Franjo Pernuš

A Review of Methods for Correction of Intensity Inhomogeneity in MRI

Medical image acquisition devices provide a vast amount of anatomical and functional information, which facilitate and improve diagnosis and patient treatment, especially when supported by modern quantitative image analysis methods. However, modality specific image artifacts, such as the phenomena of intensity inhomogeneity in magnetic resonance images (MRI), are still prominent and can adversely affect quantitative image analysis. In this paper, numerous methods that have been developed to reduce or eliminate intensity inhomogeneities in MRI are reviewed. First, the methods are classified according to the inhomogeneity correction strategy. Next, different qualitative and quantitative evaluation approaches are reviewed. Third, 60 relevant publications are categorized according to several features and analyzed so as to reveal major trends, popularity, evaluation strategies and applications. Finally, key evaluation issues and future development of the inhomogeneity correction field, supported by the results of the analysis, are discussed

A review of 3D/2D registration methods for image-guided interventions

Registration of pre- and intra-interventional data is one of the key technologies for image-guided radiation therapy, radiosurgery, minimally invasive surgery, endoscopy, and interventional radiology. In this paper, we survey those 3D/2D data registration methods that utilize 3D computer tomography or magnetic resonance images as the pre-interventional data and 2D X-ray projection images as the intra-interventional data. The 3D/2D registration methods are reviewed with respect to image modality, image dimensionality, registration basis, geometric transformation, user interaction, optimization procedure, subject, and object of registration.

Retrospective correction of MR intensity inhomogeneity by information minimization

In this paper, the problem of retrospective correction of intensity inhomogeneity in magnetic resonance (MR) images is addressed. A novel model-based correction method is proposed, based on the assumption that an image corrupted by intensity inhomogeneity contains more information than the corresponding uncorrupted image. The image degradation process is described by a linear model, consisting of a multiplicative and an additive component which are modeled by a combination of smoothly varying basis functions. The degraded image is corrected by the inverse of the image degradation model. The parameters of this model are optimized such that the information of the corrected image is minimized while the global intensity statistic is preserved. The method was quantitatively evaluated and compared to other methods on a number of simulated and real MR images and proved to be effective, reliable, and computationally attractive. The method can be widely applied to different types of MR images because it solely uses the information that is naturally present in an image, without making assumptions on its spatial and intensity distribution. Besides, the method requires no preprocessing, parameter setting, nor user interaction. Consequently, the proposed method may be a valuable tool in MR image analysis.

A hierarchical approach to elastic registration based on mutual information

Abstract A hierarchical approach to elastic registration based on mutual information, in which the images are progressively subdivided, locally registered, and elastically interpolated, is presented. To improve the registration, a combination of prior and floating information on the joint probability is proposed. It is shown that such a combination increases the registration speed at the coarser levels in hierarchy, enables a registration of finer details, and provides additional guidance to the optimisation process. Besides, a threefold local registration consistency test and correction of shading were employed to increase the overall registration performance. The proposed hierarchical method for elastic registration was tested on an experimental database of 2D images of histochemically differently stained serial cross-sections of human skeletal muscle. The obtained results show that 95% of the images could be successfully registered. The inclusion of prior information is an important break through that may enable routine use of the mutual information cost function in a variety of 2D and 3D image registration algorithms in the future.

A review of methods for quantitative evaluation of spinal curvature

The aim of this paper is to provide a complete overview of the existing methods for quantitative evaluation of spinal curvature from medical images, and to summarize the relevant publications, which may not only assist in the introduction of other researchers to the field, but also be a valuable resource for studying the existing methods or developing new methods and evaluation strategies. Key evaluation issues and future considerations, supported by the results of the overview, are also discussed.

A Survey of Mobile Robots for Distribution Power Line Inspection

The purpose of this paper is to present the most important achievements in the field of distribution power line inspection by mobile robots. Stimulated by the need for fast, accurate, safe and low-cost power line inspection, which would increase the quality of power delivery, the field of automated power line inspection has witnessed rapid development over the last decade. This paper addresses automated helicopter inspection, inspection with flying robots and inspection with climbing robots. The first attempts to automate power line inspection were conducted in the field of helicopter inspection. In recent years, however, the research was mostly focused on flying and climbing robots. These two types of robots for automated power line inspection are critically assessed according to four important characteristics: design requirements, inspection quality, autonomy and universality of inspection. Besides, some general not yet identified problems and tasks of inspection robots, which should be addressed in the future, are presented. In conclusion, the two robot types have specific benefits and drawbacks so that none can currently be considered generally advantageous.

New Robot for Power Line Inspection

Power line inspection is of the utmost importance for the reliability and stability of electric power distribution. However, manual inspection is a hazardous, slow, expensive and unreliable task. Therefore, new highly specialized robots are required to improve the overall quality and safety of the power line inspection. The research conducted so far has been mainly focused on the development of climbing and flying robots. This paper first addresses the main achievements in the field of robotic power line inspection. The proposed solutions are critically assessed and the associated problems are outlined. Based on these findings, a new concept for robot-assisted power line inspection, combining both climbing and flying principles, is proposed in the second part of the paper. The proposed concept is critically assessed and related to the other established concepts so as to demonstrate its advantages and feasibility for a routine power line inspection.

