Intelligent diagnosis auxiliary method and system based on prostate cancer lesion and storage medium

By constructing a prostate cancer case database and using deep neural network analysis, a three-dimensional probability distribution map was generated, which solved the problem of accurately determining the location of lesions in prostate cancer particle implantation, and improved the accuracy of radioactive particle implantation and treatment efficacy.

CN120853898BActive Publication Date: 2025-11-21TIANJIN YIKANG TECH CO LTD +1
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Patent Information

Application Number
CN202511353465.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-09-22
Publication Date
2025-11-21
Estimated Expiration
2045-09-22

AI Technical Summary

Technical Problem

In existing technologies, it is difficult to accurately determine the location of lesions during prostate cancer particle implantation therapy, leading to excessive local particle implantation and affecting the treatment effect.

Method used

By constructing a large database of prostate cancer cases, deep neural networks are used to analyze the morphology and spread characteristics of lesions, generating a three-dimensional probability distribution map. Combined with vascular distribution and radiation dose distribution, the implantation sites of radioactive particles are accurately determined.

Benefits of technology

It improves the precision of radioactive particle implantation, enhances the killing effect on lesion tissue, slows down or blocks the spread of cancer cells, and improves the treatment effect.

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Abstract

The application discloses a prostate cancer lesion-based intelligent diagnosis auxiliary method and system and a storage medium, relates to the tumor treatment data processing technical field, and comprises the following steps: acquiring current patient case data and image data of a lesion site; searching for and acquiring reference image data sets, statistically analyzing the probability of the lesion tissue appearing at different positions in space based on the reference image data sets, and generating a probability distribution graph of the lesion tissue; calculating and generating a radiation dose distribution graph of the three-dimensional space of the current lesion area according to particle implantation site coordinates; and determining implantation coordinates of superimposed particles according to the probability distribution graph and the radiation dose distribution graph, and marking the implantation coordinates in the image data of the current patient. Through the above scheme, the implantation coordinates of the superimposed particles are determined, the implantation positions of the radioactive particles are more suitable for the distribution of the lesion tissue, the cancer cells of the lesion tissue are killed, the spread of the cancer cells is slowed down or even blocked, and the treatment effect is improved.
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