Automatic elastic image registration by interpolation of 3D rotations and translations from discrete rigid-body transformations

Walimbe, Vivek; Shekhar, Raj

doi:10.1016/j.media.2006.09.002

Cited by 44 publications

(44 citation statements)

References 36 publications

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“…Walimbe and Shekhar [60,67] Chapter 6, we demonstrate fast and successful registration of intraprocedural abdominal CT scans with preprocedural CT and PET scans using the developed…”

Section: Motivationmentioning

confidence: 94%

“…More recently, some algorithms based on hierarchical image subdivision approaches have been reported [59,60]. These algorithms achieve deformable registration through registering image subvolumes using a locally linear transformation and then applying quaternion-based interpolation to obtain the transformation field.…”

Section: Deformable Modelsmentioning

confidence: 99%

“…3D image registration using volume subdivision has been proposed earlier, but the earlier implementations were limited to a locally translation-based model. Walimbe and Shekhar [60,67] The optimal alignment of the subvolume j within the FI is also determined by maximizing MI under a six-parameter rigid-body transformation model.…”

Section: Algorithm For Deformable Image Registrationmentioning

confidence: 99%

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High-Performance 3D Image Processing Architectures for Image-Guided Interventions

Dandekar¹

2008

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Minimally invasive image-guided interventions (IGIs) are time and cost efficient, minimize unintended damage to healthy tissues, and lead to faster patient recovery. Advanced three-dimensional (3D) image processing is a critical need for navigation during IGIs. However, achieving on-demand performance, as required by IGIs, for these image processing operations using software-only implementations is challenging because of the sheer size of the 3D images, and memory and compute intensive nature of the operations. This dissertation, therefore, is geared toward developing high-performance 3D image processing architectures, which will enable improved intraprocedural visualization and navigation capabilities during IGIs.In this dissertation we present an architecture for real-time implementation of 3D filtering operations that are commonly employed for preprocessing of medical images. This architecture is approximately two orders of magnitude faster than corresponding software implementations and is capable of processing 3D medical images at their acquisition speeds. Report Documentation PageCombining complementary information through registration between pre-and intraprocedural images is a fundamental need in the IGI workflow. Intensity-based deformable registration, which is completely automatic and locally accurate, is a promising approach to achieve this alignment. These algorithms, however, are extremely compute intensive, which has prevented their clinical use. We present an FPGA-based architecture for accelerated implementation of intensity-based deformable image registration. This high-performance architecture achieves over an order of magnitude speedup when compared with a corresponding software implementation and reduces the execution time of deformable registration from hours to minutes while offering comparable image registration accuracy.Furthermore, we present a framework for multiobjective optimization of finite-precision implementations of signal processing algorithms that takes into account multiple conflicting objectives such as implementation accuracy and hardware resource consumption. The evaluation that we have performed in the context of FPGA-based image registration demonstrates that such an analysis can be used to enhance automated hardware design processes, and efficiently identify a system configuration that meets given design constraints. In addition, we also outline two novel clinical applications that can directly benefit from these developments and demonstrate the feasibility of our approach in the context of these applications. These advances will ultimately enable integration of 3D image processing into clinical workflow.

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“…Walimbe and Shekhar [60,67] Chapter 6, we demonstrate fast and successful registration of intraprocedural abdominal CT scans with preprocedural CT and PET scans using the developed…”

Section: Motivationmentioning

confidence: 94%

Section: Deformable Modelsmentioning

confidence: 99%

Section: Algorithm For Deformable Image Registrationmentioning

confidence: 99%

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High-Performance 3D Image Processing Architectures for Image-Guided Interventions

Dandekar¹

2008

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“…We used a nonrigid registration algorithm to recover the nonlinear mismatch between the stress perfusion with underlying rest anatomy from SPECT and actual stress anatomy from echocardiography. Details of the algorithm have been described (10). For a pair of reference and floating images, the registration algorithm initially recovers the global mismatch, followed by hierarchical (based on an octree subdivision scheme) refinement of the localized matching between the globally registered images.…”

Section: Automatic Image Fusion and Quantitative Analysismentioning

confidence: 99%

Multimodality Cardiac Stress Testing: Combining Real-Time 3-Dimensional Echocardiography and Myocardial Perfusion SPECT

