A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting.

Rezaeifar, Behzad; Wolfs, Cecile J A; Lieuwes, Natasja G; Biemans, Rianne; Reniers, Brigitte; Dubois, Ludwig J; Verhaegen, Frank

Rezaeifar, Behzad; Wolfs, Cecile J A; Lieuwes, Natasja G; Biemans, Rianne; Reniers, Brigitte; Dubois, Ludwig J; Verhaegen, Frank.

Afiliação

Rezaeifar B; Department of Radiation Oncology (Maastro), GROW-School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands.
Wolfs CJA; Research group NuTeC, Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.
Lieuwes NG; Department of Radiation Oncology (Maastro), GROW-School for Oncology and Reproduction, Maastricht University Medical Centre+, Maastricht, The Netherlands.
Biemans R; The M-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.
Reniers B; The M-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.
Dubois LJ; Research group NuTeC, Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.
Verhaegen F; The M-Lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands.

Phys Med Biol ; 67(14)2022 07 08.

Article em En | MEDLINE | ID: mdl-35714611

Assuntos

Aprendizado Profundo; Glioblastoma; Animais; Glioblastoma/diagnóstico por imagem; Glioblastoma/patologia; Glioblastoma/radioterapia; Método de Monte Carlo; Redes Neurais de Computação; Ratos; Tomografia

Palavras-chave

3D convolutional neural network; Monte Carlo simulation; bioluminescence tomography reconstruction; center of mass; deep learning; small animal precision radiotherapy; transfer learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Glioblastoma / Aprendizado Profundo Tipo de estudo: Health_economic_evaluation / Prognostic_studies Limite: Animals Idioma: En Revista: Phys Med Biol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Holanda País de publicação: Reino Unido

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