Real‐time registration of 3D to 2D ultrasound images for image‐guided prostate biopsy

Abstract

The presented method encourages real-time implementation of motion compensation algorithms in prostate biopsy with clinically acceptable registration errors. Continuous motion compensation demonstrated registration accuracy with submillimeter and subdegree error, while performing < 50 ms computation times. Image registration technique approaching the frame rate of an ultrasound system offers a key advantage to be smoothly integrated to the clinical workflow. In addition, this technique could be used further for a variety of image-guided interventional procedures to treat and diagnose patients by improving targeting accuracy.

Towards real‐time free‐hand biopsy navigation

“…To our knowledge, no other approach in this field has used such a large amount of data from real clinical patients to validate their algorithm. From a technical point of view, most of the other methods proposed in the literature like [8,9,18] do not use motorized 3D probes but reconstruct these volumes by combining the data from a localization device and the captured stream of 2D images. This acquisition protocol does not allow them to estimate their ground truth from real 3D data, which in our opinion may introduce an underestimation of out-of-plane displacements.…”

A novel enhanced intensity‐based automatic registration: Augmented reality for visualization and localization cancer tumors

“…In the offline stage, Magnetic Resonance Imaging (MRI) was chosen as the imaging modality to gather pre-operative data (breast tumors and lymph nodes) because it can more accurately distinguish breast cancer tissue from normal breast tissue as compared to CT scans. 6 The pre-operative data went through the segmentation process by masking, cropping, and down sampling techniques. For our purpose, we have done some pre-processing on images such as masking, cropping and down sampling.…”

“…However, it must be noted that the drawback of the Mahmoud et al system is that it requires interaction, albeit minimal, from the medical staff. Specifically, the system requires a surgeon to manually choose landmarks from the pre‐operative data and anchor points from the intra‐operative data.…”

“…Nonetheless, this system does offer possibilities for improvement by altering the algorithms and methods used to produce acceptable registration accuracy and processing time. Gillies et al investigated on improving visualization accuracy in terms of registration accuracy in prostate biopsy surgery. This system used Intensity‐based Automatic Registration (IbAR) using Normalized Cross Correlation (NCC) which achieved an accuracy of 2.5 mm target registration error and a processing time of 36 ± 4 ms.…”

“…Nonetheless, this system does offer possibilities for improvement by altering the (a) (b) (c) algorithms and methods used to produce acceptable registration accuracy and processing time. Gillies et al 6 images, which will be of great significance to the proposed system. [8][9][10] Bernhardt et al 11 proposed a new automatic registration and reconstruction method by aligning the intraoperative CT images with the static endoscopic view.…”