Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques

Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating and tracking. Gating is considered as the current state of the art for precise lung cancer radiotherapy, which irradiates the tumor when it moves into a predefined gating window. Tracking seems to be a next-generation technique, and it operates in a more aggressive fashion by following the tumor position with radiation beam in real time. Existing methods for gating and tracking often rely on observed motion patterns of external surrogates or implanted fiducial markers. However, external surrogates suffer from certain degrees of inaccuracy, and implanted fiducial markers are in limited uses due to the risk of pneumothorax. Therefore, direct tumor targeting techniques without implanting fiducial markers are desired. Previous studies in fluoroscopic markerless targeting are mainly based on template matching method...

• Type: Conference
• Year: 2008
• Where: ICMLA
• Authors: Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconcelos, Steve B. Jiang
• Keywords: Fiducial Markers, Gating, ICMLA 2008, Machine Learning, Tumor