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Asia-Pacific conference on Intelligent Robot Systems (ACIRS)

作者： Sriram Marisetty Pavan Kumar Pothula Pon Deepika C K Vinay Vikas Vazhayil Madhav Rao Surgical and Assistive Robotics Lab IIIT Bangalore Department of Neurosurgery NIMHANS

ISBN: (数字)9781728198187

ISBN: (纸本)9781728198194

Mechanical drilling and perforation of bone is one of the most standard practices followed in neurosurgery, but is a highly specialised task performed by trained neurosurgeons. Craniotomy refers to removing part of the skull bone to access the underlying tissues, which is currently performed manually involving a series of precautionary procedures. The non-planar surface of the brain makes the manual drilling process over a series of marked points less accurate. guided robotic drilling is one such alternative towards the contemporary craniotomy method that leads to increased accuracy, thereby minimizing permanent secondary damages to the patient under treatment. The paper proposes a design towards achieving the first step in building an autonomous neurosurgical tool for craniotomy practices over a non-planar surface. The proposed device caters towards reaching to a specified target location in the surgical space, and orient the drilling head system perpendicular to the specified point on the non-planar surface to perform needle insertion, or deep drilling. In addition, the proposed tool follows the guided path in a perpendicular orientation along the series of drilling points on a non-planar skull surface, where the skull surface is derived from IR imaging of the patient in the operative field. The real-time 3D model of the patient's head is reconstructed post multiple scanning from the handheld portable IR camera. The developed autonomous drilling system is driven by the path planned and annotated by the neurosurgeon on the 3D model generated from the handheld IR camera in the intraoperative space. The autonomous drill positioning system is validated experimentally on a 3D printed human head, and the system placement, along with the orientation errors and accuracy in guided path showed promising results.

关键词： Three-dimensional displays Head Neurosurgery Solid modeling Bones image reconstruction

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A deep learning-based approach to identify in vivo catheter tips during photoacoustic-guided cardiac interventions

A deep learning-based approach to identify in vivo catheter ...

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conference on Photons Plus Ultrasound - imaging and Sensing

作者： Allman, Derek Assis, Fabrizio Chrispin, Jonathan Bell, Muyinatu A. Lediju Johns Hopkins Univ Dept Elect & Comp Engn Baltimore MD 21218 USA Johns Hopkins Med Inst Div Cardiol Baltimore MD 21205 USA Johns Hopkins Univ Dept Biomed Engn Baltimore MD USA Johns Hopkins Univ Dept Comp Sci Baltimore MD 21218 USA

ISBN: (纸本)9781510623996

Interventional cardiac procedures often require ionizing radiation to guide cardiac catheters to the heart. To reduce the associated risks of ionizing radiation, our group is exploring photoacoustic imaging in conjunction with robotic visual servoing, which requires segmentation of catheter tips. However, typical segmentation algorithms are susceptible to reflection artifacts. To address this challenge, signal sources can be identified in the presence of reflection artifacts using a deep neural network, as we previously demonstrated with a linear array ultrasound transducer. This paper extends our previous work to detect photoacoustic sources received by a phased array transducer, which is more common in cardiac applications. We trained a convolutional neural network ( CNN) with simulated photoacoustic channel data to identify point sources. The network was tested with an independent simulated validation data set not included during training as well as in vivo data acquired during a pig catheterization procedure. When tested on the independent simulated validation data set, the CNN correctly classified 84.2% of sources with a misclassification rate of 0.01%, and the mean absolute location error of correctly classified sources was 0.095 mm and 0.462 mm in the axial and lateral dimensions, respectively. When applied to in vivo data, the network correctly classified 91.4% of sources with a 7.86% misclassification rate. These results indicate that a CNN is capable of identifying photoacoustic sources recorded by phased array transducers, which is promising for cardiac applications.

