Medical Imaging: Image-Guided Procedures最新文献_第9页

Healthcare in need of innovation: exponential technology and biomedical entrepreneurship as solution providers (Keynote Paper) 需要创新的医疗保健:作为解决方案提供者的指数技术和生物医学创业(主题论文)

Medical Imaging: Image-Guided Procedures Pub Date : 2020-03-16 DOI: 10.1117/12.2556776

M. Friebe

{"title":"Healthcare in need of innovation: exponential technology and biomedical entrepreneurship as solution providers (Keynote Paper)","authors":"M. Friebe","doi":"10.1117/12.2556776","DOIUrl":"https://doi.org/10.1117/12.2556776","url":null,"abstract":"There are significant challenges in global healthcare delivery at the moment. Some countries have abundant services, but are stuck with a rather nimble and expensive system that focuses on incremental innovations. Other geographies are still in need of basic tools, infrastructure and require completely different, inexpensive, and with that more disruptive solutions to satisfy their healthcare needs. Next Generation Healthcare systems with a focus on prevention / early detection and pro-active therapy will employ exponential technologies (AI, Big Data, Blockchain, Sensor Technology, Synthetic Biology, Tissue Engineering, Robotics, 3D Printing, ...) that will surely lead to significant changes in the way we experience, think about, and deliver healthcare and in which a digitally empowered patient will play a more important role. In the coming years/decades we will experience a shift from the current SICK-CARE provision to real HEALTHCARE to a focus on personal HEALTH, supported by an integration of patient generated health data with other external diagnostic and therapeutic data components creating a digital health twin as a base for prevention and patient centered precision medicine. Education and training of Biomedical Engineers needs to be adjusted to these developments focussing on solving unmet clinical needs, which requires a solid understanding of current health problems (regional, global), future technologies, economic realities and global health markets. The paper will present and discuss some of these future global innovation needs and the subsequent need for a change in the biomedical engineering curriculum that needs to include learning- (creativity, critical thinking, collaboration) and life skills (flexibility, leadership, social), as well as basic economic and entrepreneurial training — all of which are currently not taught or emphasized.","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132239129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

A guidance system for electrode placement in epilepsy cases 一种用于癫痫患者电极放置的引导系统

Medical Imaging: Image-Guided Procedures Pub Date : 2020-03-16 DOI: 10.1117/12.2549649

X. Fan, D. Roberts, K. Paulsen

引用次数: 0

Patient-specific deep deformation models (PsDDM) to register planning and interventional ultrasound volumes in image fusion-guided interventions 患者特异性深度变形模型(PsDDM)用于记录图像融合引导介入计划和介入超声体积

Medical Imaging: Image-Guided Procedures Pub Date : 2020-03-16 DOI: 10.1117/12.2549352

J. Mitra, Michael MacDonald, David M. Mills, S. Ghose, L. Smith, Shourya Sarcar, D. Yeo, C. Tempany, B. Bednarz, S. Jupitz, Thomas K. Foo

引用次数: 1

Efficient target tracking for 3D ultrasound-guided needle steering 三维超声引导针导向的高效目标跟踪

Medical Imaging: Image-Guided Procedures Pub Date : 2020-02-15 DOI: 10.1117/12.2548321

Guillaume Lapouge, G. Fiard, P. Poignet, J. Troccaz

{"title":"Efficient target tracking for 3D ultrasound-guided needle steering","authors":"Guillaume Lapouge, G. Fiard, P. Poignet, J. Troccaz","doi":"10.1117/12.2548321","DOIUrl":"https://doi.org/10.1117/12.2548321","url":null,"abstract":"3D ultrasound imaging can be used in the context of robotic needle steering to reach a physical target with a flexible, steerable needle. During the insertion, the tissue may be deformed by the inserted needle, patient breathing or external force application. It may therefore be necessary to track intra-operatively the displacement of the target. Most ultrasound based needle steering works concentrate on 2D ultrasound probes [1], [2], [3] which do not allow to simultaneously track both the target and the needle during 3D needle steering. Physical target tracking in 3D ultrasound-guided needle steering is seldom carried out [4][5], and may require computational power that is precious for intra-operative needle steering. This paper proposes a new approach for computationally inexpensive and precise tracking of a moving target in 3D B-mode ultrasound volumes. It is based on the interconnection of intensity-based tracking and motion estimation algorithms. The intensity-based tracking consists in a 3D extension of the Diamond Shape block matching algorithm, used here for the first time in 3D ultrasound volumes for tissue tracking. The motion estimation is done by linear Kalman filtering. It predicts the next target position and ensures faster and more robust convergence of the Diamond Shape block matching algorithm. An experimental validation on ex-vivo tissue is proposed with promising tracking precision (estimated average error of 0.3mm) while significantly lowering the computational cost when compared to classical block matching based tracking.","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121809377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning? 基于成人心脏磁共振成像数据训练的u - net分割在罕见先天性心脏病手术规划中的推广效果如何?

