| Speech-driven facial reenactment using conditional generative adversarial networks SA Jalalifar, H Hasani, H Aghajan arXiv preprint arXiv:1803.07461, 2018 | 33 | 2018 |
| A brain tumor segmentation framework based on outlier detection using one-class support vector machine A Jalalifar, H Soliman, M Ruschin, A Sahgal, A Sadeghi-Naini 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 24 | 2020 |
| Deep learning of quantitative ultrasound multi-parametric images at pre-treatment to predict breast cancer response to chemotherapy H Taleghamar, SA Jalalifar, GJ Czarnota, A Sadeghi-Naini Scientific reports 12 (1), 2244, 2022 | 23 | 2022 |
| Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI‐based deep learning features SA Jalalifar, H Soliman, A Sahgal, A Sadeghi‐Naini Medical Physics 49 (11), 7167-7178, 2022 | 16 | 2022 |
| A cascaded deep-learning framework for segmentation of metastatic brain tumors before and after stereotactic radiation therapy A Jalalifar, H Soliman, A Sahgal, A Sadeghi-Naini 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 9 | 2020 |
| A self-attention-guided 3D deep residual network with big transfer to predict local failure in brain metastasis after radiotherapy using multi-channel MRI SA Jalalifar, H Soliman, A Sahgal, A Sadeghi-Naini IEEE Journal of Translational Engineering in Health and Medicine 11, 13-22, 2022 | 7 | 2022 |
| Data-efficient training of pure vision transformers for the task of chest x-ray abnormality detection using knowledge distillation SA Jalalifar, A Sadeghi-Naini 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 5 | 2022 |
| Automatic Assessment of Stereotactic Radiation Therapy Outcome in Brain Metastasis Using Longitudinal Segmentation on Serial MRI SA Jalalifar, H Soliman, A Sahgal, A Sadeghi-Naini IEEE Journal of Biomedical and Health Informatics, 2023 | 4 | 2023 |
| Impact of tumour segmentation accuracy on efficacy of quantitative MRI biomarkers of radiotherapy outcome in brain metastasis SA Jalalifar, H Soliman, A Sahgal, A Sadeghi-Naini Cancers 14 (20), 5133, 2022 | 3 | 2022 |
| An attention-guided deep neural network for annotating abnormalities in chest X-ray images: visualization of network decision basis K Saednia, A Jalalifar, S Ebrahimi, A Sadeghi-Naini 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 2 | 2020 |
| An automatic framework for segmentation of brain tumours at Follow-up scans after radiation therapy E Karami, A Jalalifar, M Ruschin, H Soliman, A Sahgal, GJ Stanisz, ... 2019 41st Annual International Conference of the IEEE Engineering in …, 2019 | 2 | 2019 |
| Machine Learning and Quantitative Imaging for the Management of Brain Metastasis SA Jalalifar | | 2022 |
| Radiomics and Its Role in Predicting Radiotherapy Response and Outcome in Brain Metastasis SA Jalalifar, H Soliman, A Sahgal, A Sadeghi-Naini Image-Guided Hypofractionated Stereotactic Radiosurgery, 563-581, 2021 | | 2021 |
Ali Sadeghi-NainiAssociate Professor, Department of Electrical Engineering and Computer Science, York UniversityBestätigte E-Mail-Adresse bei yorku.ca
