Multiple organ segmentation framework for brain metastasis radiotherapy.
Comput Biol Med
; 177: 108637, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38824789
ABSTRACT
Radiotherapy is a preferred treatment for brain metastases, which kills cancer cells via high doses of radiation meanwhile hardly avoiding damage to surrounding healthy cells. Therefore, the delineation of organs-at-risk (OARs) is vital in treatment planning to minimize radiation-induced toxicity. However, the following aspects make OAR delineation a challenging task extremely imbalanced organ sizes, ambiguous boundaries, and complex anatomical structures. To alleviate these challenges, we imitate how specialized clinicians delineate OARs and present a novel cascaded multi-OAR segmentation framework, called OAR-SegNet. OAR-SegNet comprises two distinct levels of segmentation networks an Anatomical-Prior-Guided network (APG-Net) and a Point-Cloud-Guided network (PCG-Net). Specifically, APG-Net handles segmentation for all organs, where multi-view segmentation modules and a deep prior loss are designed under the guidance of prior knowledge. After APG-Net, PCG-Net refines small organs through the mini-segmentation and the point-cloud alignment heads. The mini-segmentation head is further equipped with the deep prior feature. Extensive experiments were conducted to demonstrate the superior performance of the proposed method compared to other state-of-the-art medical segmentation methods.
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Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Planejamento da Radioterapia Assistida por Computador
/
Neoplasias Encefálicas
Limite:
Humans
Idioma:
En
Revista:
Comput Biol Med
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China