Titlebook: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries; 4th International Wo Alessandro Crimi,Spyridon Bakas,Theo van

赞美者

JIBE

Simultaneous Decisions: Cold-Turkey Policies models, it obtains a testing accuracy of . without any additional effort towards extraction and selection of features. We also study the properties of self-learned kernels/filters in different layers, through visualization of the intermediate layer outputs.

incisive

Patrimony

Multipath Densely Connected Convolutional Neural Network for Brain Tumor Segmentationomplete segmentation network. The model’s training and validation are performed on the BraTS2017 dataset. Experimental results demonstrate that the proposed network is capable to effectively extract more accurate tumor locations and contours with improved stability.

公司

Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Braiodal brain scans is similar to that of models trained by sharing data (Dice = 0.862). We compare federated learning with two alternative collaborative learning methods and find that they fail to match the performance of federated learning.

碌碌之人

Shallow vs Deep Learning Architectures for White Matter Lesion Segmentation in the Early Stages of Mshallow architecture yields the best Dice coefficient (63%) and volume difference (19%). Combining both shallow and deep architectures further improves the lesion-wise metrics (69% and 26% lesion-wise true and false positive rate, respectively).