Can Cui
Computer Science · Purdue University West Lafayette
Publications
67
Citations
445
Est. group size
~3
Recurring co-author estimate
Active years
18
Publishing since 2009
Can Cui's work focuses on applying machine learning and deep learning methods to medical imaging, especially digital pathology (analysis of tissue slide images) and radiology. Recent projects include using foundation models like the Segment Anything Model for cell and tissue segmentation, dataset distillation for efficient training on medical images, and applying radiomics (extracting quantitative features from medical images) to help distinguish tumor types. The group also explores related methods in areas like diffusion MRI analysis and autonomous vehicle sensing.
Publication output grew substantially from 2017 to a peak around 2022–2023, then slightly declined but has remained relatively active through 2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
Electronic Imaging · 2025
- Dataset distillation in medical imaging: a feasibility study
2025
- Distinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists
PLoS ONE · 2025
- Bridging Cultural Divides in Higher Education: Innovative Strategies for Cross-Cultural Teaching and Inclusive Learning Environments
Lex localis - Journal of Local Self-Government · 2025
- Poster: Connected Vehicle Surveillance
2025
- IRS: Incremental Relationship-guided Segmentation for Digital Pathology
arXiv (Cornell University) · 2025
- Career Interest Assessment: College Students Career Planning Based On Machine Leaning
Journal of Electrical Systems · 2024
- Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis.
PubMed · 2024
- Dataset Distillation in Medical Imaging: A Feasibility Study
arXiv (Cornell University) · 2024
- Glo-In-One-v2: Holistic Identification of Glomerular Cells, Tissues, and Lesions in Human and Mouse Histopathology
arXiv (Cornell University) · 2024
- Score and Distribution Matching Policy: Advanced Accelerated Visuomotor Policies via Matched Distillation
arXiv (Cornell University) · 2024
- Value of loop electrosurgical excision procedure conization and imaging for the diagnosis of papillary squamous cell carcinoma of the cervix
Frontiers in Oncology · 2023
- Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
arXiv (Cornell University) · 2023
- Robust Fiber Orientation Distribution Function Estimation Using Deep Constrained Spherical Deconvolution for Diffusion MRI
arXiv (Cornell University) · 2023
- CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation
arXiv (Cornell University) · 2023
- arXiv (Cornell University)×26
- Zhonghua fangshexian yixue zazhi×2
- 2022 IEEE 5th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)×2
- IEEE Intelligent Transportation Systems Magazine×1
- Electronic Imaging×1
- Shubham Innani
Computer Science · Indiana University
- Abdul Akbar
Computer Science · The Ohio State University
- Brian J. Sanderson
Computer Science · Purdue University West Lafayette
- Anil V. Parwani
Computer Science · The Ohio State University
- Giovanni Lujan
Computer Science · The Ohio State University
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 20, 2026.
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