Automated detection of a blood pool in ultrasound images of abdominal trauma.

Ultrasound imaging is commonly used for emergency diagnosis of blunt trauma. Portable scanners are able to provide adequate imaging in remote and dangerous areas; however, medical expertise may not be available in the immediate local area to interpret the acquired images. The presence of pooled blood in the abdomen is a critical clinical symptom after trauma. This article describes an automated algorithm to detect blood pools in ultrasound images of abdominal trauma. The algorithm creates and uses a feature space consisting of local intensities, averaged local gradient magnitudes and second-order central rotation invariant moments. Successful tests were performed with a set of clinical images of a liver-kidney interface covering the Morrison's pouch, which is the most likely space for blood from an abdominal injury to gather. When implemented in a portable scanner, the reported algorithm will provide rapid, on-the-spot detection of trauma-induced blood pooling and advance notice of a significant blunt traumatic injury.

Automated 3-dimensional elastic registration of whole-body PET and CT from separate or combined scanners.

UNLABELLED: Registration and fusion of whole-body functional PET and anatomic CT is significant for accurate differentiation of viable tumors from benign masses, radiotherapy planning and monitoring treatment response, and cancer staging. Whole-body PET and CT acquired on separate scanners are misregistered because of differences in patient positions and orientations, couch shapes, and breathing protocols. Although a combined PET/CT scanner removes many of these misalignments, breathing-related nonrigid mismatches still persist. METHODS: We have developed a new, fully automated normalized mutual information-based 3-dimensional elastic image registration technique that can accurately align whole-body PET and CT images acquired on stand-alone scanners as well as a combined PET/CT scanner. The algorithm morphs the PET image to align spatially with the CT image by generating an elastic transformation field by interpolating quaternions and translations from multiple 6-parameter rigid-body registrations, each obtained for hierarchically subdivided image subvolumes. Fifteen whole-body (spanning thorax and abdomen) PET/CT image pairs acquired separately and 5 image pairs acquired on a combined scanner were registered. The cases were selected on the basis of the availability of both CT and PET images, without any other screening criteria, such as a specific clinical condition or prognosis. A rigorous quantitative validation was performed by evaluating algorithm performance in the context of variability among 3 clinical experts in the identification of up to 32 homologous anatomic landmarks. RESULTS: The average execution time was 75 and 45 min for images acquired using separate scanners and combined scanner, respectively. Visual inspection indicated improved matching of homologous structures in all cases. The mean registration accuracy (5.5 and 5.9 mm for images from separate scanners and combined scanner, respectively) was found comparable to the mean interexpert difference in landmark identification (5.6 +/- 2.4 and 6.6 +/- 3.4 mm, respectively). The variability in landmark identification did not show statistically significant changes on replacing any expert by the algorithm. CONCLUSION: We have presented a new and automated elastic registration algorithm to correct for nonrigid misalignments in whole-body PET/CT images as well as improve the "mechanical" registration of a combined PET/CT scanner. The algorithm performance was on par with the average opinion of 3 experts.

Registration-assisted segmentation of real-time 3-D echocardiographic data using deformable models.

Real-time three-dimensional (3-D) echocardiography is a new imaging modality that presents the unique opportunity to visualize the complex 3-D shape and motion of the left ventricle (LV) in vivo and to measure the associated global and local function parameters. To take advantage of this opportunity in routine clinical practice, automatic segmentation of the LV in the 3-D echocardiographic data, usually hundreds of megabytes large, is essential. We report a new segmentation algorithm for this task. Our algorithm has two distinct stages, initialization of a deformable model and its refinement, which are connected by a dual "voxel + wiremesh" template. In the first stage, mutual-information-based registration of the voxel template with the image to be segmented helps initialize the wiremesh template. In the second stage, the wiremesh is refined iteratively under the influence of external and internal forces. The internal forces have been customized to preserve the nonsymmetric shape of the wiremesh template in the absence of external forces, defined using the gradient vector flow approach. The algorithm was validated against expert-defined segmentation and demonstrated acceptable accuracy. Our segmentation algorithm is fully automatic and has the potential to be used clinically together with real-time 3-D echocardiography for improved cardiovascular disease diagnosis.

Registration of real-time 3-D ultrasound images of the heart for novel 3-D stress echocardiography.

Stress echocardiography is a routinely used clinical procedure to diagnose cardiac dysfunction by comparing wall motion information in prestress and poststress ultrasound images. Incomplete data, complicated imaging protocols and misaligned prestress and poststress views, however, are known limitations of conventional stress echocardiography. We discuss how the first two limitations are overcome via the use of real-time three-dimensional (3-D) ultrasound imaging, an emerging modality, and have called the new procedure "3-D stress echocardiography." We also show that the problem of misaligned views can be solved by registration of prestress and poststress 3-D image sequences. Such images are misaligned because of variations in placing the ultrasound transducer and stress-induced anatomical changes. We have developed a technique to temporally align 3-D images of the two sequences first and then to spatially register them to rectify probe placement error while preserving the stress-induced changes. The 3-D spatial registration is mutual information-based. Image registration used in conjunction with 3-D stress echocardiography can potentially improve the diagnostic accuracy of stress testing.