Medical Imaging: Image-Guided Procedures Pub Date : 2020-02-10 DOI: 10.1117/12.2550651

Sven Koehler, A. Tandon, T. Hussain, H. Latus, T. Pickardt, S. Sarikouch, P. Beerbaum, G. Greil, S. Engelhardt, I. Wolf

{"title":"How well do U-Net-based segmentation trained on adult cardiac magnetic resonance imaging data generalise to rare congenital heart diseases for surgical planning?","authors":"Sven Koehler, A. Tandon, T. Hussain, H. Latus, T. Pickardt, S. Sarikouch, P. Beerbaum, G. Greil, S. Engelhardt, I. Wolf","doi":"10.1117/12.2550651","DOIUrl":"https://doi.org/10.1117/12.2550651","url":null,"abstract":"Planning the optimal time of intervention for pulmonary valve replacement surgery in patients with the congenital heart disease Tetralogy of Fallot (TOF) is mainly based on ventricular volume and function according to current guidelines. Both of these two biomarkers are most reliably assessed by segmentation of 3D cardiac magnetic resonance (CMR) images. In several grand challenges in the last years, U-Net architectures have shown impressive results on the provided data. However, in clinical practice, data sets are more diverse considering individual pathologies and image properties derived from different scanner properties. Additionally, specific training data for complex rare diseases like TOF is scarce. \u0000For this work, 1) we assessed the accuracy gap when using a publicly available labelled data set (the Automatic Cardiac Diagnosis Challenge (ACDC) data set) for training and subsequent applying it to CMR data of TOF patients and vice versa and 2) whether we can achieve similar results when applying the model to a more heterogeneous data base. \u0000Multiple deep learning models were trained with four-fold cross validation. Afterwards they were evaluated on the respective unseen CMR images from the other collection. Our results confirm that current deep learning models can achieve excellent results (left ventricle dice of $0.951pm{0.003}$/$0.941pm{0.007}$ train/validation) within a single data collection. But once they are applied to other pathologies, it becomes apparent how much they overfit to the training pathologies (dice score drops between $0.072pm{0.001}$ for the left and $0.165pm{0.001}$ for the right ventricle).","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129393323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Towards Augmented Reality-based Suturing in Monocular Laparoscopic Training 基于增强现实的单眼腹腔镜缝合训练

Medical Imaging: Image-Guided Procedures Pub Date : 2020-01-19 DOI: 10.1117/12.2550830

C. J. Preetha, J. Kloss, F. Wehrtmann, Lalith Sharan, C. Fan, B. Müller-Stich, F. Nickel, S. Engelhardt

{"title":"Towards Augmented Reality-based Suturing in Monocular Laparoscopic Training","authors":"C. J. Preetha, J. Kloss, F. Wehrtmann, Lalith Sharan, C. Fan, B. Müller-Stich, F. Nickel, S. Engelhardt","doi":"10.1117/12.2550830","DOIUrl":"https://doi.org/10.1117/12.2550830","url":null,"abstract":"Minimally Invasive Surgery (MIS) techniques have gained rapid popularity among surgeons since they offer significant clinical benefits including reduced recovery time and diminished post-operative adverse effects. However, conventional endoscopic systems output monocular video which compromises depth perception, spatial orientation and field of view. Suturing is one of the most complex tasks performed under these circumstances. Key components of this tasks are the interplay between needle holder and the surgical needle. Reliable 3D localization of needle and instruments in real time could be used to augment the scene with additional parameters that describe their quantitative geometric relation, e.g. the relation between the estimated needle plane and its rotation center and the instrument. This could contribute towards standardization and training of basic skills and operative techniques, enhance overall surgical performance, and reduce the risk of complications. The paper proposes an Augmented Reality environment with quantitative and qualitative visual representations to enhance laparoscopic training outcomes performed on a silicone pad. This is enabled by a multi-task supervised deep neural network which performs multi-class segmentation and depth map prediction. Scarcity of labels has been conquered by creating a virtual environment which resembles the surgical training scenario to generate dense depth maps and segmentation maps. The proposed convolutional neural network was tested on real surgical training scenarios and showed to be robust to occlusion of the needle. The network achieves a dice score of 0.67 for surgical needle segmentation, 0.81 for needle holder instrument segmentation and a mean absolute error of 6.5 mm for depth estimation.","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127218544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Pivot calibration concept for sensor attached mobile c-arms 传感器连接移动c型臂的枢轴校准概念

