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

Medical imaging analysis with artificial neural networks

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging

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

Effective and Efficient Non-Destructive Testing of Large and Complex Shaped Aircraft Structures

The main aim of the research described within this thesis is to develop methodologies that enhance the defect detection capabilities of nondestructive testing (NDT) for the aircraft industry. Modem aircraft non-destructive testing requires the detection of small defects in large complex shaped components. Research has therefore focused on the limitations of ultrasonic, radioscopic and shearographic methods and the complimentary aspects associated with each method. The work has identified many parameters that have significant effect on successful defect detection and has developed methods for assessing NDT systems capabilities by noise analysis, excitation performance and error contributions attributed to the positioning of sensors. The work has resulted in 1. The demonstration that positional accuracy when ultrasonic testing has a significant effect on defect detection and a method to measure positional accuracy by evaluating the compensation required in a ten axis scanning system has revealed limitsio the achievable defect detection when using complex geometry scanning systems. 2. A method to reliably detect 15 micron voids in a diffusion bonded joint at ultrasonic frequencies of 20 MHz and above by optimising transducer excitation, focussing and normalisation. 3. A method of determining the minimum detectable ultrasonic attenuation variation by plotting the measuring error when calibrating the alignment of a ten axis scanning system. 4. A new formula for the calculation of the optimum magnification for digital radiography. The formula is applicable for focal spot sizes less than 0.1 mm. 5. A practical method of measuring the detection capabilities of a digital radiographic system by calculating the modulation transfer function and the noise power spectrum from a reference image. 6. The practical application of digital radiography to the inspection of super plastically formed ditThsion bonded titanium (SPFDB) and carbon fibre composite structure has been demonstrated but has also been supported by quantitative measurement of the imaging systems capabilities. 7. A method of integrating all the modules of the shearography system that provides significant improvement in the minimum defect detection capability for which a patent has been granted. 8. The matching of the applied stress to the data capture and processing during a shearographic inspection which again contributes significantly to the defect detection capability. 9. The testing and validation of the Parker and Salter [1999] temporal unwrapping and laser illumination work has led to the realisation that producing a pressure drop that would result in a linear change in surface deformation over time is difficult to achieve. 10. The defect detection capabilities achievable by thermal stressing during a shearographic inspection have been discovered by applying the pressure drop algorithms to a thermally stressed part. 11. The minimum surface displacement measurable by a shearography system and therefore the defect detection capabilities can be determined by analysing the signal to noise ratio of a transition from a black (poor reflecting surface) to white (good reflecting surface). The quantisation range for the signal to noise ratio is then used in the Hung [1982] formula to calculate the minimum displacement. Many of the research aspects contained within this thesis are cuffently being implemented within the production inspection process at BAE Samlesbury

Estimating Target Vessel Location on Robot-Assisted CABG using Feature-based CT to US Registration

Although robot-assisted coronary artery bypass grafting (RA-CABG) has gained more acceptance worldwide, its success still depends on the surgeon’s experience and expertise, and the conversion rate to full sternotomy is in the order of 15%—25%. One of the reasons for conversion is poor pre-operative planning, which is based solely on pre-operative computed tomography (CT) images. This thesis proposes a technique to estimate the global peri-operative displacement of the heart and to predict the intra-operative target vessel location. The technique has been validated via both an in vitro and a clinical study, and predicted the position of the peri-operative target vessel location with ~ 3.5 mm RMS accuracy in the in vitro study while it yielded ~ 5.0 mm accuracy for the clinical validation. As the desired clinical accuracy imposed by this procedure is on the order of one intercostal space (10 - 15 mm), our technique suits the clinical requirements. It is therefore believed that this technique has the potential to improve the pre-operative planning by updating peri-operative migration patterns of the heart and, consequently, will lead to reduced conversion to conventional open thoracic procedures

Automatic quantification of intravascular optical coherence tomography

As mentioned above, IVOCT, as a novel imaging modality, has played an active role in a wide range of CAD applications, including research and clinical routine. Due to its unparalleled high resolution and the ability to delineate complex vascular structures, IVOCT technology makes many precise measurement and novel applications possible. However, currently, a lot of analyses in IVOCT images are still relying on the manual work which decreases their value. The goal of this thesis is to develop robust and accurate (semi)automated methods that can detect and segment the interesting components in IVOCT pullback runs, such as implanted stent struts and side branches in 3D for accurate measurement, so that the results could contribute to medical research as well as for clinical decision-making. My thesis presents four different automated algorithms to detect metallic stent struts, bioresorbable vascular scaffold struts, side branches and all the common components in IVOCT images. It also presented a semi-automated method to assess the stent support to vessel wall and the stent-jailed side branch access through stent cells in 3-dimentional spaceChina Scholarship Council (CSC)UBL - phd migration 201

Analysis of contrast-enhanced medical images.

