body with inclusions show that the method can accurately recover the spatial structure and contrast of the slowness distribution under different grid resolutions and source configurations. A comparative analysis of simple gradient and heavy ball method has shown that the use of adaptive relaxation of steps accelerates the convergence of gradient methods, including accelerated gradient methods.
Библиографическая ссылка: Dudar M. , Shishlenin M.
Inverse kinematic problem in 2d medical acoustic travel-time tomography
Computational Mathematics and Modeling. 2026. DOI: 10.1007/s10598-026-09724-5 Scopus OpenAlex
Даты:
Поступила в редакцию: 10 мар. 2026 г.
Принята к публикации: 26 мая 2026 г.
Опубликована online: 16 июн. 2026 г.
Идентификаторы БД:
≡ Scopus: 2-s2.0-105041947348
≡ OpenAlex: W7164971967
Альметрики: