Search Results for author: Seyed Sadegh Mohseni Salehi

Found 8 papers, 3 papers with code

Deep Predictive Motion Tracking in Magnetic Resonance Imaging: Application to Fetal Imaging

2 code implementations25 Sep 2019 Ayush Singh, Seyed Sadegh Mohseni Salehi, Ali Gholipour

Nevertheless, visual monitoring of fetal motion based on displayed slices, and navigation at the level of stacks-of-slices is inefficient.

3D Object Reconstruction Image Registration +2

Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection

no code implementations28 Mar 2018 Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour

One of the major challenges in training such networks raises when data is unbalanced, which is common in many medical imaging applications such as lesion segmentation where lesion class voxels are often much lower in numbers than non-lesion voxels.

Data Augmentation Image Segmentation +3

Real-time Deep Pose Estimation with Geodesic Loss for Image-to-Template Rigid Registration

no code implementations15 Mar 2018 Seyed Sadegh Mohseni Salehi, Shadab Khan, Deniz Erdogmus, Ali Gholipour

Our results show that in such registration applications that are amendable to learning, the proposed deep learning methods with geodesic loss minimization can achieve accurate results with a wide capture range in real-time (<100ms).

3D Pose Estimation Anatomy +1

Tversky loss function for image segmentation using 3D fully convolutional deep networks

2 code implementations18 Jun 2017 Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Ali Gholipour

One of the main challenges in training these networks is data imbalance, which is particularly problematic in medical imaging applications such as lesion segmentation where the number of lesion voxels is often much lower than the number of non-lesion voxels.

Image Segmentation Lesion Segmentation +1

Cannot find the paper you are looking for? You can Submit a new open access paper.