Zobrazeno 1 - 10
of 3 883
pro vyhledávání: '"A Visvikis"'
Direct3{\gamma}PET is a novel, comprehensive pipelinefor direct estimation of emission points in three-gamma (3-{\gamma})positron emission tomography (PET) imaging using \b{eta}+ and {\gamma}emitters. This approach addresses limitations in existing d
Externí odkaz:
http://arxiv.org/abs/2407.18337
Dosimetry is an essential tool to provide the best and safest radio-therapies to a patient. In this field, Monte-Carlo simulations are considered to be the golden standard for predicting accurately the deposited dose in the body. Such methods are ver
Externí odkaz:
http://arxiv.org/abs/2405.02477
This paper presents a novel approach for learned synergistic reconstruction of medical images using multi-branch generative models. Leveraging variational autoencoders (VAEs), our model learns from pairs of images simultaneously, enabling effective d
Externí odkaz:
http://arxiv.org/abs/2404.08748
Autor:
Cao, Yi-Heng, Bourbonne, Vincent, Lucia, François, Schick, Ulrike, Bert, Julien, Jaouen, Vincent, Visvikis, Dimitris
Objective: Four-dimensional computed tomography (4DCT) imaging consists in reconstructing a CT acquisition into multiple phases to track internal organ and tumor motion. It is commonly used in radiotherapy treatment planning to establish planning tar
Externí odkaz:
http://arxiv.org/abs/2404.00163
Autor:
Vazia, Corentin, Bousse, Alexandre, Froment, Jacques, Vedel, Béatrice, Vermet, Franck, Wang, Zhihan, Dassow, Thore, Tasu, Jean-Pierre, Visvikis, Dimitris
This paper proposes a novel approach to spectral computed tomography (CT) material decomposition that uses the recent advances in generative diffusion models (DMs) for inverse problems. Spectral CT and more particularly photon-counting CT (PCCT) can
Externí odkaz:
http://arxiv.org/abs/2403.10183
Autor:
Vazia, Corentin, Bousse, Alexandre, Vedel, Béatrice, Vermet, Franck, Wang, Zhihan, Dassow, Thore, Tasu, Jean-Pierre, Visvikis, Dimitris, Froment, Jacques
Using recent advances in generative artificial intelligence (AI) brought by diffusion models, this paper introduces a new synergistic method for spectral computed tomography (CT) reconstruction. Diffusion models define a neural network to approximate
Externí odkaz:
http://arxiv.org/abs/2403.06308
Autor:
Mellak, Youness, Chatzipapas, Konstantinos, Bousse, Alexandre, Rest, Catherine Chez-Le, Visvikis, Dimitris, Bert, Julien
In recent years, the use of Monte Carlo (MC) simulations in the domain of Medical Physics has become a state-of-the-art technology that consumes lots of computational resources for the accurate prediction of particle interactions. The use of generati
Externí odkaz:
http://arxiv.org/abs/2403.06307
Autor:
Bousse, Alexandre, Kandarpa, Venkata Sai Sundar, Shi, Kuangyu, Gong, Kuang, Lee, Jae Sung, Liu, Chi, Visvikis, Dimitris
Low-dose emission tomography (ET) plays a crucial role in medical imaging, enabling the acquisition of functional information for various biological processes while minimizing the patient dose. However, the inherent randomness in the photon counting
Externí odkaz:
http://arxiv.org/abs/2401.00232
Autor:
Wang, Zhihan, Bousse, Alexandre, Vermet, Franck, Froment, Jacques, Vedel, Béatrice, Perelli, Alessandro, Tasu, Jean-Pierre, Visvikis, Dimitris
Spectral computed tomography (CT) offers the possibility to reconstruct attenuation images at different energy levels, which can be then used for material decomposition. However, traditional methods reconstruct each energy bin individually and are vu
Externí odkaz:
http://arxiv.org/abs/2311.00666
Autor:
Ronrick Da-ano, Gustavo Andrade-Miranda, Olena Tankyevych, Dimitris Visvikis, Pierre-Henri Conze, Catherine Cheze Le Rest
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Programmed death-ligand 1 (PD-L1) expressions play a crucial role in guiding therapeutic interventions such as the use of tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) in lung cancer. Conventional determination of
Externí odkaz:
https://doaj.org/article/2fb3cf78fc2c46258fb325ade1006fe9