Dr. Banafshe Felfeliyan, Computer-aided Diagnosis, Best Researcher Award
Dr. Banafshe Felfeliyan, Computer-aided Diagnosis, Best Researcher Award
- Doctorate at University of Alberta, Canada
Banafshe Felfeliyan is a highly accomplished researcher in the field of biomedical engineering, specializing in medical imaging and machine learning. With a Ph.D. in Biomedical Engineering from the University of Calgary, Canada, she has demonstrated expertise in developing automated AI biomarkers extraction methods for various medical imaging modalities. Her work focuses on advancing the understanding and diagnosis of conditions like osteoarthritis through the application of deep learning techniques. Felfeliyan’s professional journey includes roles as a Postdoctoral Research Fellow at the University of Alberta and as a Computer Research Engineer at the McCaig Institute, University of Calgary. She has received numerous honors and awards for her contributions to the field, including prestigious fellowships and scholarships. Felfeliyan has made significant contributions to the scientific community through her publications, presentations, and mentorship activities, showcasing her leadership and commitment to advancing biomedical engineering research.
Author Metrics:
Felfeliyan’s research output is characterized by high-quality publications in top-tier journals and conferences in the field of biomedical engineering. Her work has garnered attention and citations from peers, indicating its impact and relevance within the scientific community.
Citations:
- Felfeliyan’s work has been cited 105 times in scholarly publications.
Documents:
- She has authored 11 documents in various journals and conference proceedings.
h-index:
- Her h-index, a metric indicating both the productivity and citation impact of her published work, stands at 5.
Banafshe Felfeliyan’s author metrics reflect a significant contribution to the field of biomedical engineering, particularly in the areas of medical imaging and machine learning.
Education:
Banafshe Felfeliyan pursued her academic journey with a strong focus on engineering and biomedical sciences. She completed her Ph.D. in Biomedical Engineering, specializing in medical imaging, at the University of Calgary, Canada. Prior to that, she obtained her Master’s and Bachelor’s degrees in Computer Engineering from Isfahan University of Technology, Iran.
Research Focus:
Felfeliyan’s research primarily revolves around the intersection of medical imaging and machine learning. Her work involves the development and optimization of deep learning models for automated AI biomarker extraction from various medical imaging modalities. She is particularly interested in areas such as automated quantification of osteoarthritis features, domain adaptation, semi-supervised learning, and vision-language processing in the context of medical imaging.
Professional Journey:
Banafshe Felfeliyan has had a distinguished professional journey, starting as a Computer Research Engineer at the McCaig Institute, University of Calgary. She then transitioned to a Postdoctoral Research Fellow position at the Radiology & Diagnostic Imaging Department, University of Alberta, where she leads projects focused on developing automated AI biomarker profiles for osteoarthritis. Throughout her career, she has collaborated with multidisciplinary teams, mentored students, and delivered results at peer-reviewed conferences.
Honors & Awards:
Felfeliyan has been recognized with several prestigious honors and awards for her outstanding contributions to biomedical engineering research. These include the Alberta Innovates Postdoctoral Recruitment Fellowship, Biomedical Engineering Research Excellence Award, AI Week Talent Bursary from the Alberta Machine Intelligence Institute (AMII), and various scholarships throughout her academic journey.
Publications Top Noted & Contributions:
Banafshe Felfeliyan has made significant contributions to the scientific community through her publications and presentations. Her research papers span reputable journals and conferences, covering topics such as automated quantification of medical imaging features, vision-language models for assessing osteoarthritis, and self-supervised learning for medical image segmentation.
Title: Vessel extraction in X-ray angiograms using deep learning
Authors: E Nasr-Esfahani, S Samavi, N Karimi, SMR Soroushmehr, K Ward, …
Conference: 2016 38th Annual international conference of the IEEE engineering in …
Citations: 90
Year: 2016
Title: Vessel segmentation in low contrast x-ray angiogram images
Authors: B Felfelian, HR Fazlali, N Karimi, SMR Soroushmehr, S Samavi, …
Conference: IEEE International Conference on Image Processing (ICIP) 2016
Citations: 20
Year: 2016
Authors: B Felfeliyan, A Hareendranathan, G Kuntze, JL Jaremko, JL Ronsky
Journal: Computerized Medical Imaging and Graphics
Citations: 15
Year: 2022
Title: Liver segmentation in abdominal CT images using probabilistic atlas and adaptive 3D region growing
Authors: S Rafiei, N Karimi, B Mirmahboub, K Najarian, B Felfeliyan, S Samavi, …
Conference: 2019 41st annual international conference of the IEEE engineering in …
Citations: 14
Year: 2019
Authors: B Felfeliyan, A Hareendranathan, G Kuntze, J Jaremko, J Ronsky
Conference: 2021 43rd Annual International Conference of the IEEE Engineering in …
Research Timeline:
Banafshe Felfeliyan’s research timeline showcases a progressive journey of academic and professional growth. Starting from her undergraduate studies in computer engineering, she has continuously expanded her expertise in biomedical engineering through her Master’s and Ph.D. studies. Her professional journey includes roles as a research engineer and postdoctoral fellow, where she has contributed significantly to advancing the field of medical imaging and machine learning.