no code implementations • 27 Oct 2022 • Sadaf Khademi, Shahin Heidarian, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos Plataniotis, Arash Mohammadi
The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT) slices to predict Lung Adenocarcinoma (LUAC) malignancy with minimum expert involvement.
no code implementations • 12 Oct 2022 • Zohreh Hajiakhondi-Meybodi, Arash Mohammadi, Ming Hou, Elahe Rahimian, Shahin Heidarian, Jamshid Abouei, Konstantinos N. Plataniotis
Most existing datadriven popularity prediction models, however, are not suitable for the coded/uncoded content placement frameworks.
no code implementations • 1 Dec 2021 • Zohreh Hajiakhondi Meybodi, Arash Mohammadi, Elahe Rahimian, Shahin Heidarian, Jamshid Abouei, Konstantinos N. Plataniotis
As a consequence of the COVID-19 pandemic, the demand for telecommunication for remote learning/working and telemedicine has significantly increased.
no code implementations • 17 Oct 2021 • Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
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 one.
no code implementations • 19 Sep 2021 • Sadaf Khademi, Shahin Heidarian, Parnian Afshar, Nastaran Enshaei, Farnoosh Naderkhani, Moezedin Javad Rafiee, Anastasia Oikonomou, Akbar Shafiee, Faranak Babaki Fard, Konstantinos N. Plataniotis, Arash Mohammadi
We showed that while our proposed model is trained on a relatively small dataset acquired from only one imaging center using a specific scanning protocol, the model performs well on heterogeneous test sets obtained by multiple scanners using different technical parameters.
no code implementations • 4 Jul 2021 • Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee, Parnian Afshar, Shahin Heidarian, Arash Mohammadi, Konstantinos N. Plataniotis, Farnoosh Naderkhani
In this context, first, the paper introduces an open access COVID-19 CT segmentation dataset containing 433 CT images from 82 patients that have been annotated by an expert radiologist.
1 code implementation • 31 May 2021 • Parnian Afshar, Moezedin Javad Rafiee, Farnoosh Naderkhani, Shahin Heidarian, Nastaran Enshaei, Anastasia Oikonomou, Faranak Babaki Fard, Reut Anconina, Keyvan Farahani, Konstantinos N. Plataniotis, Arash Mohammadi
The AI model achieves COVID-19 sensitivity of 89. 5% +\- 0. 11, CAP sensitivity of 95% +\- 0. 11, normal cases sensitivity (specificity) of 85. 7% +\- 0. 16, and accuracy of 90% +\- 0. 06.
1 code implementation • 30 Oct 2020 • Shahin Heidarian, Parnian Afshar, Arash Mohammadi, Moezedin Javad Rafiee, Anastasia Oikonomou, Konstantinos N. Plataniotis, Farnoosh Naderkhani
Capsule Networks, on the other hand, can capture spatial relations, require smaller datasets, and have considerably fewer parameters.
1 code implementation • 30 Oct 2020 • Shahin Heidarian, Parnian Afshar, Nastaran Enshaei, Farnoosh Naderkhani, Anastasia Oikonomou, S. Farokh Atashzar, Faranak Babaki Fard, Kaveh Samimi, Konstantinos N. Plataniotis, Arash Mohammadi, Moezedin Javad Rafiee
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 2019.
3 code implementations • 28 Sep 2020 • Parnian Afshar, Shahin Heidarian, Nastaran Enshaei, Farnoosh Naderkhani, Moezedin Javad Rafiee, Anastasia Oikonomou, Faranak Babaki Fard, Kaveh Samimi, Konstantinos N. Plataniotis, Arash Mohammadi
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.
2 code implementations • 6 Apr 2020 • Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
Pre-training with a dataset of similar nature further improved accuracy to 98. 3% and specificity to 98. 6%.