Breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. The current procedure allows the clinician to determine the location and extent of a tumor in the patient breast before inserting the needle. However, there are several problems with this procedure: the complex interaction dynamics between the needle force and the breast tissue will likely displace the tumor from its original position, necessitating multiple insertions, causing clinicianspsila fatigue, patient's discomfort, and compromising the integrity of the tissue specimen. In this paper, we present a new concept for real-time manipulation of a tumor using a robotic controller that monitors the image of the tumor to generate appropriate external force to position the tumor at a desired location. The idea here is to demonstrate that it is possible to manipulate a tumor in real time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. Experiments on breast phantoms are presented to demonstrate the essence of this concept. The success of this approach has the potential to reduce the number of attempts a clinician makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, reduce patient discomfort, and eliminate false negative results.

Breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. The current procedure allows the physician to determine the location and extent of a tumor in the patient breast before inserting the needle. However, there are several problems with this procedure: the complex interaction dynamics between the needle force and the breast tissue will likely displace the tumor from its original position necessitating multiple insertions, causing surgeons' fatigue, patient's discomfort, and compromising the integrity of the tissue specimen. In this work, we present a new concept for real-time manipulation of a tumor using a robotic controller that monitors the image of the tumor to generate appropriate external force to position the tumor at a desired location. The idea here is to demonstrate that it is possible to manipulate a tumor in real-time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. A laboratory experiment has been presented on a phantom that demonstrates the essence of this concept. The success of this approach has the potential to reduce the number of attempts a surgeon makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, and reduce patient discomfort.

Breast biopsy guided by imaging techniques such as ultrasound is widely used to evaluate suspicious masses within the breast. Currently, ultrasound imaging does not allow live guidance during breast biopsy. The current procedure allows the physician to determine the location and extent of a tumor in the patient breast before inserting the needle. However, there are several problems with this procedure: the complex interaction dynamics between the needle force and the breast tissue will likely displace the tumor from its original position necessitating multiple insertions, causing surgeons' fatigue, and compromising the structural integrity of the tissue specimen. In this work, we present a new concept for real-time manipulation of a tumor using a robotic force controller that monitors the image of the tumor to generate appropriate force to position the tumor at a desired location. The idea here is to demonstrate that it is possible to manipulate a tumor in real-time by applying controlled external force in an automated way such that the tumor does not deviate from the path of the needle. A laboratory experiment has been presented on a phantom that demonstrates the essence of this concept. The success of this approach has the potential to reduce the number of attempts a surgeon makes to capture the desired tissue specimen, minimize tissue damage, improve speed of biopsy, and reduce patient discomfort.

We propose a new control technique for force control on unknown environments. In particular, the proposed approach overcomes the need for precise estimation of environment parameters, which are needed in many system identification-based force control approaches. This framework uses an artificial neural network (ANN)-based proportional-integral (PI)-gain scheduling direct force controller to track the desired force by adjusting control gains based on online parameter estimation. However, the ANN is tolerant to imprecise estimation of environment parameters. Experimental results are presented to demonstrate the efficacy of the proposed control framework. Finally, the advantages and limitations of the proposed controller are discussed