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1.
Sci Rep ; 14(1): 9784, 2024 04 29.
Artigo em Inglês | MEDLINE | ID: mdl-38684904

RESUMO

Accurate multi-organ segmentation in 3D CT images is imperative for enhancing computer-aided diagnosis and radiotherapy planning. However, current deep learning-based methods for 3D multi-organ segmentation face challenges such as the need for labor-intensive manual pixel-level annotations and high hardware resource demands, especially regarding GPU resources. To address these issues, we propose a 3D proxy-bridged region-growing framework specifically designed for the segmentation of the liver and spleen. Specifically, a key slice is selected from each 3D volume according to the corresponding intensity histogram. Subsequently, a deep learning model is employed to pinpoint the semantic central patch on this key slice, to calculate the growing seed. To counteract the impact of noise, segmentation of the liver and spleen is conducted on superpixel images created through proxy-bridging strategy. The segmentation process is then extended to adjacent slices by applying the same methodology iteratively, culminating in the comprehensive segmentation results. Experimental results demonstrate that the proposed framework accomplishes segmentation of the liver and spleen with an average Dice Similarity Coefficient of approximately 0.93 and a Jaccard Similarity Coefficient of around 0.88. These outcomes substantiate the framework's capability to achieve performance on par with that of deep learning methods, albeit requiring less guidance information and lower GPU resources.


Assuntos
Aprendizado Profundo , Imageamento Tridimensional , Fígado , Baço , Tomografia Computadorizada por Raios X , Fígado/diagnóstico por imagem , Baço/diagnóstico por imagem , Baço/anatomia & histologia , Humanos , Imageamento Tridimensional/métodos , Tomografia Computadorizada por Raios X/métodos , Processamento de Imagem Assistida por Computador/métodos , Algoritmos
2.
Zhonghua Zheng Xing Wai Ke Za Zhi ; 21(2): 85-7, 2005 Mar.
Artigo em Chinês | MEDLINE | ID: mdl-16011188

RESUMO

OBJECTIVE: This paper presents a new method of skeleton reconstruction for oblique facial clefts using autogenous bone of the mandibular outer table. METHODS: In the operation, the mandibular outer table was harvested through the intraoral approach. Assisted with internal rigid fixation technique, the mandibular outer table was used to reconstruct the naso-orbital framework as inlay or onlay bone graft. RESULTS: From 1993 to 2001, seven cases of oblique facial clefts were repaired with mandibular outer table bone graft. Postoperative follow-up for 6 months to 3 years demonstrated that the grafted bone healed well with the adjacent bones. No obvious bone resorption was observed. The facial appearance was improved greatly. CONCLUSIONS: The mandibular outer table, with similar bone density to the calvarium, is easy to harvest without donor site scar. The method is quite ideal for skeleton reconstruction of oblique facial clefts.


Assuntos
Transplante Ósseo , Ossos Faciais/anormalidades , Mandíbula/transplante , Procedimentos de Cirurgia Plástica/métodos , Adolescente , Criança , Feminino , Humanos , Masculino , Osso Nasal/anormalidades , Órbita/anormalidades , Resultado do Tratamento
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