1,400 results match your criteria International Journal of Computer Assisted Radiology and Surgery [Journal]


Learning soft tissue behavior of organs for surgical navigation with convolutional neural networks.

Int J Comput Assist Radiol Surg 2019 Apr 16. Epub 2019 Apr 16.

National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.

Purpose: In surgical navigation, pre-operative organ models are presented to surgeons during the intervention to help them in efficiently finding their target. In the case of soft tissue, these models need to be deformed and adapted to the current situation by using intra-operative sensor data. A promising method to realize this are real-time capable biomechanical models. Read More

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http://dx.doi.org/10.1007/s11548-019-01965-7DOI Listing

Pedicle screw navigation using surface digitization on the Microsoft HoloLens.

Int J Comput Assist Radiol Surg 2019 Apr 15. Epub 2019 Apr 15.

Computer Assisted Research and Development Group, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.

Purpose: In spinal fusion surgery, imprecise placement of pedicle screws can result in poor surgical outcome or may seriously harm a patient. Patient-specific instruments and optical systems have been proposed for improving precision through surgical navigation compared to freehand insertion. However, existing solutions are expensive and cannot provide in situ visualizations. Read More

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http://dx.doi.org/10.1007/s11548-019-01973-7DOI Listing

Implicit domain adaptation with conditional generative adversarial networks for depth prediction in endoscopy.

Int J Comput Assist Radiol Surg 2019 Apr 15. Epub 2019 Apr 15.

Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, UK.

Purpose: Colorectal cancer is the third most common cancer worldwide, and early therapeutic treatment of precancerous tissue during colonoscopy is crucial for better prognosis and can be curative. Navigation within the colon and comprehensive inspection of the endoluminal tissue are key to successful colonoscopy but can vary with the skill and experience of the endoscopist. Computer-assisted interventions in colonoscopy can provide better support tools for mapping the colon to ensure complete examination and for automatically detecting abnormal tissue regions. Read More

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http://dx.doi.org/10.1007/s11548-019-01962-wDOI Listing

Design optimization of a contact-aided continuum robot for endobronchial interventions based on anatomical constraints.

Int J Comput Assist Radiol Surg 2019 Apr 15. Epub 2019 Apr 15.

The Hamlyn Centre for Robotic Surgery, Imperial College London, London, SW7 2AZ, UK.

Purpose: A laser-profiled continuum robot (CR) with a series of interlocking joints has been developed in our center to reach deeper areas of the airways. However, it deflects with constant curvature, which thus increases the difficulty of entering specific bronchi without relying on the tissue reaction forces. This paper aims to propose an optimization framework to find the best design parameters for nonconstant curvature CRs to reach distal targets while attempting to avoid the collision with the surrounding tissue. Read More

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http://dx.doi.org/10.1007/s11548-019-01972-8DOI Listing

High-precision evaluation of electromagnetic tracking.

Int J Comput Assist Radiol Surg 2019 Apr 13. Epub 2019 Apr 13.

Department of Computer Science, Technischer Universität Darmstadt, Darmstadt, Germany.

Purpose: Navigation in high-precision minimally invasive surgery (HP-MIS) demands high tracking accuracy in the absence of line of sight (LOS). Currently, no tracking technology can satisfy this requirement. Electromagnetic tracking (EMT) is the best tracking paradigm in the absence of LOS despite limited accuracy and robustness. Read More

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http://dx.doi.org/10.1007/s11548-019-01959-5DOI Listing

Preliminary results of DSA denoising based on a weighted low-rank approach using an advanced neurovascular replication system.

Int J Comput Assist Radiol Surg 2019 Apr 12. Epub 2019 Apr 12.

Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.

Purpose: 2D digital subtraction angiography (DSA) has become an important technique for interventional neuroradiology tasks, such as detection and subsequent treatment of aneurysms. In order to provide high-quality DSA images, usually undiluted contrast agent and a high X-ray dose are used. The iodinated contrast agent puts a burden on the patients' kidneys while the use of high-dose X-rays expose both patients and medical staff to a considerable amount of radiation. Read More

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http://link.springer.com/10.1007/s11548-019-01968-4
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http://dx.doi.org/10.1007/s11548-019-01968-4DOI Listing
April 2019
1 Read

A novel gaze-supported multimodal human-computer interaction for ultrasound machines.

Int J Comput Assist Radiol Surg 2019 Apr 11. Epub 2019 Apr 11.

Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.

Purpose: Conventional ultrasound (US) machines employ a physical control panel (PCP) as the primary user interface for machine control. This panel is adjacent to the main machine display that requires the operator's constant attention. The switch of attention to the control panel can lead to interruptions in the flow of the medical examination. Read More

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http://link.springer.com/10.1007/s11548-019-01964-8
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http://dx.doi.org/10.1007/s11548-019-01964-8DOI Listing
April 2019
2 Reads

Objective assessment of intraoperative technical skill in capsulorhexis using videos of cataract surgery.

Int J Comput Assist Radiol Surg 2019 Apr 11. Epub 2019 Apr 11.

Johns Hopkins University, 3400 N. Charles Street, Malone Hall 340, Baltimore, MD, 21218, USA.

Purpose: Objective assessment of intraoperative technical skill is necessary for technology to improve patient care through surgical training. Our objective in this study was to develop and validate deep learning techniques for technical skill assessment using videos of the surgical field.

Methods: We used a data set of 99 videos of capsulorhexis, a critical step in cataract surgery. Read More

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http://link.springer.com/10.1007/s11548-019-01956-8
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http://dx.doi.org/10.1007/s11548-019-01956-8DOI Listing
April 2019
1 Read

Prostate cancer detection using residual networks.

Int J Comput Assist Radiol Surg 2019 Apr 10. Epub 2019 Apr 10.

Ezra AI Canada, Unit 310, 545 King St. West, Toronto, Canada.

Purpose: To automatically identify regions where prostate cancer is suspected on multi-parametric magnetic resonance images (mp-MRI).

Methods: A residual network was implemented based on segmentations from an expert radiologist on T2-weighted, apparent diffusion coefficient map, and high b-value diffusion-weighted images. Mp-MRIs from 346 patients were used in this study. Read More

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http://dx.doi.org/10.1007/s11548-019-01967-5DOI Listing

Weakly supervised convolutional LSTM approach for tool tracking in laparoscopic videos.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

ICube, University of Strasbourg, CNRS, IHU, Strasbourg, France.

Purpose: Real-time surgical tool tracking is a core component of the future intelligent operating room (OR), because it is highly instrumental to analyze and understand the surgical activities. Current methods for surgical tool tracking in videos need to be trained on data in which the spatial positions of the tools are manually annotated. Generating such training data is difficult and time-consuming. Read More

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http://dx.doi.org/10.1007/s11548-019-01958-6DOI Listing

Active learning using deep Bayesian networks for surgical workflow analysis.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

Department for Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.

Purpose: For many applications in the field of computer-assisted surgery, such as providing the position of a tumor, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery, methods for surgical workflow analysis are a prerequisite. Often machine learning-based approaches serve as basis for analyzing the surgical workflow. In general, machine learning algorithms, such as convolutional neural networks (CNN), require large amounts of labeled data. Read More

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http://dx.doi.org/10.1007/s11548-019-01963-9DOI Listing

Cervical cell recognition based on AGVF-Snake algorithm.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

School of Electrical and Information Engineering, Tianjin University, 92 Weijin Road, Tianjin, China.

Purpose: In recent years, with the increasing incidence of cervical cancer, it is a tedious and time-consuming task with unsatisfying accuracy to manually recognize the cells. Machine recognition can be a good solution, but it suffers from the difficulty of obtaining precise edges of cells, which directly influence the final recognition accuracy. To improve the recognition accuracy and shorten the time used for cell recognition, an AGVF-Snake (Adaptive Gradient Vector Flow-Snake) model for the extraction of cell edges has been proposed in this paper. Read More

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http://link.springer.com/10.1007/s11548-019-01961-x
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http://dx.doi.org/10.1007/s11548-019-01961-xDOI Listing
April 2019
1 Read

Face detection in the operating room: comparison of state-of-the-art methods and a self-supervised approach.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

ICube, University of Strasbourg, CNRS, IHU Strasbourg, Strasbourg, France.

Purpose: Face detection is a needed component for the automatic analysis and assistance of human activities during surgical procedures. Efficient face detection algorithms can indeed help to detect and identify the persons present in the room and also be used to automatically anonymize the data. However, current algorithms trained on natural images do not generalize well to the operating room (OR) images. Read More

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http://dx.doi.org/10.1007/s11548-019-01944-yDOI Listing

Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

Department for Translational Surgical Oncology, National Center for Tumor Diseases (NCT), Partner Site Dresden, Dresden, Germany.

Purpose: The course of surgical procedures is often unpredictable, making it difficult to estimate the duration of procedures beforehand. This uncertainty makes scheduling surgical procedures a difficult task. A context-aware method that analyses the workflow of an intervention online and automatically predicts the remaining duration would alleviate these problems. Read More

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http://link.springer.com/10.1007/s11548-019-01966-6
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http://dx.doi.org/10.1007/s11548-019-01966-6DOI Listing
April 2019
1 Read

Catheter localization in 3D ultrasound using voxel-of-interest-based ConvNets for cardiac intervention.

Int J Comput Assist Radiol Surg 2019 Apr 9. Epub 2019 Apr 9.

Eindhoven University of Technology, Eindhoven, The Netherlands.

Purpose: Efficient image-based catheter localization in 3D US during cardiac interventions is highly desired, since it facilitates the operation procedure, reduces the patient risk and improves the outcome. Current image-based catheter localization methods are not efficient or accurate enough for real clinical use.

Methods: We propose a catheter localization method for 3D cardiac ultrasound (US). Read More

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http://dx.doi.org/10.1007/s11548-019-01960-yDOI Listing

Flexible needle and patient tracking using fractional scanning in interventional CT procedures.

Int J Comput Assist Radiol Surg 2019 Apr 8. Epub 2019 Apr 8.

CASMIP Laboratory, School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.

Purpose: We present a new method for flexible needle and patient localization in interventional CT procedures based on fractional CT scanning. Our method accurately localizes the trajectory of a flexible needle to which a spherical marker is attached at a known distance from the tip with respect to a baseline scan of patient in the CT scanner coordinate frame.

Methods: The localization is achieved with a significantly lower dose compared to a full scan using sparse view angle sampling and without reconstructing the CT image of the repeat scan. Read More

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http://dx.doi.org/10.1007/s11548-019-01945-xDOI Listing

Integrated datasets of normalized brain with functional localization using intra-operative electrical stimulation.

Int J Comput Assist Radiol Surg 2019 Apr 6. Epub 2019 Apr 6.

Faculty of Advanced Techno-Surgery, Institute of Advanced Biomedical Engineering and Science, Tokyo Women's Medical University, 8-1 (TWIns) Kawada-cho, Shinjuku-ku, Tokyo, 162-8666, Japan.

Purpose: The purpose of this study was to transform brain mapping data into a digitized intra-operative MRI and integrated brain function dataset for predictive glioma surgery considering tumor resection volume, as well as the intra-operative and postoperative complication rates.

Methods: Brain function data were transformed into digitized localizations on a normalized brain using a modified electric stimulus probe after brain mapping. This normalized brain image with functional information was then projected onto individual patient's brain images including predictive brain function data. Read More

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http://dx.doi.org/10.1007/s11548-019-01957-7DOI Listing
April 2019
1.659 Impact Factor

Automatic biplane left ventricular ejection fraction estimation with mobile point-of-care ultrasound using multi-task learning and adversarial training.

Int J Comput Assist Radiol Surg 2019 Apr 2. Epub 2019 Apr 2.

The University of British Columbia, Vancouver, Canada.

Purpose: Left ventricular ejection fraction (LVEF) is one of the key metrics to assess the heart functionality, and cardiac ultrasound (echo) is a standard imaging modality for EF measurement. There is an emerging interest to exploit the point-of-care ultrasound (POCUS) usability due to low cost and ease of access. In this work, we aim to present a computationally efficient mobile application for accurate LVEF estimation. Read More

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http://dx.doi.org/10.1007/s11548-019-01954-wDOI Listing

Four-dimensional fully convolutional residual network-based liver segmentation in Gd-EOB-DTPA-enhanced MRI.

Int J Comput Assist Radiol Surg 2019 Mar 30. Epub 2019 Mar 30.

Department of Radiology, the University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.

Purpose: Gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) tends to show higher diagnostic accuracy than other modalities. There is a demand for computer-assisted detection (CAD) software for Gd-EOB-DTPA-enhanced MRI. Segmentation with high accuracy is important for CAD software. Read More

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http://dx.doi.org/10.1007/s11548-019-01935-zDOI Listing
March 2019
1 Read
1.659 Impact Factor

The hind- and midfoot alignment computed after a medializing calcaneal osteotomy using a 3D weightbearing CT.

Int J Comput Assist Radiol Surg 2019 Mar 26. Epub 2019 Mar 26.

Department of Orthopaedics, Ghent University Hospital, Corneel Heymanslaan 10, 9000, Ghent, OVL, Belgium.

Purpose: A medializing calcaneal osteotomy (MCO) is a surgical procedure frequently performed to correct an adult acquired flatfoot (AAFD) deformity. However, most studies are limited to a 2D analysis of 3D deformity. Therefore, the aim is to perform a 3D assessment of the hind- and midfoot alignment using a weightbearing CT (WBCT) preoperatively as well as postoperatively. Read More

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http://dx.doi.org/10.1007/s11548-019-01949-7DOI Listing

Learning needle tip localization from digital subtraction in 2D ultrasound.

Int J Comput Assist Radiol Surg 2019 Mar 25. Epub 2019 Mar 25.

Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, 08854, USA.

Purpose: This paper addresses localization of needles inserted both in-plane and out-of-plane in challenging ultrasound-guided interventions where the shaft and tip have low intensity. Our approach combines a novel digital subtraction scheme for enhancement of low-level intensity changes caused by tip movement in the ultrasound image and a state-of-the-art deep learning scheme for tip detection.

Methods: As the needle tip moves through tissue, it causes subtle spatiotemporal variations in intensity. Read More

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http://dx.doi.org/10.1007/s11548-019-01951-zDOI Listing

Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies.

Int J Comput Assist Radiol Surg 2019 Mar 23. Epub 2019 Mar 23.

Queen's University, Kingston, ON, Canada.

Prostate cancer (PCa) is the most frequent noncutaneous cancer in men. Early detection of PCa is essential for clinical decision making, and reducing metastasis and mortality rates. The current approach for PCa diagnosis is histopathologic analysis of core biopsies taken under transrectal ultrasound guidance (TRUS-guided). Read More

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http://dx.doi.org/10.1007/s11548-019-01950-0DOI Listing

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks.

Int J Comput Assist Radiol Surg 2019 Mar 22. Epub 2019 Mar 22.

Computer Assisted Medical Interventions, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 223, 69120, Heidelberg, Germany.

Purpose: Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to address the inverse problem of converting pixel-wise multispectral reflectance measurements to underlying tissue parameters, such as oxygenation. Assessment of the specific hardware used in conjunction with such algorithms, however, has not properly addressed the possibility that the problem may be ill-posed. Read More

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http://link.springer.com/10.1007/s11548-019-01939-9
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http://dx.doi.org/10.1007/s11548-019-01939-9DOI Listing
March 2019
2 Reads

Estimation of tissue oxygen saturation from RGB images and sparse hyperspectral signals based on conditional generative adversarial network.

Int J Comput Assist Radiol Surg 2019 Mar 21. Epub 2019 Mar 21.

The Hamlyn Centre for Robotic Surgery, Imperial College London, London, UK.

Purpose: Intra-operative measurement of tissue oxygen saturation ([Formula: see text]) is important in detection of ischaemia, monitoring perfusion and identifying disease. Hyperspectral imaging (HSI) measures the optical reflectance spectrum of the tissue and uses this information to quantify its composition, including [Formula: see text]. However, real-time monitoring is difficult due to capture rate and data processing time. Read More

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http://dx.doi.org/10.1007/s11548-019-01940-2DOI Listing
March 2019
1 Read

Semantic segmentation and detection of mediastinal lymph nodes and anatomical structures in CT data for lung cancer staging.

Int J Comput Assist Radiol Surg 2019 Mar 19. Epub 2019 Mar 19.

Medical Technology Department, SINTEF, Trondheim, Norway.

Purpose: Accurate lung cancer diagnosis is crucial to select the best course of action for treating the patient. From a simple chest CT volume, it is necessary to identify whether the cancer has spread to nearby lymph nodes or not. It is equally important to know precisely where each malignant lymph node is with respect to the surrounding anatomical structures and the airways. Read More

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http://dx.doi.org/10.1007/s11548-019-01948-8DOI Listing

Deformable multimodal registration for navigation in beating-heart cardiac surgery.

Int J Comput Assist Radiol Surg 2019 Mar 19. Epub 2019 Mar 19.

Queen's University, Kingston, K7L 3N6, Canada.

Purpose: Minimally invasive beating-heart surgery is currently performed using endoscopes and without navigation. Registration of intraoperative ultrasound to a preoperative cardiac CT scan is a valuable step toward image-guided navigation.

Methods: The registration was achieved by first extracting a representative point set from each ultrasound image in the sequence using a deformable registration. Read More

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http://dx.doi.org/10.1007/s11548-019-01932-2DOI Listing
March 2019
1 Read

Toward an automatic preoperative pipeline for image-guided temporal bone surgery.

Int J Comput Assist Radiol Surg 2019 Mar 19. Epub 2019 Mar 19.

Department of Computer Science, Technische Universität Darmstadt, Darmstadt, Germany.

Purpose: Minimally invasive surgery is often built upon a time-consuming preoperative step consisting of segmentation and trajectory planning. At the temporal bone, a complete automation of these two tasks might lead to faster interventions and more reproducible results, benefiting clinical workflow and patient health.

Methods: We propose an automatic segmentation and trajectory planning pipeline for image-guided interventions at the temporal bone. Read More

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http://link.springer.com/10.1007/s11548-019-01937-x
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http://dx.doi.org/10.1007/s11548-019-01937-xDOI Listing
March 2019
2 Reads

Preliminary study of an RNN-based active interventional robotic system (AIRS) in retinal microsurgery.

Int J Comput Assist Radiol Surg 2019 Mar 18. Epub 2019 Mar 18.

LCSR, Johns Hopkins University, Baltimore, MD, 21218, USA.

Purpose: Retinal microsurgery requires highly dexterous and precise maneuvering of instruments inserted into the eyeball through the sclerotomy port. During such procedures, the sclera can potentially be injured from extreme tool-to-sclera contact force caused by surgeon's unintentional misoperations.

Methods: We present an active interventional robotic system to prevent such iatrogenic accidents by enabling the robotic system to actively counteract the surgeon's possible unsafe operations in advance of their occurrence. Read More

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http://dx.doi.org/10.1007/s11548-019-01947-9DOI Listing

Optimization of electronic prescription for parallel external fixator based on genetic algorithm.

Int J Comput Assist Radiol Surg 2019 May 18;14(5):861-871. Epub 2019 Mar 18.

School of Artificial Intelligence and Data Science, Hebei University of Technology, No. 8 Guangrong Road, Hong Qiao, Tianjin, 300130, China.

Purpose: For the parallel external fixator, there are some defects, such as uneven distraction rate, unbearable pain and uncontrollable movement trajectory in practical clinical applications. In order to solve the problems, a new deformity correction algorithm, which is used to calculate the elongation of the six struts, is developed. Meanwhile, the corresponding computer software for getting the electronic prescription is developed. Read More

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http://dx.doi.org/10.1007/s11548-019-01931-3DOI Listing
May 2019
2 Reads

Automatic self-gated 4D-MRI construction from free-breathing 2D acquisitions applied on liver images.

Int J Comput Assist Radiol Surg 2019 Mar 18. Epub 2019 Mar 18.

Polytechnique Montreal, Montreal, Canada.

Purpose: MRI slice reordering is a necessary step when three-dimensional (3D) motion of an anatomical region of interest has to be extracted from multiple two-dimensional (2D) dynamic acquisition planes, e.g., for the construction of motion models used for image-guided radiotherapy. Read More

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http://dx.doi.org/10.1007/s11548-019-01941-1DOI Listing

A novel image-based retrieval system for characterization of maxillofacial lesions in cone beam CT images.

Int J Comput Assist Radiol Surg 2019 May 14;14(5):785-796. Epub 2019 Mar 14.

Graduate School of Information Science, Nara Institute of Science and Technology (NAIST), 8916-5, Takayama, Ikoma, Nara, 630-0192, Japan.

Purpose: The objective of medical content-based image retrieval (CBIR) is to assist clinicians in decision making by retrieving the most similar cases to a given query image from a large database. Herein, a new method for content-based image retrieval of cone beam CT (CBCT) scans is presented.

Methods: The introduced framework consists of two main phases: training database construction and querying. Read More

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http://dx.doi.org/10.1007/s11548-019-01946-wDOI Listing
May 2019
1 Read

Liver segmentation from low-radiation-dose pediatric computed tomography using patient-specific, statistical modeling.

Int J Comput Assist Radiol Surg 2019 Mar 14. Epub 2019 Mar 14.

Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan.