Mutual information-based multimodality registration of cardiac ultrasound and SPECT images: a preliminary investigation.

BACKGROUND: Ultrasound (US) and single photon emission computed tomography (SPECT) are the two most commonly prescribed procedures for diagnosing coronary artery disease (CAD). We have demonstrated the feasibility of multimodality registration of two-dimensional (2D) and three-dimensional (3D) cardiac US images with cardiac SPECT images with an aim to simultaneously present the complementary anatomical and perfusion information from the two modalities. We have also tested the clinicians' assessment of the clinical adequacy of the registered images. METHODS AND RESULTS: We have demonstrated temporal and spatial registration for nine sets of cardiac US and SPECT cine loops covering the entire cardiac cycle. Temporal alignment was performed by interpolation of existing SPECT images at cardiac phases corresponding to available US images. Spatial registration was performed in 3D image space using a mutual information-based approach. Experts from echocardiography and nuclear medicine determined the clinical utility of the registration by rating each registration on a scale of 1 to 5, a rating of 3 or above indicating clinical utility. 2DUS-SPECT registration (five cases) received an average rating of 4.2, whereas 3DUS-SPECT registration (four cases) received an average rating of 2.85. By one-sample t test, the overall evaluations (mean 3.58) were greater than the pre-specified clinical cut-off of 3 with p < 0.05, indicating likelihood of clinical utility. CONCLUSION: Our method demonstrates the feasibility of registering cardiac US and SPECT images in their present as well as possible future forms. Such registration has the potential to provide a more accurate and powerful tool for diagnosing CAD.

High-speed registration of three- and four-dimensional medical images by using voxel similarity.

A generalized, accurate, automatic, retrospective method of image registration for three-dimensional images has been developed. The method is based on mutual information, a specific measure of voxel similarity, and is applicable to a wide range of imaging modalities and organs, rigid or deformable. A drawback of mutual information-based image registration is long execution times. To overcome the speed problem, low-cost, customized hardware to accelerate this computationally intensive task was developed. Individual hardware accelerator units (each, in principle, 25-fold faster than a comparable software implementation) can be concatenated to perform image registration at any user-desired speed. A first-generation prototype board with two processing units provided a 12- to 16-fold increase in speed. Enhancements for increasing the speed further are being developed. These advances have enabled many nontraditional applications of image registration and have made the traditional applications more efficient. Clinical applications include fusion of computed tomographic (CT), magnetic resonance, and positron emission tomographic (PET) images of the brain; fusion of whole-body CT and PET images; fusion of four-dimensional spatiotemporal ultrasonographic (US) and single photon emission CT images of the heart; and correction of misalignment between pre- and poststress four-dimensional US images.

Cine MPR: interactive multiplanar reformatting of four-dimensional cardiac data using hardware-accelerated texture mapping.

Four-dimensional (4-D) imaging to capture the three-dimensional (3-D) structure and motion of the heart in real time is an emerging trend. We present here our method of interactive multiplanar reformatting (MPR), i.e., the ability to visualize any chosen anatomical cross section of 4-D cardiac images and to change its orientation smoothly while maintaining the original heart motion. Continuous animation to show the time-varying 3-D geometry of the heart and smooth dynamic manipulation of the reformatted planes, as well as large image size (100-300 MB), make MPR challenging. Our solution exploits the hardware acceleration of 3-D texture mapping capability of high-end commercial PC graphics boards. Customization of volume subdivision and caching concepts to periodic cardiac data allows us to use this hardware effectively and efficiently. We are able to visualize and smoothly interact with real-time 3-D ultrasound cardiac images at the desired frame rate (25 Hz). The developed methods are applicable to MPR of one or more 3-D and 4-D medical images, including 4-D cardiac images collected in a gated fashion.

Mutual information-based rigid and nonrigid registration of ultrasound volumes.

We investigated the registration of ultrasound volumes based on the mutual information measure, a technique originally applied to multimodality registration of brain images. A prerequisite for successful registration is a smooth, quasi-convex mutual information surface with an unambiguous maximum. We discuss the necessary preprocessing to create such a surface for ultrasound volumes. Abdominal and thoracic organs imaged with ultrasound typically move relative to the exterior of the body and are deformable. Consequently, four specific instances of image registration involving progressively generalized transformations were studied: rigid-body, rigid-body + uniform scaling, rigid-body + nonuniform scaling, and affine. Registration was applied to clinically acquired volumetric images. The accuracy was comparable with the voxel dimension for all transformation modes, although it degraded as the transformation grew more complex. Likewise, the capture range became narrower with the complexity of transformation. As the use of real-time three-dimensional ultrasound becomes more prevalent, the method we present should work well for a variety of applications examining serial anatomic and physiologic changes. Developers of these clinical applications would match the deformation model of their problem to one of the four transformation models presented here.

Interactive visualization of four-dimensional ultrasound data.

We present a hardware-accelerated method using three-dimensional (3D) textures to visualize four-dimensional (4D) images of the heart. Novel data subdivision and caching ideas enable interactive performance even though 4D data exceed the size of 3D texture memory. The capability to visualize 4D images is critical to continued evolution and clinical acceptance of 4D imaging.