关键词： Transducers In vivo imaging Phased arrays Photoacoustic spectroscopy Computer simulations Ultrasonography image segmentation Visualization Data acquisition robotics Machine learning Photoacoustic imaging

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Architectural Analysis on Dynamic MRI to Study Thoracic Insufficiency Syndrome

Architectural Analysis on Dynamic MRI to Study Thoracic Insu...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Sone, Jie Udupa, Jayaram K. Tong, Yubing Xiao, Liang Wu, Caiyun McDonough, Joseph Capraro, Anthony Torigian, Drew A. Campbel, Robert M., Jr. Univ Penn Med Image Proc Grp Dept Radiol 602 Goddard Bldg3710 Hamilton Walk Philadelphia PA 19104 USA Childrens Hosp Philadelphia Ctr Thorac Insufficiency Syndrome Philadelphia PA 19104 USA Nanjing Univ Sci & Technol Dept Comp Sci & Technol Nanjing 210094 Jiangsu Peoples R China

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

The major hurdles currently preventing advance and innovation in thoracic insufficiency syndrome (TIS) assessment and treatment are the lack of standardizable objective diagnostic measurement techniques that describe the 3D thoracoabdominal structures and the dynamics of respiration. Our goal is to develop, test, and evaluate a quantitative dynamic magnetic resonance imaging (QdMRI) methodology and a biomechanical understanding for deriving key quantitative parameters from free-tidal-breathing dMRI image data for describing the 3D structure and dynamics of the thoracoabdominal organs of TIS patients. In this paper, we propose an idea of a shape sketch to codify and then quantify the overall thoracic architecture, which involves the selection of 3D landmark points and computation of 3D dynamic distances over a respiratory cycle. We perform two statistical analyses of distance sketches on 25 different TIS patients to try to understand the pathophysiological mechanisms in relation to spine deformity and to quantitatively evaluate improvements from pre-operative to post-operative states. This QdMRI methodology involves developing: (1) a 4D image construction method;(2) an algorithm for the 4D segmentation of thoraco-abdominal structures;and (3) a set of key quantitative parameters. We illustrate that the TIS dynamic distance analysis method produces results previously unknown and precisely describes the morphologic and dynamic alterations of the thorax in TIS. A set of 3D thoracoabdominal distances and/or distance differences enables the precise estimation of key measures such as left & right differences, differences over tidal breathing, and differences from pre- to post-operative condition.

关键词： Thoracic insufficiency syndrome dynamic magnetic resonance imaging dynamic distance analysis

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Pipeline to Build and Test Robust 3D T1 Mapping-Based Heart Models for EP interventions: Preliminary Results 10th

Pipeline to Build and Test Robust 3D T1 Mapping-Based Heart ...

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10th International conference on Functional imaging and modeling of the Heart (FIMH)

作者： Li, Mengyuan Sermesant, Maxime Ferguson, Sebastian Guo, Fumin Barry, Jen Qi, Xiuling Lin, Peter Ng, Matthew Wright, Graham Pop, Mihaela Sunnybrook Res Inst Toronto ON Canada Univ Toronto Med Biophys Toronto ON Canada INRIA Epione Grp Sophia Antipolis France

ISBN: (纸本)9783030219499;9783030219482

Computational models are powerful tools in electrophysiology (EP), helping us understand and predict arrhythmia associated with heart attack (i.e., myocardial infarction), a major cause of sudden cardiac death. Our broad aim is to combine novel scar imaging methods with fast computational models to enable accurate predictions of electrical wave propagation, and then to test these models in preclinical frameworks prior to clinical translation. In this work we used n = 3 swine with chronic infarct, which underwent MR followed by conventional x-ray guided electro-anatomical EP mapping. For scar imaging, we employed our T1-mapping MR method based on multi-contrast late enhancement (MCLE) at 1 x 1 mm in-plane resolution and 5 mm slice thickness. Next, we used the MCLE images as input to a fuzzy-logic algorithm and segmented the infarcted area into two zones: infarct core IC (dense fibrosis) and grey-zone, GZ (i.e., arrhythmia substrate). We further built 3D heart models from the stack of segmented 2D MCLE images, integrating tissue zones (healthy, IC and GZ) into detailed tetrahedral heart meshes (similar to 1.5 mm element size). Finally, we investigated the accuracy of model predictions by comparing measured maps of activation times (i.e., depolarization times) with simulated maps obtained by employing a macroscopic formalism and reaction-diffusion equations. We obtained an acceptable small mean absolute error between the simulated and measured depolarization times (similar to 12 ms, in average). Future work will focus on refining MR imaging resolution and use the models to guide ablation procedures.