Purpose: The pediatric computed tomography (CT) volume is acquired at a low dose because radiation is harmful to young children. Consequently, the pediatric CT volume has lower signal-to-noise ratio, which makes organ segmentation difficult. In this paper, we propose a liver segmentation algorithm for pediatric CT scan using a patient-specific level set distribution model (LSDM). Read More

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http://dx.doi.org/10.1007/s11548-019-01929-xDOI Listing

Automatic segmentation of bone surfaces from ultrasound using a filter-layer-guided CNN.

Int J Comput Assist Radiol Surg 2019 May 13;14(5):775-783. Epub 2019 Mar 13.

Department of Biomedical Engineering, Rutgers University, Piscataway, NJ, USA.

Purpose: Ultrasound (US) provides real-time, two-/three-dimensional safe imaging. Due to these capabilities, it is considered a safe alternative to intra-operative fluoroscopy in various computer-assisted orthopedic surgery (CAOS) procedures. However, interpretation of the collected bone US data is difficult due to high levels of noise, various imaging artifacts, and bone surfaces response appearing several millimeters (mm) in thickness. Read More

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http://dx.doi.org/10.1007/s11548-019-01934-0DOI Listing
May 2019
1 Read

On the feasibility of transperineal 3D ultrasound image guidance for robotic radical prostatectomy.

Int J Comput Assist Radiol Surg 2019 Mar 13. Epub 2019 Mar 13.

Department of Electrical and Computer Engineering, University of British Columbia, 2332 Main Mall, Vancouver, BC, V6T 1Z4, Canada.

Purpose: Prostate cancer is the most prevalent form of male-specific cancers. Robot-assisted laparoscopic radical prostatectomy (RALRP) using the da Vinci surgical robot has become the gold-standard treatment for organ-confined prostate cancer. To improve intraoperative visualization of anatomical structures, many groups have developed techniques integrating transrectal ultrasound (TRUS) into the surgical workflow. Read More

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http://link.springer.com/10.1007/s11548-019-01938-w
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http://dx.doi.org/10.1007/s11548-019-01938-wDOI Listing
March 2019
5 Reads

Interactive Flying Frustums (IFFs): spatially aware surgical data visualization.

Int J Comput Assist Radiol Surg 2019 Mar 12. Epub 2019 Mar 12.

Computer Aided Medical Procedures, Johns Hopkins University, Baltimore, MD, USA.

Purpose: As the trend toward minimally invasive and percutaneous interventions continues, the importance of appropriate surgical data visualization becomes more evident. Ineffective interventional data display techniques that yield poor ergonomics that hinder hand-eye coordination, and therefore promote frustration which can compromise on-task performance up to adverse outcome. A very common example of ineffective visualization is monitors attached to the base of mobile C-arm X-ray systems. Read More

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http://link.springer.com/10.1007/s11548-019-01943-z
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http://dx.doi.org/10.1007/s11548-019-01943-zDOI Listing
March 2019
3 Reads

Unifying the seeds auto-generation (SAGE) with knee cartilage segmentation framework: data from the osteoarthritis initiative.

Int J Comput Assist Radiol Surg 2019 May 11;14(5):755-762. Epub 2019 Mar 11.

Diagnostic Imaging Services, KPJ Ipoh Specialist Hospital, 30350, Ipoh, Perak, Malaysia.

Purpose: Manual segmentation is sensitive to operator bias, while semiautomatic random walks segmentation offers an intuitive approach to understand the user knowledge at the expense of large amount of user input. In this paper, we propose a novel random walks seed auto-generation (SAGE) hybrid model that is robust to interobserver error and intensive user intervention.

Methods: Knee image is first oversegmented to produce homogeneous superpixels. Read More

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http://dx.doi.org/10.1007/s11548-019-01936-yDOI Listing
May 2019
4 Reads

HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules.

Int J Comput Assist Radiol Surg 2019 Mar 11. Epub 2019 Mar 11.

Tokyo University of Agriculture and Technology, Tokyo, Japan.

Purpose: A novel image feature set named histogram of triangular paths in graph (HoTPiG) is presented. The purpose of this study is to evaluate the feasibility of the proposed HoTPiG feature set through two clinical computer-aided detection tasks: nodule detection in lung CT images and aneurysm detection in head MR angiography images.

Methods: The HoTPiG feature set is calculated from an undirected graph structure derived from a binarized volume. Read More

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http://dx.doi.org/10.1007/s11548-019-01942-0DOI Listing
March 2019
1.659 Impact Factor

Random forest classifiers aid in the detection of incidental osteoblastic osseous metastases in DEXA studies.

