10 citations · 11 across the 6 of their papers we have counts for
5 papers · 1 filter
SomaNet: Weakly Supervised Learning for Instance Soma Segmentation in 3D Electron Microscopy with Partial Annotations
Mohammad Khateri, Morteza Ghahremani, Jussi Tohka +1
Soma instance segmentation, i.e., identifying and delineating individual cell somas as distinct instances, is crucial for cellular analysis and connectomic reconstruction. Three-di…
USFetal: Tools for Fetal Brain Ultrasound Compounding
Mohammad Khateri, Morteza Ghahremani, Sergio Valencia +5
Ultrasound offers a safe, cost-effective, and widely accessible technology for fetal brain imaging, making it especially suitable for routine clinical use. However, it suffers from…
MRI Super-Resolution with Deep Learning: A Comprehensive Survey
Mohammad Khateri, Serge Vasylechko, Morteza Ghahremani +9
High-resolution (HR) magnetic resonance imaging (MRI) is crucial for many clinical and research applications. However, achieving it remains costly and constrained by technical trad…
Self-Supervised Super-Resolution Approach for Isotropic Reconstruction of 3D Electron Microscopy Images from Anisotropic Acquisition
Mohammad Khateri, Morteza Ghahremani, Alejandra Sierra +1
Three-dimensional electron microscopy (3DEM) is an essential technique to investigate volumetric tissue ultra-structure. Due to technical limitations and high imaging costs, sample…
Adversarial Distortion Learning for Medical Image Denoising
Morteza Ghahremani, Mohammad Khateri, Alejandra Sierra +1
We present a novel adversarial distortion learning (ADL) for denoising two- and three-dimensional (2D/3D) biomedical image data. The proposed ADL consists of two auto-encoders: a d…