Maryam Parvin MT final talk: Automatic Detection of Bronchoscopes on X-Ray Images
Bronchoscopy plays a pivotal role in early lung cancer detection but poses significant challenges due to its complexity. This thesis introduces an AI-driven pipeline for automatic bronchoscope detection in X-ray images, aiming to streamline airway navigation for clinicians. By leveraging advanced preprocessing techniques, innovative loss functions, and robust post-processing algorithms, the approach demonstrates promising accuracy and efficiency. Discover how this work pushes the boundaries of AI in medical imaging to improve outcomes for patients and clinicians alike!
09
Oct
9:00 am - 10:00 am
A Reasoning Agent for Chest X-ray with Memory – MT Intro Talk by Yipeng Zhang
Thursday
09
Oct
9:00 am - 10:00 am
Cold Diffusion for CT Field-of-View Extension – MT Intro Talk by Qianxin Wang
Thursday
16
Oct
9:00 am - 10:00 am
Deep Learning-based Orientation Estimation in Intraoperative X-Ray Images – MT Intro Talk by Anne Leipertz
Thursday
16
Oct
9:00 am - 10:00 am
Evolving Universal Datasets: Cross-Architecture Generalization via Evolutionary Distillation – MT Intro Talk by Shouqiang Wu
Thursday
23
Oct
9:00 am - 9:45 am
MA Final Talk: Deep Learning for low-dose Computed Tomography CAD systems
Thursday, Conference Room 09.150
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