关键词： Cardiac MRI T1-mapping Modelling Electrophysiology

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Real-time workflow detection using webcam video for providing real-time feedback in central venous catheterization training

Real-time workflow detection using webcam video for providin...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Hisey, Rebecca Ungi, Tamas Holden, Matthew Baum, Zachary Keri, Zsuzsanna McCallum, Caitlin Howes, Daniel W. Fichtinger, Gabor Queens Univ Sch Comp Lab Percutaneous Surg Kingston ON Canada Kingston Gen Hosp Dept Crit Care Med Kingston ON Canada

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

Purpose: medical schools are shifting from a time-based approach to a competency-based education approach. A competency-based approach requires continuous observation and evaluation of trainees. The goal of Central Line Tutor is to be able to provide instruction and real-time feedback for trainees learning the procedure of central venous catheterization, without requiring a continuous expert observer. The purpose of this study is to test the accuracy of the workflow detection method of Central Line Tutor. This study also looks at the effectiveness of object recognition from a webcam video for workflow detection. Methods: Five trials of the procedure were recorded from Central Line Tutor. Five reviewers were asked to identify the timestamp of the transition points in each recording. Reviewer timestamps were compared to those identified by Central Line Tutor. Differences between these values were used to calculate average transitional delay. Results: Central Line Tutor was able to identify 100% of transition points in the procedure with an average transitional delay of -1.46 +/- 0.81s. The average transitional delay of EM and webcam tracked steps were -0.35 +/- 2.51s and -2.46 +/- 3.57s respectively. Conclusions: Central line tutor was able to detect completion of all workflow tasks with minimal delay and may be used to provide trainees with real-time feedback. The results also show that object recognition from a webcam video is an effective method for detecting workflow tasks in the procedure of central venous catheterization.

关键词： Video Ultrasonography Object recognition RGB color model 3D modeling 3D displays 3D image processing Human-machine interfaces Sensors Visualization

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Automatic Definition of Surgical Trajectories and Acceptance Window in Pelvic Trauma Surgery Using Deformable Registration

Automatic Definition of Surgical Trajectories and Acceptance...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Han, R. Ramsay, B. De Silva, T. Goerres, J. Uneri, A. Ketcha, M. Jacobson, M. Sheth, N. Vogt, S. Kleinszig, G. Osgood, G. Siewerdsen, J. H. Johns Hopkins Univ Dept Biomed Engn Baltimore MD 21218 USA Siemens Healthineers Erlangen Germany Johns Hopkins Univ Hosp Dept Orthopaed Surg Baltimore MD 21287 USA

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

Purpose: Pelvic screw insertion for percutaneous fixation is a challenging surgical procedure that requires interpretation of complex 3D anatomy from 2D fluoroscopic images. Extensive surgical training is needed and trial and error often occurs in device placement, causing extended fluoroscopy time and increased radiation dose. A system is reported for automatic definition of acceptable surgical trajectories to facilitate guidance and quality assurance in a manner consistent with surgical workflow. Methods: An atlas was constructed with segmented pelvis shapes containing standard reference trajectories for screw placement. A statistical shape model computed from the atlas is used for deformable registration to the patient's preoperative CT (without segmentation). By transferring the reference trajectories and surrounding acceptance windows (i.e., volumetric corridors of acceptable device placement) from the atlas, the system automatically computes reliable K-wire and screw trajectories for guidance (overlay in fluoroscopy) and QA. Results: A leave-one-out analysis was performed to evaluate the accuracy or registration and overlay. The registration achieved average surface registration accuracy of 1.82 +/- 0.39 mm. Automatically determined trajectories conformed within acceptable cortical bone margins, maintaining 3.75 +/- 0.68 mm distance from cortex in narrow bone corridors and demonstrating accurate registration and surgical trajectory definition without breaching cortex. Conclusions: The framework proposed in this work allows for multi-atlas based automatic planning of surgical trajectory without tracker or manual segmentation. The planning information can be further used to facilitate intraoperative guidance and post-operatively quality assurance in a manner consistent with surgical workflow.

