output
20062025
most citedNon-invasive real-time imaging through scattering layers and around corners via speckle correlations

1.2k citations

Showing 2021 · eess.IVShow all

7 papers · 2 filters

eess.IV20212 cited

Echocardiography Segmentation with Enforced Temporal Consistency

Nathan Painchaud, Nicolas Duchateau, Olivier Bernard +1

Convolutional neural networks (CNN) have demonstrated their ability to segment 2D cardiac ultrasound images. However, despite recent successes according to which the intra-observer…

eess.IV20216 cited

Patch vs. Global Image-Based Unsupervised Anomaly Detection in MR Brain Scans of Early Parkinsonian Patients

Verónica Muñoz-Ramírez, Nicolas Pinon, Florence Forbes +2

Although neural networks have proven very successful in a number of medical image analysis applications, their use remains difficult when targeting subtle tasks such as the identif…

eess.IV20214 cited

3D-StyleGAN: A Style-Based Generative Adversarial Network for Generative Modeling of Three-Dimensional Medical Images

Sungmin Hong, Razvan Marinescu, Adrian V. Dalca +4

Image synthesis via Generative Adversarial Networks (GANs) of three-dimensional (3D) medical images has great potential that can be extended to many medical applications, such as,…

eess.IV202110 cited

Bone Surface Reconstruction and Clinical Features Estimation from Sparse Landmarks and Statistical Shape Models: A feasibility study on the femur

Alireza Asvadi, Guillaume Dardenne, Jocelyne Troccaz +1

In this study, we investigated a method allowing the determination of the femur bone surface as well as its mechanical axis from some easy-to-identify bony landmarks. The reconstru…

eess.IV2021

EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation

Yuting He, Rongjun Ge, Xiaoming Qi +6

3D complete renal structures(CRS) segmentation targets on segmenting the kidneys, tumors, renal arteries and veins in one inference. Once successful, it will provide preoperative p…

eess.IV202132 cited

A self-supervised learning strategy for postoperative brain cavity segmentation simulating resections

Fernando Pérez-García, Reuben Dorent, Michele Rizzi +9

Accurate segmentation of brain resection cavities (RCs) aids in postoperative analysis and determining follow-up treatment. Convolutional neural networks (CNNs) are the state-of-th…