Walimbe

Jaber

García³

et al. 2009

J Nucl Med

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Early experience is described in implementing a new multimodality stress test for accurate correlation of complementary functional and perfusion information from real-time 3-dimensional (3D) echocardiography and SPECT, respectively. The proposed new multimodality stress test has the potential for simultaneously improving sensitivity and specificity in the detection of early coronary artery disease (CAD). Methods: Pre-and poststress real-time 3D echocardiography and SPECT images were acquired in 20 patients referred for CAD evaluation and processed using previously developed algorithms for automatic fusion and quantitative analysis of myocardial function and perfusion. All cases of CAD were diagnosed by reviewing quantitatively analyzed fused images, using newly developed software. Results: Real-time 3D echocardiography, SPECT, advance processing, and image review were successfully performed in all 20 patients. Compared with the angiographic findings in 12 patients, diagnosis based on fused images correctly identified 13 of 13 diseased arteries, compared with 11 of 13 identified by SPECT and 6 of 13 identified by echocardiography-based analysis. Conclusion: The results suggest the feasibility and potential effectiveness of novel multimodality stress testing. St ress echocardiography and stress SPECT are the 2 most commonly prescribed first-step noninvasive diagnostic procedures for detection of coronary artery disease (CAD) (1) in patients with left ventricular (LV) dysfunction. However, both modalities suffer from low sensitivity and specificity (2,3), often necessitating costly and invasive follow-up procedures. Simultaneous improvement in sensitivity and specificity for detecting CAD may be achieved with multimodality stress testing, wherein diagnosis is based on accurately correlated (temporally and spatially) complementary functional and perfusion information available from echocardiography and SPECT, respectively. Previous studies reporting the combined use of echocardiography and SPECT for diagnosing CAD (4-6) adopted the inherently flawed approach of analyzing echocardiography and SPECT images separately and combining the independent diagnoses of both tests to arrive at a final diagnosis. The result was an inability to simultaneously improve both sensitivity and specificity.We propose a true multimodality stress-testing approach, wherein diagnosis is based on fused real-time 3-dimensional (3D) echocardiography and SPECT images. This approach allows direct correlation of myocardial perfusion with underlying anatomy during diagnosis, thus eliminating the confounding effects of suspected artifactual defects commonly encountered during diagnosis based on echocardiography and SPECT individually.This article summarizes our early experience in implementing the proposed multimodality stress-testing approach in a small cohort of patients and presents preliminary results indicating the potential clinical feasibility and effectiveness of the proposed methodology. Figure 1 is a schematic of the proposed interactive, ...

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“…Consequently, the analysis presented in this article pertains to locally rigid transformations. However, it must be noted that hierarchical rigid-body transformations can be used to represent deformable (nonrigid) transformation models as demonstrated in the volume subdivision-based approach reported by Walimbe and Shekhar [26].…”

Section: In This Equation H(ri) and H(fi) Are The Individual Entropimentioning

confidence: 99%

Multiobjective Optimization for Reconfigurable Implementation of Medical Image Registration

Dandekar

Plishker

Bhattacharyya

et al. 2008

International Journal of Reconfigurable Computing

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In real-time signal processing, a single application often has multiple computationally intensive kernels that can benefit from acceleration using custom or reconfigurable hardware platforms, such as field-programmable gate arrays (FPGAs). For adaptive utilization of resources at run time, FPGAs with capabilities for dynamic reconfiguration are emerging. In this context, it is useful for designers to derive sets of efficient configurations that trade off application performance with fabric resources. Such sets can be maintained at run time so that the best available design tradeoff is used. Finding a single, optimized configuration is difficult, and generating a family of optimized configurations suitable for different run-time scenarios is even more challenging. We present a novel multiobjective wordlength optimization strategy developed through FPGA-based implementation of a representative computationally intensive image processing application: medical image registration. Tradeoffs between FPGA resources and implementation accuracy are explored, and Pareto-optimized wordlength configurations are systematically identified. We also compare search methods for finding Pareto-optimized design configurations and demonstrate the applicability of search based on evolutionary techniques for identifying superior multiobjective tradeoff curves. We demonstrate feasibility of this approach in the context of FPGA-based medical image registration; however, it may be adapted to a wide range of signal processing applications.

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Automatic elastic image registration by interpolation of 3D rotations and translations from discrete rigid-body transformations

Cited by 44 publications

References 36 publications

High-Performance 3D Image Processing Architectures for Image-Guided Interventions

High-Performance 3D Image Processing Architectures for Image-Guided Interventions

Multimodality Cardiac Stress Testing: Combining Real-Time 3-Dimensional Echocardiography and Myocardial Perfusion SPECT

Multiobjective Optimization for Reconfigurable Implementation of Medical Image Registration

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