关键词： image registration image segmentation Bone Surgery Computed tomography Binary data Fluoroscopy Error analysis Principal component analysis Statistical modeling

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Tumor Margin Classification of Head and Neck Cancer Using Hyperspectral imaging and Convolutional Neural Networks

Tumor Margin Classification of Head and Neck Cancer Using Hy...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Halicek, Martin Little, James V. Wang, Xu Patel, Mihir Griffith, Christopher C. Chen, Amy Y. Fei, Baowei Georgia Inst Technol Atlanta GA 30332 USA Emory Univ Wallace H Coulter Dept Biomed Engn Atlanta GA 30322 USA Augusta Univ Med Coll Georgia Augusta GA USA Emory Univ Sch Med Dept Pathol & Lab Med Atlanta GA 30322 USA Emory Univ Sch Med Dept Hematol & Med Oncol Atlanta GA USA Emory Univ Sch Med Dept Otolaryngol Atlanta GA 30322 USA Emory Univ Winship Canc Inst Atlanta GA 30322 USA Emory Univ Dept Math & Comp Sci Atlanta GA 30322 USA Emory Univ Dept Radiol & Imaging Sci Atlanta GA 30322 USA

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

One of the largest factors affecting disease recurrence after surgical cancer resection is negative surgical margins. Hyperspectral imaging (HSI) is an optical imaging technique with potential to serve as a computer aided diagnostic tool for identifying cancer in gross ex-vivo specimens. We developed a tissue classifier using three distinct convolutional neural network (CNN) architectures on HSI data to investigate the ability to classify the cancer margins from ex-vivo human surgical specimens, collected from 20 patients undergoing surgical cancer resection as a preliminary validation group. A new approach for generating the HSI ground truth using a registered histological cancer margin is applied in order to create a validation dataset. The CNN-based method classifies the tumor-normal margin of squamous cell carcinoma (SCCa) versus normal oral tissue with an area under the curve (AUC) of 0.86 for inter-patient validation, performing with 81% accuracy, 84% sensitivity, and 77% specificity. Thyroid carcinoma cancer-normal margins are classified with an AUC of 0.94 for inter-patient validation, performing with 90% accuracy, 91% sensitivity, and 88% specificity. Our preliminary results on a limited patient dataset demonstrate the predictive ability of HSI-based cancer margin detection, which warrants further investigation with more patient data and additional processing techniques to optimize the proposed deep learning method.

关键词： Hyperspectral imaging convolutional neural network deep learning cancer margin detection intraoperative imaging head and neck surgery head and neck cancer

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Technical note: Probabilistic visual and electromagnetic data fusion for robust drift-free sequential mosaicking. Application to fetoscopy

Technical note: Probabilistic visual and electromagnetic dat...

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conference on medical imaging - image-guided procedures, robotic interventions, and modeling

作者： Tella-Amo, Marcel Peter, Loic Shakir, Dzhoshkun I. Deprest, Jan Stoyanov, Danail Iglesias, Juan Eugenio Vercauteren, Tom Ourselin, Sebastien UCL Wellcome EPSRC Ctr Intervent & Surg Sci 66-72 Gower St London WC1E 6AA England UCL Translat Imaging Grp CMIC Med Phys 8-18 Malet Pl Engn Bldg London WC1E 6B England Katholieke Univ Leuven Ctr Surg Technol Fac Med Herestr 49 B-3000 Leuven Belgium

