Automatic delineation system of pelvic tumor ctv based on deep learning

Abstract

The invention discloses an automatic delineation system for pelvic tumor CTV based on deep learning, which is suitable for pelvic lymphatic drainage area, cervical cancer CTV and rectal cancer CTV. The automatic delineation system includes the following steps: Step S1: Collect CT image data and clinical The doctor marks the drainage area and preprocesses the image data; step S2: constructs the deep learning segmentation model of the drainage area; step S3: after the processing of steps S1 and S2, the CT image data and the image of the drainage area marked by the clinician are input into the network, Train the network to obtain the partition contour; step S4: automatically generate the cervical cancer CTV contour through the partition contour; and step S5: automatically generate the rectal cancer CTV contour through the partition contour. The automatic delineation system of the present invention can assist doctors in delineating cervical cancer CTV and rectal cancer CTV according to the patient's condition and staging situation, and the introduced dense network can effectively improve the identification ability of pelvic lymphatic drainage area.

Description

technical field [0001] The invention relates to the fields of medical imaging and computer technology, in particular to an automatic delineation system for pelvic lymphatic drainage area, cervical cancer CTV and rectal cancer CTV in CT images based on a deep learning network. Background technique [0002] In the field of radiotherapy, accurate delineation of cervical cancer CTV (tumor target volume) and rectal cancer CTV has important clinical significance. During the delineation of cervical cancer CTV and rectal cancer CTV, clinicians must refer to the pelvic lymphatic drainage area, and consider the patient's clinical stage and treatment plan for CTV delineation. In addition, when clinicians delineate the target area, they should also delineate the pelvic lymphatic drainage area. Therefore, the automatic delineation of pelvic lymphatic drainage area, cervical cancer CTV and rectal cancer CTV has very important clinical significance. [0003] At present, the mediastinal d...

AI Technical Summary

Problems solved by technology

This traditional manual method has the following disadvantages: first, manual sketching consumes a lot of time, and it often takes several hours to draw a patient; second, the sketching is prone to objective errors, which are difficult to detect and easily cause medical accidents

Fourth, different doctors have different subjective understandings when considering the clinical stage and treatment plan of the same patient, resulting in inconsistencies in the sketching style

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