Automatic tracking of gold seed markers from CBCT image projections in lung and prostate radiotherapy

• A low-cost model to track markers from CBCT projections.
• Edge detection algorithms with filtering and discreet cosine transforms.
• Capable of processing Varian and Elekta images.
• Data collected for 12 prostate patients and 1 lung patient.
• Model accuracy dependant on the localisation of excessive bony anatomy.

PurposeTo construct a method and software to track gold seed implants in prostate and lung patients undergoing radiotherapy using CBCT image projections.MethodsA mathematical model was developed in the MatLab (Mathworks, Natick, USA) environment which uses a combination of discreet cosine transforms and filtering to enhance several edge detection methods for identifying and tracking gold seed fiducial markers in images obtained from Varian (Varian Medical Systems, Palo Alto, USA) and Elekta (Kungstensgatan, Sweden) CBCT projections.ResultsOrgan motion was captured for 16 prostate patients and 1 lung patient.ConclusionImage enhancement and edge detection is capable of automatically tracking markers for up to 98% (Varian) and 79% (Elekta) of CBCT projections for prostate and lung markers however inclusion of excessive bony anatomy (LT and RT LAT) inhibit the ability of the model to accurate determine marker location.