2017/06/25 · We evaluate the scalable architecture for brain tumour segmentation and give evidence of its regularisation effect compared to the conventional ...

2017/09/04 · We propose a novel scalable multimodal deep learning architecture using new nested structures that explicitly leverage deep features within or across ...

This aims at making the early layers of the architecture structured and sparse so that the final architecture becomes scalable to the number of modalities. We ...

We evaluate the scalable architecture for brain tumour segmentation and give evidence of its regularisation effect compared to the conventional concatenation ...

2017/06/25 · We evaluate the scalable architecture for brain tumour segmentation and give evidence of its regularisation effect compared to the conventional ...

Bibliographic details on Scalable multimodal convolutional networks for brain tumour segmentation.

Scalable multimodal convolutional networks for brain tumour segmentation. L Fidon, W Li, LC Garcia-Peraza-Herrera, J Ekanayake, N Kitchen, ... MICCAI 2017 ...

Brain tumour segmentation plays a key role in computer-assisted surgery. Deep neural networks have increased the accuracy of automatic segmentation.

2023/10/10 · The proposed model outperforms the state-of-the-art methods in terms of all parameters, achieving a classification accuracy of 99.11%, surpassing other ...

In this paper, a novel 3D multi-threading dilated convolutional network (MTDC-Net) is proposed for the automatic brain tumor segmentation.