Isfahan Artificial Intelligence Event 2023: Lesion Segmentation and Localization in Magnetic Resonance Images of Patients with Multiple Sclerosis
The results show that deep learning methods can be useful for segmentation and localization of lesions in MR images. In this study, we briefly described the dataset and the methods of teams attending the competition.
Authors
- Iman Adibi (ORCID: https://orcid.org/0000-0003-4409-9404)
- Ahmadreza Montazerolghaem (ORCID: https://orcid.org/0000-0003-4968-2375)
- Nasrin Sharifi (ORCID: https://orcid.org/0000-0002-6849-7653)
- Sadaf Moharreri (ORCID: https://orcid.org/0000-0002-1781-476X)
- Hossein Rabbani (ORCID: https://orcid.org/0000-0002-0551-3636)
- Farnaz Sedighin (ORCID: https://orcid.org/0000-0002-0384-3981)
- Maryam Monemian (ORCID: https://orcid.org/0000-0002-3449-2408)
- Kian Shahriari
- Mahnoosh Tajmirriahi (ORCID: https://orcid.org/0000-0002-5477-754X)
- Fariba Davanian (ORCID: https://orcid.org/0000-0001-8623-6791)
- Mohammad Reza Iravani (ORCID: https://orcid.org/0000-0003-2115-6912)
- Zahra Zojaji (ORCID: https://orcid.org/0000-0003-0921-0170)
- Mohammad Kazemi (ORCID: https://orcid.org/0000-0003-1139-3076)
- Mohammad Amin Asadinia
- Seyed Mojtaba Mirghaderi
- Seyed Amin Naji Esfahani
Institutions
- Isfahan University of Medical Sciences (IR)
- Islamic Azad University, Science and Research Branch (IR)
- Isfahan University of Technology (IR)
- Islamic Azad University of Khomeynishahr (IR)
- University of Isfahan (IR)
- K. N. Toosi University of Technology (IR)
Publication Details
- Journal
- Journal of Medical Signals & Sensors
- Published
- 2025-02-01
- DOI
- https://doi.org/10.4103/jmss.jmss_55_24
- Citations
- 1
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.47