The MURAB project has the ambition to drastically improve precision and effectiveness of breast biopsies by creating a new paradigm in which the precision of great medical imaging modalities like MRI and ultrasound are combined with the precision of robotics.
Possible breast cancer lesions can be detected during a highly sensitive magnetic resonance (MR) scan. These lesions should then be further investigated with a biopsy to confirm that the lesion is breast cancer. Unfortunately, the MR-environment is highly constricting for robotic guided biopsies. To overcome the MR constrictions the breast is rescanned with an autonomously robotic ultrasound scan, which ensures a high precision scan of the breast. During the robotic ultrasound scan the transducer position and orientation is known so the 2D ultrasound images can be reassembled as 3D ultrasound volume. Both 3D datasets of the MR and ultrasound scans can be fused, which allows for high precision robotic guided biopsies of the lesions detected on the sensitive MR images. The complete robotic procedure results in high precision biopsies of small lesion that cannot be detected by ultrasound scanning alone.
The virtual path is obtained from the 3D MR-dataset, but after the MR scan the patient is moved to the ultrasound scanner. This results in a new orientation of the breast that is similar to the MR-dataset, but not the same. So, the goal of this master thesis is to develop a robotic controller that can follow a virtual path and real-time optimizes the ultrasound image by repositioning the ultrasound transducer relative to the virtual path. The ultrasound transducer is fixed to a medical grade intrinsically passive 7-DOF KUKA LBR Med lightweight robot arm. This will ensure high quality ultrasound acquisition within an intrinsically passive framework that ensures the safety of the patients.