A fusion of salient and convolutional features applying healthy templates for MRI brain tumor segmentation
  • Metaadatok
Tartalom: http://real.mtak.hu/149736/
Archívum: REAL
Gyűjtemény: Status = Published
Subject = R Medicine / orvostudomány: R1 Medicine (General) / orvostudomány általában
Subject = R Medicine / orvostudomány: RC Internal medicine / belgyógyászat: RC0254 Neoplasms. Tumors. Oncology (including Cancer) / daganatok, tumorok, onkológia
Type = Article
Cím:
A fusion of salient and convolutional features applying healthy templates for MRI brain tumor segmentation
Létrehozó:
Takács, Petra
Kovács, Levente Attila
Manno-Kovács, Andrea
Dátum:
2021
Téma:
R1 Medicine (General) / orvostudomány általában
RC0254 Neoplasms. Tumors. Oncology (including Cancer) / daganatok, tumorok, onkológia
Tartalmi leírás:
This paper proposes an improved brain tumor segmentation method based on visual saliency features on MRI image volumes. The proposed method introduces a novel combination of multiple MRI modalities used as pseudo-color channels for highlighting the potential tumors. The novel pseudo-color model incorporates healthy templates generated from the MRI slices without tumors. The constructed healthy templates are also used during the training of neural network models. Based on a saliency map built using the pseudo-color templates, combination models are proposed, fusing the saliency map with convolutional neural networks’ prediction maps to improve predictions and to reduce the networks’ eventual overfitting which may result in weaker predictions for previously unseen cases. By introducing the combination technique for deep learning techniques and saliency-based, handcrafted feature models, the fusion approach shows good abstraction capabilities and it is able to handle diverse cases that the networks were less trained for. The proposed methods were tested on the BRATS2015 and BRATS2018 databases, and the quantitative results show that hybrid models (including both trained and handcrafted features) can be promising alternatives for reaching higher segmentation performance. Moreover, healthy templates can provide additional information for the training process, enhancing the prediction performance of neural network models.
Nyelv:
angol
Típus:
Article
PeerReviewed
info:eu-repo/semantics/article
Formátum:
text
Azonosító:
Takács, Petra and Kovács, Levente Attila and Manno-Kovács, Andrea (2021) A fusion of salient and convolutional features applying healthy templates for MRI brain tumor segmentation. MULTIMEDIA TOOLS AND APPLICATIONS: AN INTERNATIONAL JOURNAL, 80. pp. 22533-22550. ISSN 1380-7501
Kapcsolat:
MTMT:31638810 10.1007/s11042-020-09871-w
Létrehozó:
cc_by