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Seyed Ali Jalalifar 0001

Ali Jalalifar 0001

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affiliation: York University, Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, Toronto, ON, Canada

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2020 – today

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2023
[j1]
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Seyed Ali Jalalifar, Hany Soliman, Arjun Sahgal, Ali Sadeghi-Naini:
Automatic Assessment of Stereotactic Radiation Therapy Outcome in Brain Metastasis Using Longitudinal Segmentation on Serial MRI. IEEE J. Biomed. Health Informatics 27(6): 2681-2692 (2023)
2022
[c5]
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Seyed Ali Jalalifar, Ali Sadeghi-Naini:
Data-Efficient Training of Pure Vision Transformers for the Task of Chest X-ray Abnormality Detection Using Knowledge Distillation. EMBC 2022: 1444-1447
2020
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Ali Jalalifar, Hany Soliman, Arjun Sahgal, Ali Sadeghi-Naini:
A Cascaded Deep-Learning Framework for Segmentation of Metastatic Brain Tumors Before and After Stereotactic Radiation Therapy^*. EMBC 2020: 1063-1066
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Ali Jalalifar, Hany Soliman, Mark Ruschin, Arjun Sahgal, Ali Sadeghi-Naini:
A Brain Tumor Segmentation Framework Based on Outlier Detection Using One-Class Support Vector Machine. EMBC 2020: 1067-1070
[c2]
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  - conf/embc/SaedniaJES20
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Khadijeh Saednia, Ali Jalalifar, Shahin Ebrahimi, Ali Sadeghi-Naini:
An Attention-Guided Deep Neural Network for Annotating Abnormalities in Chest X-ray Images: Visualization of Network Decision Basis^*. EMBC 2020: 1258-1261

2010 – 2019

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2019
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Elham Karami, Ali Jalalifar, Mark Ruschin, Hany Soliman, Arjun Sahgal, Greg J. Stanisz, Ali Sadeghi-Naini:
An Automatic Framework for Segmentation of Brain Tumours at Follow-up Scans after Radiation Therapy. EMBC 2019: 463-466

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