Yanna Zhao

Papers

Total Citations

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About

Yanna Zhao is a rising researcher in medical image processing and computer-aided diagnosis, with a focus on early cancer detection. Her most-cited work, "Lung nodule pre-diagnosis and insertion path planning for chest CT images" (2023, 11 citations), addresses a critical gap in oncological imaging: the lack of reliable methods for nodule recognition, screening, classification, and detection. Zhao’s key contribution lies in integrating deep learning with path planning for biopsy procedures, offering a dual-purpose framework that not only identifies suspicious nodules but also optimizes insertion trajectories for minimally invasive interventions. This work has immediate clinical relevance, potentially reducing false positives and improving diagnostic accuracy in lung cancer screening. Beyond this flagship paper, Zhao’s research spans thyroid and other cancer imaging, consistently applying AI to enhance early-stage diagnosis. While her citation count is still growing, her innovative approach to combining detection with procedural planning marks a notable achievement in the field. For students and researchers, Zhao’s work exemplifies how computational methods can bridge the gap between image analysis and practical clinical workflows, making her a promising voice in the future of precision oncology.