Comparative evaluation of retrospective shading correction methods

Because of the inherent imperfections of the image formation process, microscopical images are often corrupted by spurious intensity variations. This phenomenon, known as shading or intensity inhomogeneity, may have an adverse affect on automatic image processing, such as segmentation and registration. Shading correction methods may be prospective or retrospective. The former require an acquisition protocol tuned to shading correction, whereas the latter can be applied to any image, because they only use the information already present in an image. Nine retrospective shading correction methods were implemented, evaluated and compared on three sets of differently structured synthetic shaded and shading‐free images and on three sets of real microscopical images acquired by different acquisition set‐ups. The performance of a method was expressed quantitatively by the coefficient of joint variations between two different object classes. The results show that all methods, except the entropy minimization method, work well for certain images, but perform poorly for others. The entropy minimization method outperforms the other methods in terms of reduction of true intensity variations and preservation of intensity characteristics of shading‐free images. The strength of the entropy minimization method is especially apparent when applied to images containing large‐scale objects.

A review of methods for evaluating the quantitative parameters of sagittal pelvic alignment

BACKGROUND CONTEXT The sagittal alignment of the pelvis represents the basic mechanism for maintaining postural equilibrium, and a number of methods were developed to assess normal and pathologic pelvic alignments from two-dimensional sagittal radiographs in terms of positional and anatomic parameters. PURPOSE To provide a complete overview of the existing methods for quantitative evaluation of sagittal pelvic alignment and summarize the relevant publications. STUDY DESIGN Review article. METHODS An Internet search for terms related to sagittal pelvic alignment was performed to obtain relevant publications, which were further supplemented by selected publications found in their lists of references. By summarizing the obtained publications, the positional and anatomic parameters of sagittal pelvic alignment were described, and their values and relationships to other parameters and features were reported. RESULTS Positional pelvic parameters relate to the position and orientation of the observed subject and are represented by the sacral slope, pelvic tilt, pelvic overhang, sacral inclination, sacrofemoral angle, sacrofemoral distance, pelvic femoral angle, pelvic angle, and sacropelvic translation. Anatomic pelvic parameters relate to the anatomy of the observed subject and are represented by the pelvisacral angle (PSA), pelvic incidence (PI), pelvic thickness (PTH), sacropelvic angle (PRS1), pelvic radius (PR), femorosacral posterior angle (FSPA), sacral table angle (STA), and sacral anatomic orientation (SAO). The review was mainly focused on the evaluation of anatomic pelvic parameters, as they can be compared among subjects and therefore among different studies. However, ambiguous results were yielded for normal and pathologic subjects, as the reported values show a relatively high variability in terms of standard deviation for every anatomic parameter, which amounts to around 10 mm for PTH and PR; 10° for PSA, PI, and SAO; 9° for PRS1 and FSPA; and 5° for STA in the case of normal subjects and is usually even higher in the case of pathologic subjects. Among anatomic pelvic parameters, PI was the most studied and therefore represents a key parameter in the complex framework of sagittal spinal alignment and related deformities. From the reviewed studies, the regression lines for PI and the corresponding age of the subjects indicate that PI tends to increase with age for normal (PI = +0.17 × age+46.40) and scoliotic (PI = +0.20 × age+50.52) subjects and decrease with age for subjects with spondylolisis or spondylolisthesis (PI = -0.26 × age+75.69). CONCLUSIONS Normative values for anatomic parameters of sagittal pelvic alignment do not exist because the variability of the measured values is relatively high even for normal subjects but can be predictive for spinal alignment and specific spinopelvic pathologies.

Robust Gradient-Based 3-D/2-D Registration of CT and MR to X-Ray Images

One of the most important technical challenges in image-guided intervention is to obtain a precise transformation between the intrainterventional patients anatomy and corresponding preinterventional 3-D image on which the intervention was planned. This goal can be achieved by acquiring intrainterventional 2-D images and matching them to the preinterventional 3-D image via 3-D/2-D image registration. A novel 3-D/2-D registration method is proposed in this paper. The method is based on robustly matching 3-D preinterventional image gradients and coarsely reconstructed 3-D gradients from the intrainterventional 2-D images. To improve the robustness of finding the correspondences between the two sets of gradients, hypothetical correspondences are searched for along normals to anatomical structures in 3-D images, while the final correspondences are established in an iterative process, combining the robust random sample consensus algorithm (RANSAC) and a special gradient matching criterion function. The proposed method was evaluated using the publicly available standardized evaluation methodology for 3-D/2-D registration, consisting of 3-D rotational X-ray, computed tomography, magnetic resonance (MR), and 2-D X-ray images of two spine segments, and standardized evaluation criteria. In this way, the proposed method could be objectively compared to the intensity, gradient, and reconstruction-based registration methods. The obtained results indicate that the proposed method performs favorably both in terms of registration accuracy and robustness. The method is especially superior when just a few X-ray images and when MR preinterventional images are used for registration, which are important advantages for many clinical applications.