Sequential Deep Neural Network Models for Proton Dose Calculation: Comparing LSTM, Transformer and RetNet in a Unified Convolutional Encoder-Decoder Framework

Bucher, Lina

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Home > Publications database > Sequential Deep Neural Network Models for Proton Dose Calculation: Comparing LSTM, Transformer and RetNet in a Unified Convolutional Encoder-Decoder Framework

Bachelor Thesis

DKFZ-2024-02005

Sequential Deep Neural Network Models for Proton Dose Calculation: Comparing LSTM, Transformer and RetNet in a Unified Convolutional Encoder-Decoder Framework

Bucher, L. (Corresponding author)DKFZ*

2024

Bachelorarbeit, Universität Heidelberg, 2024

Note: Bachelorarbeit, Universität Heidelberg, 2024

Contributing Institute(s):

E040 Med. Physik in der Strahlentherapie (E040)

Research Program(s):

315 - Bildgebung und Radioonkologie (POF4-315) (POF4-315)

Appears in the scientific report 2024

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Document types > Theses > Bachelor Theses
Institute Collections > E040
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Record created 2024-10-07, last modified 2024-10-07

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