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ORCIDAbolfazl Zargari Khuzani
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2020 – today
- 2021
[c12]Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Gopichandh Danala
, Yuchen Qiu, Bin Zheng:
Detecting COVID-19 infected pneumonia from x-ray images using a deep learning model with image preprocessing algorithm. Medical Imaging: Computer-Aided Diagnosis 2021- [c11]Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan, Sam Teymoori:
Applying a new feature fusion method to classify breast lesions. Medical Imaging: Computer-Aided Diagnosis 2021 - 2020
- [j2]Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu, Bin Zheng:
Improving the performance of CNN to predict the likelihood of COVID-19 using chest X-ray images with preprocessing algorithms. Int. J. Medical Informatics 144: 104284 (2020) - [c10]Rezvan Ezatian, Donya Khaledyan, Kian Jafari, Morteza Heidari, Abolfazl Zargari Khuzani, Najmeh Mashhadi:
Image quality enhancement in wireless capsule endoscopy with Adaptive Fraction Gamma Transformation and Unsharp Masking filter. GHTC 2020: 1-7 - [c9]Donya Khaledyan, Abdolah Amirany, Kian Jafari, Mohammad Hossein Moaiyeri, Abolfazl Zargari Khuzani, Najmeh Mashhadi:
Low-Cost Implementation of Bilinear and Bicubic Image Interpolation for Real-Time Image Super-Resolution. GHTC 2020: 1-5 - [c8]Donya Khaledyan, Mohammad Eshghi, Morteza Heidari, Abolfazl Zargari Khuzani, Najmeh Mashhadi:
A Practical Method for Pupil segmentation in challenging conditions. GHTC 2020: 1-5 - [c7]Abolfazl Zargari Khuzani, Najmeh Mashhadi, Morteza Heidari, Donya Khaledyan:
An approach to human iris recognition using quantitative analysis of image features and machine learning. GHTC 2020: 1-6 - [c6]Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan:
Deep learning denoising for EOG artifacts removal from EEG signals. GHTC 2020: 1-6 - [i3]Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu, Bin Zheng:
Improving performance of CNN to predict likelihood of COVID-19 using chest X-ray images with preprocessing algorithms. CoRR abs/2006.12229 (2020) - [i2]Abolfazl Zargari Khuzani, Najmeh Mashhadi, Morteza Heidari, Donya Khaledyan:
An approach to human iris recognition using quantitative analysis of image features and machine learning. CoRR abs/2009.05880 (2020) - [i1]Najmeh Mashhadi, Abolfazl Zargari Khuzani, Morteza Heidari, Donya Khaledyan:
Deep learning denoising for EOG artifacts removal from EEG signals. CoRR abs/2009.08809 (2020)
2010 – 2019
- 2019
- [j1]Xuxin Chen, Abolfazl Zargari, Alan B. Hollingsworth, Hong Liu, Bin Zheng, Yuchen Qiu:
Applying a new quantitative image analysis scheme based on global mammographic features to assist diagnosis of breast cancer. Comput. Methods Programs Biomed. 179 (2019) - [c5]Abolfazl Zargari Khuzani, Rakshit Agrawal, Najmeh Mashhadi:
Fire detection in video sequences using a machine learning system and a clustered quantitative image marker. GHTC 2019: 1-5 - [c4]Morteza Heidari, Seyedehnafiseh Mirniaharikandehei, Abolfazl Zargari Khuzani, Wei Qian, Yuchen Qiu, Bin Zheng:
Assessment of a quantitative mammographic imaging marker for breast cancer risk prediction. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2019: 109520X - 2018
- [c3]Morteza Heidari, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu, Bin Zheng:
Improving performance of breast cancer risk prediction using a new CAD-based region segmentation scheme. Medical Imaging: Computer-Aided Diagnosis 2018: 105750P - [c2]Abolfazl Zargari Khuzani, Gopichandh Danala, Morteza Heidari, Yue Du, Najmeh Mashhadi, Yuchen Qiu, Bin Zheng:
Applying a new unequally weighted feature fusion method to improve CAD performance of classifying breast lesions. Medical Imaging: Computer-Aided Diagnosis 2018: 105752L - [c1]Yue Du, Roy Zhang, Abolfazl Zargari, Theresa C. Thai, Camille C. Gunderson, Katherine M. Moxley, Hong Liu, Bin Zheng, Yuchen Qiu:
A performance comparison of low- and high-level features learned by deep convolutional neural networks in epithelium and stroma classification. Medical Imaging: Digital Pathology 2018: 1058116
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