Tumor clinical target region automatic sketching method and system based on conditional random vector field

Abstract

The embodiment of the invention provides a tumor clinical target area automatic sketching method and system based on a conditional random vector field, and the method comprises the following steps: S1, carrying out data discrete operation of an image sequence of a template CT, and generating a binary image of a tumor primary lesion region; s2, preprocessing a read primary lesion tumor data, defining a transfer characteristic function and a state characteristic function in a given data set, training a model, and determining parameters; and S3, reading primary tumor data of a new patient to obtain a corresponding binary image, and continuously iteratively calculating the state transition probability between adjacent voxels from the general tumor target region to the outside according to a set voxel state transition formula, thereby finally obtaining the global tumor probability invasion probability. According to the method, the conditional random vector field is used, the invasion probability of the tumor can be predicted, the radiotherapy clinical target area is automatically determined, and a prediction result is more reasonable and more suitable for the actual clinical situation.

Description

technical field [0001] The present invention relates to the fields of predicting tumor growth and simulating tumor spreading regions, in particular to a method and system for automatically delineating clinical target areas of tumors based on conditional random vector fields. Background technique [0002] In clinical practice, the main ways to treat tumors include surgery, chemotherapy and radiotherapy. Compared with surgery and chemotherapy, radiation therapy can reduce trauma and improve the quality of life of patients. During radiotherapy, accurate target volume delineation can effectively improve the treatment dose plan of the tumor target area, while reducing the side effects of radiotherapy, which is crucial to the effect of patient treatment and subsequent quality of life. [0003] At present, some software can provide some automatic target area delineation systems, for example, by expanding the primary tumor area in a certain area in the three-dimensional direction, ...

AI Technical Summary

Problems solved by technology

The problem with the local optimal solution is that in addition to the area of ​​the tumor itself, more anatomical structures around the tumor cannot be paid attention to, which is not suitable for the actual clinical situation.

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