25 citations · 29 across the 3 of their papers we have counts for
5 papers
Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces
Helena Williams, João Pedrosa, Laura Cattani +4
Automatic medical image segmentation via convolutional neural networks (CNNs) has shown promising results. However, they may not always be robust enough for clinical use. Sub-optim…
Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography
Sarah Leclerc, Erik Smistad, João Pedrosa +11
Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has be…
A Novel Deep Learning Based Approach for Left Ventricle Segmentation in Echocardiography: MFP-Unet
Shakiba Moradi, Mostafa Ghelich-Oghli, Azin Alizadehasl +5
Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D ec…
A Low-Rank and Joint-Sparse Model for Ultrasound Signal Reconstruction
Miaomiao Zhang, Ivan Markovsky, Colas Schretter +1
With the introduction of very dense sensor arrays in ultrasound (US) imaging, data transfer rate and data storage became a bottleneck in ultrasound system design. To reduce the amo…
Automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalising neural network
Ester Bonmati, Yipeng Hu, Nikhil Sindhwani +5
Segmentation of the levator hiatus in ultrasound allows to extract biometrics which are of importance for pelvic floor disorder assessment. In this work, we present a fully automat…