Medical Imaging: Image-Guided Procedures Pub Date : 2020-01-09 DOI: 10.1117/12.2547581

Sing Chun Lee, Matthias Seibold, P. Fürnstahl, M. Farshad, N. Navab

{"title":"Pivot calibration concept for sensor attached mobile c-arms","authors":"Sing Chun Lee, Matthias Seibold, P. Fürnstahl, M. Farshad, N. Navab","doi":"10.1117/12.2547581","DOIUrl":"https://doi.org/10.1117/12.2547581","url":null,"abstract":"Medical augmented reality has been actively studied for decades and many methods have been proposed torevolutionize clinical procedures. One example is the camera augmented mobile C-arm (CAMC), which providesa real-time video augmentation onto medical images by rigidly mounting and calibrating a camera to the imagingdevice. Since then, several CAMC variations have been suggested by calibrating 2D/3D cameras, trackers, andmore recently a Microsoft HoloLens to the C-arm. Different calibration methods have been applied to establishthe correspondence between the rigidly attached sensor and the imaging device. A crucial step for these methodsis the acquisition of X-Ray images or 3D reconstruction volumes; therefore, requiring the emission of ionizingradiation. In this work, we analyze the mechanical motion of the device and propose an alternatative methodto calibrate sensors to the C-arm without emitting any radiation. Given a sensor is rigidly attached to thedevice, we introduce an extended pivot calibration concept to compute the fixed translation from the sensor tothe C-arm rotation center. The fixed relationship between the sensor and rotation center can be formulated as apivot calibration problem with the pivot point moving on a locus. Our method exploits the rigid C-arm motiondescribing a Torus surface to solve this calibration problem. We explain the geometry of the C-arm motion andits relation to the attached sensor, propose a calibration algorithm and show its robustness against noise, as wellas trajectory and observed pose density by computer simulations. We discuss this geometric-based formulationand its potential extensions to different C-arm applications.","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"204 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120983840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development and in vivo application of real-time intrahepatic flow display to guide liver dissection in minimally invasive surgery (Conference Presentation) 实时肝内血流显示技术在微创手术中指导肝剥离的研制及活体应用(会议报告)

Medical Imaging: Image-Guided Procedures Pub Date : 2019-03-15 DOI: 10.1117/12.2512537

J. Cha, G. Cheon, J. Namgoong

{"title":"Development and in vivo application of real-time intrahepatic flow display to guide liver dissection in minimally invasive surgery (Conference Presentation)","authors":"J. Cha, G. Cheon, J. Namgoong","doi":"10.1117/12.2512537","DOIUrl":"https://doi.org/10.1117/12.2512537","url":null,"abstract":"The primary liver cancer including intrahepatic bile duct cancer pose significant global burden of illness\u0000with increasing incidence and mortality in US and around the world. Surgery remains the most effective\u0000form of treatment. However, surgical complication rates for medium to high complexity hepatectomies persist in 30-40% range even in highly skilled hands and at high volume centers. The critical challenges appear to be attributable to navigating liver parenchymal dissection, where size of resection surface, associated with blood loss and missed bile leaks from the liver parenchyma, and prolonged operative time during dissection pose significant obstacle. In this work, we present a new laparoscopic real-time liver flow display of subsurface liver structures (e.g., intrahepatic artery, portal vein, and bile duct) by creating a ‘Surgical Map’ to guide liver parenchymal dissection in hepatobiliary surgery. The intelligent display of intrahepatic critical structures and functional physiology in real-time can make the hepatic dissection safer and more efficient for any liver surgery. We integrated multimodal optical imaging technologies into a single laparoscopic vision tool, created a continuously evolving quantitative surgical map based on Bayesian framework, and finally validated the usefulness of Surgical Map through preclinical porcine studies.","PeriodicalId":302939,"journal":{"name":"Medical Imaging: Image-Guided Procedures","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129057734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Front Matter: Volume 9415 前题:9415卷

Medical Imaging: Image-Guided Procedures Pub Date : 2015-05-01 DOI: 10.1117/12.2184297

R. Webster, Z. Yaniv

引用次数: 0

Front Matter: Volume 8316 封面:第8316卷

Medical Imaging: Image-Guided Procedures Pub Date : 2012-02-13 DOI: 10.1117/12.929062

D. Holmes, Kenneth H. Wong

引用次数: 0