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20172021
most citedReal-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking

92 citations · 121 across the 6 of their papers we have counts for

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9 papers · 1 filter

cs.CV2021

FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Dataset

Sophia Bano, Alessandro Casella, Francisco Vasconcelos +9

Fetoscopy laser photocoagulation is a widely used procedure for the treatment of Twin-to-Twin Transfusion Syndrome (TTTS), that occur in mono-chorionic multiple pregnancies due to…

cs.CV2021

MIDeepSeg: Minimally Interactive Segmentation of Unseen Objects from Medical Images Using Deep Learning

Xiangde Luo, Guotai Wang, Tao Song +6

Segmentation of organs or lesions from medical images plays an essential role in many clinical applications such as diagnosis and treatment planning. Though Convolutional Neural Ne…

cs.CV2020

Active Annotation of Informative Overlapping Frames in Video Mosaicking Applications

Loic Peter, Marcel Tella-Amo, Dzhoshkun Ismail Shakir +4

Video mosaicking requires the registration of overlapping frames located at distant timepoints in the sequence to ensure global consistency of the reconstructed scene. However, ful…

cs.CV202092 cited

Real-Time Segmentation of Non-Rigid Surgical Tools based on Deep Learning and Tracking

Luis C. García-Peraza-Herrera, Wenqi Li, Caspar Gruijthuijsen +7

Real-time tool segmentation is an essential component in computer-assisted surgical systems. We propose a novel real-time automatic method based on Fully Convolutional Networks (FC…

cs.CV2020

Deep Placental Vessel Segmentation for Fetoscopic Mosaicking

Sophia Bano, Francisco Vasconcelos, Luke M. Shepherd +6

During fetoscopic laser photocoagulation, a treatment for twin-to-twin transfusion syndrome (TTTS), the clinician first identifies abnormal placental vascular connections and laser…

cs.CV2018

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…