19 citations · 36 across the 11 of their papers we have counts for
11 papers
Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction
Sadaf Khademi, Shahin Heidarian, Parnian Afshar +4
The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT)…
Multi-Content Time-Series Popularity Prediction with Multiple-Model Transformers in MEC Networks
Zohreh HajiAkhondi-Meybodi, Arash Mohammadi, Ming Hou +4
Coded/uncoded content placement in Mobile Edge Caching (MEC) has evolved as an efficient solution to meet the significant growth of global mobile data traffic by boosting the conte…
Recolouring planar graphs of girth at least five
Valentin Bartier, Nicolas Bousquet, Carl Feghali +3
For a positive integer , the -recolouring graph of a graph has as vertex set all proper -colourings of with two -colourings being adjacent if they differ by the…
CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans
Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou +2
Lung cancer is the leading cause of mortality from cancer worldwide and has various histologic types, among which Lung Adenocarcinoma (LUAC) has recently been the most prevalent on…
Robust Framework for COVID-19 Identification from a Multicenter Dataset of Chest CT Scans
Sadaf Khademi, Shahin Heidarian, Parnian Afshar +8
The objective of this study is to develop a robust deep learning-based framework to distinguish COVID-19, Community-Acquired Pneumonia (CAP), and Normal cases based on chest CT sca…
COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee +5
Novel Coronavirus disease (COVID-19) is a highly contagious respiratory infection that has had devastating effects on the world. Recently, new COVID-19 variants are emerging making…
Human-level COVID-19 Diagnosis from Low-dose CT Scans Using a Two-stage Time-distributed Capsule Network
Parnian Afshar, Moezedin Javad Rafiee, Farnoosh Naderkhani +8
Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negati…
CT-CAPS: Feature Extraction-based Automated Framework for COVID-19 Disease Identification from Chest CT Scans using Capsule Networks
Shahin Heidarian, Parnian Afshar, Arash Mohammadi +4
The global outbreak of the novel corona virus (COVID-19) disease has drastically impacted the world and led to one of the most challenging crisis across the globe since World War I…
COVID-FACT: A Fully-Automated Capsule Network-based Framework for Identification of COVID-19 Cases from Chest CT scans
Shahin Heidarian, Parnian Afshar, Nastaran Enshaei +8
The newly discovered Corona virus Disease 2019 (COVID-19) has been globally spreading and causing hundreds of thousands of deaths around the world as of its first emergence in late…
COVID-CT-MD: COVID-19 Computed Tomography (CT) Scan Dataset Applicable in Machine Learning and Deep Learning
Parnian Afshar, Shahin Heidarian, Nastaran Enshaei +7
Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 1 million lives, since its emergence in late 2019. This high…
COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images
Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani +3
Novel Coronavirus disease (COVID-19) has abruptly and undoubtedly changed the world as we know it at the end of the 2nd decade of the 21st century. COVID-19 is extremely contagious…