Publications
380
Citations
22,174
Est. group size
—
Recurring co-author estimate
Active years
20
Publishing since 2007
Spyridon Bakas works at the intersection of medical imaging and artificial intelligence, developing computational methods to analyze brain scans and tissue images for cancer research. Much of the work focuses on brain tumors such as glioma and glioblastoma, including automatic tumor segmentation (outlining tumors in scans), extracting quantitative features from images (radiomics), and linking imaging patterns to genetic and pathological data. There is also a strong emphasis on standardizing and validating these methods so they can be reliably used across different clinics.
Publication activity has grown steadily over the past decade, rising from around a dozen papers a year to a peak of over 60 in 2024, averaging roughly 39 per year over the last five years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- Brain extraction from normal and pathological images: A joint PCA/Image-Reconstruction approach
UNC Libraries · 2026
- The radiogenomic and spatiogenomic landscapes of glioblastoma and their relationship to oncogenic drivers
Communications Medicine · 2025
- Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 2: challenges, opportunities, and recommendations for clinical translation
The Lancet Oncology · 2025
- Response Assessment in Neuro-Oncology (RANO) 2009–2025: Broad scope and implementation—A progress report
Neuro-Oncology · 2025
- Artificial Intelligence for Response Assessment in Pediatric Neuro-Oncology (AI-RAPNO), part 1: review of the current state of the art
The Lancet Oncology · 2025
- GlioMODA: Robust Glioma Segmentation in Clinical Routine
medRxiv · 2025
- Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches
UNC Libraries · 2025
- An 11,000-Study Open-Access Dataset of Longitudinal Magnetic Resonance Images of Brain Metastases
arXiv (Cornell University) · 2025
- Training the next generation of physicians for artificial intelligence-assisted clinical neuroradiology: ASNR MICCAI Brain Tumor Segmentation (BraTS) 2025 Lighthouse Challenge education platform
arXiv (Cornell University) · 2025
- Editorial: Spatiotemporal & AI trends in neuroscience, neuroimaging, and neurooncology
Frontiers in Neuroimaging · 2025
- IMG-96. Association of FET PET tumor volume and radio-pathomic maps of cell density in newly diagnosed glioblastoma patients
Neuro-Oncology · 2025
- Paradoxical Response to Neoadjuvant Therapy in Undifferentiated Pleomorphic Sarcoma: Increased Tumor Size on MRI Associated with Favorable Pathology
Cancers · 2025
- Optimization of deep learning models for inference in low resource environments
Computers in Biology and Medicine · 2025
- Collaborative evaluation for performance assessment of medical imaging applications
Elsevier eBooks · 2025
- List of contributors
Elsevier eBooks · 2025
- Neuro-Oncology×73
- arXiv (Cornell University)×42
- Lecture notes in computer science×29
- Scientific Data×7
- Cancer Research×7
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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