Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images

This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.Comment: This paper was published and presented in SPIE Medical Imaging 201

3D/2D Registration of Mapping Catheter Images for Arrhythmia Interventional Assistance

Radiofrequency (RF) catheter ablation has transformed treatment for tachyarrhythmias and has become first-line therapy for some tachycardias. The precise localization of the arrhythmogenic site and the positioning of the RF catheter over that site are problematic: they can impair the efficiency of the procedure and are time consuming (several hours). Electroanatomic mapping technologies are available that enable the display of the cardiac chambers and the relative position of ablation lesions. However, these are expensive and use custom-made catheters. The proposed methodology makes use of standard catheters and inexpensive technology in order to create a 3D volume of the heart chamber affected by the arrhythmia. Further, we propose a novel method that uses a priori 3D information of the mapping catheter in order to estimate the 3D locations of multiple electrodes across single view C-arm images. The monoplane algorithm is tested for feasibility on computer simulations and initial canine data.Comment: International Journal of Computer Science Issues, IJCSI, Volume 4, Issue 2, pp10-19, September 200

Numerical methods for coupled reconstruction and registration in digital breast tomosynthesis.

Digital Breast Tomosynthesis (DBT) provides an insight into the fine details of normal fibroglandular tissues and abnormal lesions by reconstructing a pseudo-3D image of the breast. In this respect, DBT overcomes a major limitation of conventional X-ray mam- mography by reducing the confounding effects caused by the superposition of breast tissue. In a breast cancer screening or diagnostic context, a radiologist is interested in detecting change, which might be indicative of malignant disease. To help automate this task image registration is required to establish spatial correspondence between time points. Typically, images, such as MRI or CT, are first reconstructed and then registered. This approach can be effective if reconstructing using a complete set of data. However, for ill-posed, limited-angle problems such as DBT, estimating the deformation is com- plicated by the significant artefacts associated with the reconstruction, leading to severe inaccuracies in the registration. This paper presents a mathematical framework, which couples the two tasks and jointly estimates both image intensities and the parameters of a transformation. Under this framework, we compare an iterative method and a simultaneous method, both of which tackle the problem of comparing DBT data by combining reconstruction of a pair of temporal volumes with their registration. We evaluate our methods using various computational digital phantoms, uncom- pressed breast MR images, and in-vivo DBT simulations. Firstly, we compare both iter- ative and simultaneous methods to the conventional, sequential method using an affine transformation model. We show that jointly estimating image intensities and parametric transformations gives superior results with respect to reconstruction fidelity and regis- tration accuracy. Also, we incorporate a non-rigid B-spline transformation model into our simultaneous method. The results demonstrate a visually plausible recovery of the deformation with preservation of the reconstruction fidelity

Combination of Imaging Infrared Spectroscopy and X-ray Computed Microtomography for the Investigation of Bio-and Physicochemical processes in Structured Soils

Soil is a heterogeneous mixture of various organic and inorganic parent materials. Major soil functions are driven by their quality, quantity and spatial arrangement, resulting in soil structure. Physical protection of organic matter (OM) in this soil structure is considered as a vital mechanism for stabilizing organic carbon turnover, an important soil function in times of climate change. Herein, we present a technique for the correlative analysis of 2D imaging visible light near-infrared spectroscopy and 3D X-ray computed microtomography (mCT) to investigate the interplay of biogeochemical properties and soil structure in undisturbed soil samples. Samples from the same substrate but different soil management and depth (no-tilled topsoil, tilled topsoil and subsoil) were compared in order to evaluate this method in a diversely structured soil. Imaging spectroscopy is generally used to qualitatively and quantitatively identify OM with high spatial resolution, whereas 3D X-ray mCT provides high resolution information on pore characteristics. The unique combination of these techniques revealed that, in undisturbed samples, OM can be found mainly at greater distances from macropores and close to biopores. However, alterations were observed because of disturbances by tillage. The correlative application of imaging infrared spectroscopic and X-ray mCT analysis provided new insights into the biochemical processes affected by soil structural changes