output
20172026
most citedInteractive Medical Image Segmentation using Deep Learning with Image-specific Fine-tuning

869 citations

Showing 2018Show all

9 papers · 1 filter

cs.CV2018★ 163 cited

Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation

Guotai Wang, Wenqi Li, Sebastien Ourselin +1

Automatic brain tumor segmentation plays an important role for diagnosis, surgical planning and treatment assessment of brain tumors. Deep convolutional neural networks (CNNs) have…

cs.CV2018★ 7 cited

SurReal: enhancing Surgical simulation Realism using style transfer

Imanol Luengo, Evangello Flouty, Petros Giataganas +3

Surgical simulation is an increasingly important element of surgical education. Using simulation can be a means to address some of the significant challenges in developing surgical…

cs.CV2018

FaceOff: Anonymizing Videos in the Operating Rooms

Evangello Flouty, Odysseas Zisimopoulos, Danail Stoyanov

Video capture in the surgical operating room (OR) is increasingly possible and has potential for use with computer assisted interventions (CAI), surgical data science and within sm…

cs.CV2018★ 477 cited

Weakly-Supervised Convolutional Neural Networks for Multimodal Image Registration

Yipeng Hu, Marc Modat, Eli Gibson +11

One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a…

cs.CV2018★ 672 cited

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

Guotai Wang, Wenqi Li, Michael Aertsen +3

Despite the state-of-the-art performance for medical image segmentation, deep convolutional neural networks (CNNs) have rarely provided uncertainty estimations regarding their segm…

cs.CV2018★ 1 cited

Automated Performance Assessment in Transoesophageal Echocardiography with Convolutional Neural Networks

Evangelos B. Mazomenos, Kamakshi Bansal, Bruce Martin +3

Transoesophageal echocardiography (TEE) is a valuable diagnostic and monitoring imaging modality. Proper image acquisition is essential for diagnosis, yet current assessment techni…