Name
Title | ||
|---|---|---|
A LESS SUPERVISED AUTOMATIC DELINEATION METHOD FOR INTRACRANIAL GERM CELL TUMOR RADIOTHERAPY TARGETS |
Abstract | ||
|---|---|---|
Central nervous system germ cell tumor is one of the most common intracranial malignant tumors in children. Currently, radiotherapy is the main treatment method. Local tumor and whole ventricular system irradiation can ensure the curative effect while reducing radiation damage in the late stage of radiotherapy. However, it is time-consuming and laborious for doctors to manually delineate the ventricular system. Therefore, this research proposed a less supervised automatic delineation method for intracranial germ cell tumor radiotherapy targets. By integrating the idea of unsupervised image registration, it has fast segmentation speed and avoids the dependence of supervised learning methods on extensive labeled data. The average target delineation accuracy can reach 80.5% and the average time is 153.42s when only one set of annotated data is required. The proposed algorithm can assist doctors in radiotherapy target delineation and has the potential to be extended to actual clinical applications. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/ISBI52829.2022.9761416 | 2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022) |
Keywords | DocType | ISSN |
Intracranial germ cell tumor, radiotherapy target area, less supervised learning, deformable image registration, conditional random filed | Conference | 1945-7928 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianyu Wang | 1 | 0 | 0.34 |
| Shuai Liu | 2 | 0 | 0.34 |
| Ne Yang | 3 | 0 | 0.34 |
| Guochen Ning | 4 | 3 | 2.75 |
| Longfei Ma | 5 | 0 | 0.34 |
| Hui Zhang | 6 | 0 | 0.34 |
| Hongen Liao | 7 | 0 | 0.34 |