ISBN: (数字)9781510616424

ISBN: (纸本)9781510616424

The most effective treatment for Twin-to-Twin Transfusion Syndrome is laser photocoagulation of the shared vascular anastomoses in the placenta. Vascular connections are extremely challenging to locate due to their caliber and the reduced field of view of the fetoscope. Therefore, mosaicking techniques are beneficial to expand the scene, facilitate navigation and allow vessel photocoagulation decision-making. Local vision-based mosaicking algorithms inherently drift over time due to the use of pairwise transformations. We propose the use of an electromagnetic tracker (EMT) sensor mounted at the tip of the fetoscope to obtain camera pose measurements, which we incorporate into a probabilistic framework with frame-to-frame visual information to achieve globally consistent sequential mosaics. We parametrize the problem in terms of plane and camera poses constrained by EMT measurements to enforce global consistency while leveraging pairwise image relationships in a sequential fashion through the use of Local Bundle Adjustment. We show that our approach is drift-free and performs similarly to state-of-the-art global alignment techniques like Bundle Adjustment albeit with much less computational burden. Additionally, we propose a version of Bundle Adjustment that uses EMT information. We demonstrate the robustness to EMT noise and loss of visual information and evaluate mosaics for synthetic, phantom-based and ex vivo datasets.

关键词： Fetoscopy laser coagulation TTTS sequential mosaicking globally consistent mosaicking electromagnetic tracking sensor fusion

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AN ELECTROMAGNETIC TRACKING NEEDLE CLIP: AN ENABLING DESIGN FOR LOW-COST image-guided THERAPY

AN ELECTROMAGNETIC TRACKING NEEDLE CLIP: AN ENABLING DESIGN ...

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Design of medical Devices conference

作者： Zhao, Zhuo Xu, Sheng Wood, Bradford Tse, Zion Tsz Ho Univ Georgia Sch Elect & Comp Engn Athens GA 30602 USA Natl Inst Biomed Imaging & Bioengn Ctr Intervent Oncol Radiol & Imaging Sci NIH Clin Ctr Bethesda MD USA NCI Ctr Canc Res NIH Bethesda MD 20892 USA 3T Technol LLC Athens GA USA

ISBN: (纸本)9780791840788

Computer-assisted interventions (CAI) — which offer advantages such as increased accuracy, reduction of complications, and decreased intervention time — have increased in prevalence in recent years. A type of CAI called image-guided therapy (IGT) can be used to provide navigation for freehand procedures or guidance for localization of medical devices. Electromagnetic (EM) tracking technology can track instruments such as needle tips inside the patient body without the need for a line-of-sight, allowing for minimally invasive imaging-guided procedures [1–3].

关键词： Design image guided treatment needles

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Automatic planning of needle placement for robot-assisted percutaneous procedures

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INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2018年第9期13卷 1429-1438页

作者： Belbachir, Esia Golkar, Ehsan Bayle, Bernard Essert, Caroline Univ Strasbourg CNRS UMR 7357 ICube 300 Bd Sebastien BrantBP 10413 F-67412 Illkirch Graffenstaden France Univ Bourgogne Franche Comte UTBM Belfort France

PurposePercutaneous procedures allow interventional radiologists to perform diagnoses or treatments guided by an imaging device, typically a computed tomography (CT) scanner with a high spatial resolution. To reduce exposure to radiations and improve accuracy, robotic assistance to needle insertion is considered in the case of X-ray guided procedures. We introduce a planning algorithm that computes a needle placement compatible with both the patient's anatomy and the accessibility of the robot within the scanner *** preoperative planning approach is based on inverse kinematics, fast collision detection, and bidirectional rapidly exploring random trees coupled with an efficient strategy of node addition. The algorithm computes the allowed needle entry zones over the patient's skin (accessibility map) from 3D models of the patient's anatomy, the environment (CT, bed), and the robot. The result includes the admissible robot joint path to target the prescribed internal point, through the entry point. A retrospective study was performed on 16 patients datasets in different conditions: without robot (WR) and with the robot on the left or the right side of the bed (RL/RR).ResultsWe provide an accessibility map ensuring a collision-free path of the robot and allowing for a needle placement compatible with the patient's anatomy. The result is obtained in an average time of about 1min, even in difficult cases. The accessibility maps of RL and RR covered about a half of the surface of WR map in average, which offers a variety of options to insert the needle with the robot. We also measured the average distance between the needle and major obstacles such as the vessels and found that RL and RR produced needle placements almost as safe as *** introduced planning method helped us prove that it is possible to use such a general purpose redundant manipulator equipped with a dedicated tool to perform percutaneous interventions in cluttered spaces like a CT

关键词： Preoperative planning Decision-making process Robot-assisted interventions Interventional radiology

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