58 citations · 86 across the 8 of their papers we have counts for
8 papers
LARGO: Low-Rank Hypernetwork for Handling Missing Modalities
Niels Vyncke, Pooya Ashtari, Aleksandra Pižurica
Addressing missing modalities is an important challenge in multimodal image analysis and often relies on complex architectures that do not transfer easily to different datasets wit…
FUTON: Fourier Tensor Network for Implicit Neural Representations
Pooya Ashtari, Pourya Behmandpoor, Nikos Deligiannis +1
Implicit neural representations (INRs) have emerged as powerful tools for encoding signals, yet dominant MLP-based designs often suffer from slow convergence, overfitting to noise,…
Deconver: A Deconvolutional Network for Medical Image Segmentation
Pooya Ashtari, Shahryar Noei, Fateme Nateghi Haredasht +4
While convolutional neural networks (CNNs) and vision transformers (ViTs) have advanced medical image segmentation, they face inherent limitations such as local receptive fields in…
Deep Learning-Based Image Compression for Wireless Communications: Impacts on Reliability,Throughput, and Latency
Mostafa Naseri, Pooya Ashtari, Mohamed Seif +3
In wireless communications, efficient image transmission must balance reliability, throughput, and latency, especially under dynamic channel conditions. This paper presents an adap…
Quantization-aware Matrix Factorization for Low Bit Rate Image Compression
Pooya Ashtari, Pourya Behmandpoor, Fateme Nateghi Haredasht +3
Lossy image compression is essential for efficient transmission and storage. Traditional compression methods mainly rely on discrete cosine transform (DCT) or singular value decomp…
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew +55
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable A…
Factorizer: A Scalable Interpretable Approach to Context Modeling for Medical Image Segmentation
Pooya Ashtari, Diana M. Sima, Lieven De Lathauwer +3
Convolutional Neural Networks (CNNs) with U-shaped architectures have dominated medical image segmentation, which is crucial for various clinical purposes. However, the inherent lo…
Supervised Fuzzy Partitioning
Pooya Ashtari, Fateme Nateghi Haredasht, Hamid Beigy
Centroid-based methods including k-means and fuzzy c-means are known as effective and easy-to-implement approaches to clustering purposes in many applications. However, these algor…