The invention provides a
proton intensity modulated
therapy radiation field direction automatic
planning method,
system and device based on
deep learning and multi-objective optimization, and a storage medium, and the method comprises the steps: inputting a patient medical image, a
tumor target region, an endangered organ structure and a
treatment plan radiation field direction into a pre-trained 3DU-Net model, and obtaining a three-dimensional
radiation field direction probability
distribution diagram; performing Fibonacci spherical sampling to generate a candidate
radiation field direction, calculating a
path length score and an organ-at-
risk avoidance score in each direction, and dynamically weighting and balancing the two scores; a
proton range error and a
patient positioning error are introduced to simulate
dose distribution, target
area coverage and organ-endangering
dose change under the error are evaluated, and a robustness
score is calculated; performing
collision detection on the treatment rack, and rejecting directions which are not reachable or have collision risks; and selecting a direction to encrypt and sample near the direction, and optimizing a final
radiation field direction according to comprehensive scoring results. According to the method, the
radiation field direction can be automatically optimized,
target dose coverage and organ-endangering protection are improved, and the robustness of a
treatment plan to errors is enhanced.