Freehand 2D Ultrasound Probe Calibration for Image Fusion with 3D MRI/CT

The aim of this work is to implement a simple freehand ultrasound (US) probe calibration technique. This will enable us to visualize US image data during surgical procedures using augmented reality. The performance of the system was evaluated with different experiments using two different pose estimation techniques. A near-millimeter accuracy can be achieved with the proposed approach. The developed system is cost-effective, simple and rapid with low calibration erro

Development of a portable 3D ultrasound imaging system for musculoskeletal tissues

Author name used in this publication: Q. H. HuangAuthor name used in this publication: Y. P. ZhengAuthor name used in this publication: M. H. LuAuthor name used in this publication: Z. R. ChiCentre for Signal Processing, Department of Electronic and Information EngineeringRehabilitation Engineering Centre2004-2005 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

3-D calibration method and algorithm for freehand image of phased array ultrasonic testing

Phased array ultrasonic testing (UT) is an advanced technique applying ultrasound wave vibration theory to detect the flaw in tested materials by imaging. In this research, computer 3-D visualization of the flaw through calibrating the ultrasonic phased array image is proposed. 3-D calibration for ultrasonic phased array image is a procedure to calculate the spatial transformation matrix, spatial relationship between the US image plane and the tracker attached to the UT probe. The calibration method depends on a cross-string phantom and the corresponding algorithm. The phantom with a set of crosses guiding the operator quickly to find the scanning plane. The ten string crosses in the scanning plane provide the coordinates and spatial vectors for the calibration algorithm, thus the calibration algorithm can be realized based on the least-squares fitting method of the homologous points matching. Select the points having different distances and angles with the reference point to calculate the matrix and average them as the final result. The results show that the scanning plane positioning time is no more than 5 s. The precision and the accuracy results are the same as that is obtained through the other published methods in the medical 3-D ultrasound image calibration. The results make the 3-D flaw model reconstruction possible in phased array ultrasonic NDT. It will reduce the difficulties in the flaw recognizing and localization

Towards Computer Aided Management of Kidney Disease

Autosomal dominant polycystic kidney disease (ADPKD) is the fourth most common cause of kidney transplant worldwide accounting for 7-10% of all cases. Although ADPKD usually progresses over many decades, accurate risk prediction is an important task. Identifying patients with progressive disease is vital to providing new treatments being developed and enable them to enter clinical trials for new therapy. Among other factors, total kidney volume (TKV) is a major biomarker predicting the progression of ADPKD. Consortium for Radiologic Imaging Studies in Polycystic Kidney Disease (CRISP) have shown that TKV is an early, and accurate measure of cystic burden and likely growth rate. It is strongly associated with loss of renal function. While ultrasound (US) has proven as an excellent tool for diagnosing the disease; monitoring short-term changes using ultrasound has been shown to not be accurate. This is attributed to high operator variability and reproducibility as compared to tomographic modalities such as CT and MR (Gold standard). Ultrasound has emerged as one of the standout modalities for intra-procedural imaging and with methods for spatial localization has afforded us the ability to track 2D ultrasound in the physical space in which it is being used. In addition to this, the vast amount of recorded tomographic data can be used to generate statistical shape models that allow us to extract clinical value from archived image sets. Renal volumetry is of great interest in the management of chronic kidney diseases (CKD). In this work, we have implemented a tracked ultrasound system and developed a statistical shape model of the kidney. We utilize the tracked ultrasound to acquire a stack of slices that are able to capture the region of interest, in our case kidney phantoms, and reconstruct 3D volume from spatially localized 2D slices. Approximate shape data is then extracted from this 3D volume using manual segmentation of the organ and a shape model is fit to this data. This generates an instance from the shape model that best represents the scanned phantom and volume calculation is done on this instance. We observe that we can calculate the volume to within 10% error in estimation when compared to the gold standard volume of the phantom

Three-dimensional multimodal medical imaging system based on freehand ultrasound and structured light

We propose a three-dimensional (3D) multimodal medical imaging system that combines freehand ultrasound and structured light 3D reconstruction in a single coordinate system without requiring registration. To the best of our knowledge, these techniques have not been combined as a multimodal imaging technique. The system complements the internal 3D information acquired with ultrasound with the external surface measured with the structured light technique. Moreover, the ultrasound probe’s optical tracking for pose estimation was implemented based on a convolutional neural network. Experimental results show the system’s high accuracy and reproducibility, as well as its potential for preoperative and intraoperative applications. The experimental multimodal error, or the distance from two surfaces obtained with different modalities, was 0.12 m

Volume reconstruction of freehand three-dimensional ultrasound using median filters

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Automated ultrasound calibration solution for the Ultrasound Fracture Analysis Scanning System

Ultrasound calibration is an essential element for morphometric three-dimensional (3D) ultrasound medical systems that are equipped with two-dimensional (2D) ultrasound probes (transducers). Such systems have a position sensor that measures the position of a transducer in space. These measurements are used to combine 2D ultrasound scans into a 3D volume for further object reconstruction and visualisation. However, spatial transformation between the scan coordinate system and the position sensor transmitter remains unknown. The calibration procedure provides this transformation, normally obtained by scanning a device with known geometrical properties called ultrasound phantom. The accuracy of the calibration transformation directly influences the 3D reconstruction quality, however the accuracy is not the only quality characteristic of a calibration device. Phantoms vary in construction providing different calibration procedures, speed, number and positions of scans, type of calibration landmarks, automatic or manual data acquisition and segmentation, and many other criteria. The calibration method should be chosen individually for every calibrated system and there is no "one for all" solution. In this work we introduce a novel calibration phantom with a custom calibration procedure designed for the UFASS - the Ultrasound Fracture Analysis Scanning System - an automated scanner for orthopaedic diagnostics. Our method is designed to fulfil the calibration objectives of the UFASS which are not fully covered by any of the standard phantoms. Our phantom is based on spherical landmarks chosen for their support of a number of calibration requirements such as automated data acquisition and segmentation, and a variety of scanning positions and orientations. It consists of 12 small balls that centre coordinates must be measured with the ultrasound probe during the calibration procedure. We suggest and successfully implement a novel method to obtain and process the input ultrasound data from the phantom without manual operations from a user. Our method uses the motion controller of the UFASS to sequentially move the ultrasound probe and obtain parallel sphere slices with a small step. The scan corresponding to the central section is found by matching a circle template of the sphere's radius to each image. The image with the highest cross-correlation with the template is the central sphere section and it's circle centre is the sphere's centre. For the UFASS our method outperforms comparable calibration solutions providing the automated data acquisition and landmarks detection procedure, high calibration speed, low calibration error, and requiring no experience and no expert knowledge from the end user performing the calibration