Visual Perception and Cognition in Image-Guided Intervention

Surgical image visualization and interaction systems can dramatically affect the efficacy and efficiency of surgical training, planning, and interventions. This is even more profound in the case of minimally-invasive surgery where restricted access to the operative field in conjunction with limited field of view necessitate a visualization medium to provide patient-specific information at any given moment. Unfortunately, little research has been devoted to studying human factors associated with medical image displays and the need for a robust, intuitive visualization and interaction interfaces has remained largely unfulfilled to this day. Failure to engineer efficient medical solutions and design intuitive visualization interfaces is argued to be one of the major barriers to the meaningful transfer of innovative technology to the operating room. This thesis was, therefore, motivated by the need to study various cognitive and perceptual aspects of human factors in surgical image visualization systems, to increase the efficiency and effectiveness of medical interfaces, and ultimately to improve patient outcomes. To this end, we chose four different minimally-invasive interventions in the realm of surgical training, planning, training for planning, and navigation: The first chapter involves the use of stereoendoscopes to reduce morbidity in endoscopic third ventriculostomy. The results of this study suggest that, compared with conventional endoscopes, the detection of the basilar artery on the surface of the third ventricle can be facilitated with the use of stereoendoscopes, increasing the safety of targeting in third ventriculostomy procedures. In the second chapter, a contour enhancement technique is described to improve preoperative planning of arteriovenous malformation interventions. The proposed method, particularly when combined with stereopsis, is shown to increase the speed and accuracy of understanding the spatial relationship between vascular structures. In the third chapter, an augmented-reality system is proposed to facilitate the training of planning brain tumour resection. The results of our user study indicate that the proposed system improves subjects\u27 performance, particularly novices\u27, in formulating the optimal point of entry and surgical path independent of the sensorimotor tasks performed. In the last chapter, the role of fully-immersive simulation environments on the surgeons\u27 non-technical skills to perform vertebroplasty procedure is investigated. Our results suggest that while training surgeons may increase their technical skills, the introduction of crisis scenarios significantly disturbs the performance, emphasizing the need of realistic simulation environments as part of training curriculum

Advanced diagnostic imaging and intervention in tendon diseases

Degenerative tendon pathology represents one of the most frequent and disabling musculoskeletal disorders. Diagnostic radiology plays a fundamental role in the clinical evaluation of tendon pathologies. Moreover, several minimally invasive treatments can be performed under imaging guidance to treat tendon disorders, maximizing the efficacy and reducing procedural complications. In this review article we describe the most relevant diagnostic features of conventional and advanced US and MRI imaging in tendon disorders, along with the main options for image-guided intervention. (www.actabiomedica.it)

Guest Editorial : Special issue on advanced computing for image-guided intervention

Editorial Guest Editorial: Special issue on advanced computing for image-guided intervention In the past years, we have witnessed a growing number of applications of minimally invasive or non-invasive interventions in clinical practice, where imaging is playing an essential role for the success of both diagnosis and therapy. Particularly, advanced signal and image processing algorithms are receiving increasing attention, which aim to provide accurate and reliable information directly to physicians. We have seen the applications of these technologies during all stages of an intervention, including preoperational planning, intra-operational guidance and post-operational verification. For this special issue, we have received a significant number of submissions from both academia and industry, out of which we have carefully selected eleven articles with outstanding quality. These articles have covered the topics of anatomic structure identification and tracking, image registration, data visualization and newly emerging applications. In [1] have addressed the image registration problem between preand post-radiated MRI to facilitate the evaluation of the therapeutic response after External Beam Radiation Treatment (EBRT) for the prostate cancer. A different approach has been employed by We have also included three papers on ultrasound-guided image interventions. In We have included in this special issue two papers on tissue characterization from endoscopic images. Nawarathna et al. have proposed in With the increasing use of various imaging modalities in image-guided intervention and therapy, how to optimally present and visualize the data becomes also an important issue. In [10], the authors have addressed the use of autostereoscopic volumetric visualization of the patient's anatomy, which has the potential to be combined with augmented reality. The paper especially addresses the latency problem in the visualization chain, and a few improvements have been proposed. A new adjacent application has been presented in In summary, we have seen from submissions to this special issue a growing interest in applying advanced signal and image processing technologies to image-guided interventions. The submissions have covered a wide range of clinical applications using various imaging modalities. Image feature extraction remains to be an important subject and it has to be specifically designed to suit the needs for specific applications. Learning-based approaches have also attracted a lot of attention, especially in applications requiring automatic tissue characterization and classification. We are also very happy to have received new emerging applications which are able to extend the traditional interventional imaging into greater application areas. Acknowledgments We would like to thank all the reviewers who have helped to peer-review the submitted papers and their constructive comments are well appreciated

Robustness and Accuracy of Feature-Based Single Image 2-D–3-D Registration Without Correspondences for Image-Guided Intervention

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Robust Registration of Calcium Images by Learned Contrast Synthesis

Multi-modal image registration is a challenging task that is vital to fuse complementary signals for subsequent analyses. Despite much research into cost functions addressing this challenge, there exist cases in which these are ineffective. In this work, we show that (1) this is true for the registration of in-vivo Drosophila brain volumes visualizing genetically encoded calcium indicators to an nc82 atlas and (2) that machine learning based contrast synthesis can yield improvements. More specifically, the number of subjects for which the registration outright failed was greatly reduced (from 40% to 15%) by using a synthesized image

Biomedical imaging research opportunities workshop IV: A white paper

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134967/1/mp5838.pd