Antoine Leroy

Rigid Registration of Freehand 3D Ultrasound and CT-Scan Kidney Images

This paper presents a method to register a preoperative CT volume to a sparse set of intraoperative US slices. In the context of percutaneous renal puncture, the aim is to transfer a planning information to an intraoperative coordinate system. The spatial position of the US slices is measured by localizing a calibrated probe. Our method consists in optimizing a rigid 6 degree of freedom (DOF) transform by evaluating at each step the similarity between the set of US images and the CT volume. The images have been preprocessed in order to increase the relationship between CT and US pixels. Correlation Ratio turned out to be the most accurate and appropriate similarity measure to be used in a Powell-Brent minimization scheme. Results are compared to a standard rigid point-to-point registration involving segmentation, and discussed.

AID TO PERCUTANEOUS RENAL ACCESS BY VIRTUAL PROJECTION OF THE ULTRASOUND PUNCTURE TRACT ONTO FLUOROSCOPIC IMAGES

BACKGROUND AND PURPOSE Percutaneous renal access in the context of percutaneous nephrolithotomy (PCNL) is a difficult technique, requiring rapid and precise access to a particular calix. We present a computerized system designed to improve percutaneous renal access by projecting the ultrasound puncture tract onto fluoroscopic images. MATERIALS AND METHODS The system consists of a computer and a localizer allowing spatial localization of the position of the various instruments. Without any human intervention, the ultrasound nephrostomy tract is superimposed in real time onto fluoroscopic images acquired in various views. RESULTS We tested our approach by laboratory experiments on a phantom. Also, after approval by our institutions Ethics Committee, we validated this technique in the operating room during PCNL in one patient. CONCLUSION Our system is reliable, and the absence of image-processing procedures makes it robust. We have initiated a prospective study to validate this technique both for PCNL specialists and as a learning tool.

Medical Image Computing and Computer-Aided Medical Interventions Applied to Soft Tissues: Work in Progress in Urology

Until recently, computer-aided medical interventions (CAMI) and medical robotics have focused on rigid and nondeformable anatomical structures. Nowadays, special attention is paid to soft tissues, raising complex issues due to their mobility and deformation. Mini-invasive digestive surgery was probably one of the first fields where soft tissues were handled through the development of simulators, tracking of anatomical structures and specific assistance robots. However, other clinical domains, for instance urology, are concerned. Indeed, laparoscopic surgery, new tumour destruction techniques (e.g., HIFU, radiofrequency, or cryoablation), increasingly early detection of cancer, and use of interventional and diagnostic imaging modalities, recently opened new challenges to the urologist and scientists involved in CAMI. This resulted in the last five years in a very significant increase of research and developments of computer-aided urology systems. In this paper, we propose a description of the main problems related to computer-aided diagnostic and therapy of soft tissues and give a survey of the different types of assistance offered to the urologist: robotization, image fusion, surgical navigation. Both research projects and operational industrial systems are discussed

3-D ultrasound probe calibration for computer-guided diagnosis and therapy

With the emergence of swept-volume ultrasound (US) probes, precise and almost real-time US volume imaging has become available. This offers many new opportunities for computer guided diagnosis and therapy, 3-D images containing significantly more information than 2-D slices. However, computer guidance often requires knowledge about the exact position of US voxels relative to a tracking reference, which can only be achieved through probe calibration. In this paper we present a 3-D US probe calibration system based on a membrane phantom. The calibration matrix is retrieved by detection of a membrane plane in a dozen of US acquisitions of the phantom. Plane detection is robustly performed with the 2-D Hough transformation. The feature extraction process is fully automated, calibration requires about 20 minutes and the calibration system can be used in a clinical context. The precision of the system was evaluated to a root mean square (RMS) distance error of 1.15mm and to an RMS angular error of 0.61°. The point reconstruction accuracy was evaluated to 0.9mm and the angular reconstruction accuracy to 1.79°.