Early detection of human organ diseases is of great importance for the accurate diagnosis and institution of appropriate therapies. This can potentially prevent progression to end-stage disease by detecting precursors that evaluate organ functionality. In addition, it also assists the clinicians for therapy evaluation, tracking diseases progression, and surgery operations. Advances in functional and contrast-enhanced (CE) medical images enabled accurate noninvasive evaluation of organ functionality due to their ability to provide superior anatomical and functional information about the tissue-of-interest. The main objective of this dissertation is to develop a computer-aided diagnostic (CAD) system for analyzing complex data from CE magnetic resonance imaging (MRI). The developed CAD system has been tested in three case studies: (i) early detection of acute renal transplant rejection, (ii) evaluation of myocardial perfusion in patients with ischemic heart disease after heart attack; and (iii), early detection of prostate cancer. However, developing a noninvasive CAD system for the analysis of CE medical images is subject to multiple challenges, including, but are not limited to, image noise and inhomogeneity, nonlinear signal intensity changes of the images over the time course of data acquisition, appearances and shape changes (deformations) of the organ-of-interest during data acquisition, determination of the best features (indexes) that describe the perfusion of a contrast agent (CA) into the tissue. To address these challenges, this dissertation focuses on building new mathematical models and learning techniques that facilitate accurate analysis of CAs perfusion in living organs and include: (i) accurate mathematical models for the segmentation of the object-of-interest, which integrate object shape and appearance features in terms of pixel/voxel-wise image intensities and their spatial interactions; (ii) motion correction techniques that combine both global and local models, which exploit geometric features, rather than image intensities to avoid problems associated with nonlinear intensity variations of the CE images; (iii) fusion of multiple features using the genetic algorithm. The proposed techniques have been integrated into CAD systems that have been tested in, but not limited to, three clinical studies. First, a noninvasive CAD system is proposed for the early and accurate diagnosis of acute renal transplant rejection using dynamic contrast-enhanced MRI (DCE-MRI). Acute rejection–the immunological response of the human immune system to a foreign kidney–is the most sever cause of renal dysfunction among other diagnostic possibilities, including acute tubular necrosis and immune drug toxicity. In the U.S., approximately 17,736 renal transplants are performed annually, and given the limited number of donors, transplanted kidney salvage is an important medical concern. Thus far, biopsy remains the gold standard for the assessment of renal transplant dysfunction, but only as the last resort because of its invasive nature, high cost, and potential morbidity rates. The diagnostic results of the proposed CAD system, based on the analysis of 50 independent in-vivo cases were 96% with a 95% confidence interval. These results clearly demonstrate the promise of the proposed image-based diagnostic CAD system as a supplement to the current technologies, such as nuclear imaging and ultrasonography, to determine the type of kidney dysfunction. Second, a comprehensive CAD system is developed for the characterization of myocardial perfusion and clinical status in heart failure and novel myoregeneration therapy using cardiac first-pass MRI (FP-MRI). Heart failure is considered the most important cause of morbidity and mortality in cardiovascular disease, which affects approximately 6 million U.S. patients annually. Ischemic heart disease is considered the most common underlying cause of heart failure. Therefore, the detection of the heart failure in its earliest forms is essential to prevent its relentless progression to premature death. While current medical studies focus on detecting pathological tissue and assessing contractile function of the diseased heart, this dissertation address the key issue of the effects of the myoregeneration therapy on the associated blood nutrient supply. Quantitative and qualitative assessment in a cohort of 24 perfusion data sets demonstrated the ability of the proposed framework to reveal regional perfusion improvements with therapy, and transmural perfusion differences across the myocardial wall; thus, it can aid in follow-up on treatment for patients undergoing the myoregeneration therapy. Finally, an image-based CAD system for early detection of prostate cancer using DCE-MRI is introduced. Prostate cancer is the most frequently diagnosed malignancy among men and remains the second leading cause of cancer-related death in the USA with more than 238,000 new cases and a mortality rate of about 30,000 in 2013. Therefore, early diagnosis of prostate cancer can improve the effectiveness of treatment and increase the patient’s chance of survival. Currently, needle biopsy is the gold standard for the diagnosis of prostate cancer. However, it is an invasive procedure with high costs and potential morbidity rates. Additionally, it has a higher possibility of producing false positive diagnosis due to relatively small needle biopsy samples. Application of the proposed CAD yield promising results in a cohort of 30 patients that would, in the near future, represent a supplement of the current technologies to determine prostate cancer type. The developed techniques have been compared to the state-of-the-art methods and demonstrated higher accuracy as shown in this dissertation. The proposed models (higher-order spatial interaction models, shape models, motion correction models, and perfusion analysis models) can be used in many of today’s CAD applications for early detection of a variety of diseases and medical conditions, and are expected to notably amplify the accuracy of CAD decisions based on the automated analysis of CE images

Computer integrated system: medical imaging & visualization

The intent of this book’s conception is to present research work using a user centered design approach. Due to space constraints, the story of the journey, included in this book is relatively brief. However we believe that it manages to adequately represent the story of the journey, from its humble beginnings in 2008 to the point where it visualizes future trends amongst both researchers and practitioners across the Computer Science and Medical disciplines. This book aims not only to present a representative sampling of real-world collaboration between said disciplines but also to provide insights into the different aspects related to the use of real-world Computer Assisted Medical applications. Readers and potential clients should find the information particularly useful in analyzing the benefits of collaboration between these two fields, the products in and of their institutions. The work discussed here is a compilation of the work of several PhD students under my supervision, who have since graduated and produced several publications either in journals or proceedings of conferences. As their work has been published, this book will be more focused on the research methodology based on medical technology used in their research. The research work presented in this book partially encompasses the work under the MOA for collaborative Research and Development in the field of Computer Assisted Surgery and Diagnostics pertaining to Thoracic and Cardiovascular Diseases between UPM, UKM and IJN, spanning five years beginning from 15 Feb 2013