Int J Comput Assist Radiol Surg 2019 May 9;14(5):903-909. Epub 2019 Mar 9.

Department of Radiology, University of Pennsylvania, 3737 Market Street, Philadelphia, PA, 19104, USA.

Purpose: Dual-energy X-ray absorptiometry (DEXA) studies are used for screening patients for low bone mineral density (BMD). Patients with breast and prostate cancer are often treated with hormone-altering drugs that result in low BMD. These patients may have incidental osteoblastic metastases of the spine that may be detected on screening DEXA studies. Read More

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http://link.springer.com/10.1007/s11548-019-01933-1
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http://dx.doi.org/10.1007/s11548-019-01933-1DOI Listing
May 2019
6 Reads

Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach.

Int J Comput Assist Radiol Surg 2019 May 7;14(5):745-754. Epub 2019 Mar 7.

Department of Biomedical Computer Science and Mechatronics, University for Health Sciences, Medical Informatics and Technology, 6060, Hall, Tyrol, Austria.

Purpose: In radiation therapy, a key step for a successful cancer treatment is image-based treatment planning. One objective of the planning phase is the fast and accurate segmentation of organs at risk and target structures from medical images. However, manual delineation of organs, which is still the gold standard in many clinical environments, is time-consuming and prone to inter-observer variations. Read More

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http://dx.doi.org/10.1007/s11548-019-01922-4DOI Listing
May 2019
1 Read

Missed paranasal sinus compartments in sinus surgery with and without image-guidance systems: a pilot feasibility study.

Int J Comput Assist Radiol Surg 2019 May 6;14(5):895-902. Epub 2019 Mar 6.

Department of Otorhinolaryngology, Medical University of Innsbruck, Anichstr. 35, 6020, Innsbruck, Austria.

Purpose: Image-guidance systems (IGS) have gained widespread use in endoscopic sinus surgery (ESS) and have been thoroughly analysed. In this study, we looked for a new parameter to determine if patients could directly benefit from the use of IGS during primary ESS. We questioned if IGS could improve the quality of ESS in chronic rhinosinusitis (CRS) patients via allowing a more comprehensive treatment of all involved sinus compartments. Read More

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http://dx.doi.org/10.1007/s11548-019-01930-4DOI Listing

A deep learning framework for efficient analysis of breast volume and fibroglandular tissue using MR data with strong artifacts.

Int J Comput Assist Radiol Surg 2019 Mar 6. Epub 2019 Mar 6.

Department of Computational Neuroscience, Georg-August-University, Friedrich-Hund Platz, 1, 37077, Göttingen, Germany.

Purpose: The main purpose of this work is to develop, apply, and evaluate an efficient approach for breast density estimation in magnetic resonance imaging data, which contain strong artifacts including intensity inhomogeneities.

Methods: We present a pipeline for breast density estimation, which consists of intensity inhomogeneity correction, breast volume segmentation, nipple extraction, and fibroglandular tissue segmentation. For the segmentation steps, a well-known deep learning architecture is employed. Read More

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http://dx.doi.org/10.1007/s11548-019-01928-yDOI Listing

Toward versatile cooperative surgical robotics: a review and future challenges.

Int J Comput Assist Radiol Surg 2019 Mar 4. Epub 2019 Mar 4.

Helmholtz Institute for Biomedical Engineering, Pauwelsstraße 20, 52074, Aachen, Germany.

Purpose: Surgical robotics has developed throughout the past 30 years resulting in more than 5000 different approaches proposed for various surgical disciplines supporting different surgical task sequences and differing ways of human-machine cooperation or degrees of automation. However, this diversity of systems influences cost as well as usability and might hinder their widespread adoption. In combination with the current trend toward open and modular "plug and play" dynamic networks of medical devices and IT systems in the operating room, a modular human-robot system design with versatile access to cooperative functions with varying degrees of automation on demand is desirable. Read More

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http://dx.doi.org/10.1007/s11548-019-01927-zDOI Listing
March 2019
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A practical marker-less image registration method for augmented reality oral and maxillofacial surgery.

Int J Comput Assist Radiol Surg 2019 May 1;14(5):763-773. Epub 2019 Mar 1.

Stomatological Hospital, Southern Medical University, Guangzhou, China.

Background: Image registration lies in the core of augmented reality (AR), which aligns the virtual scene with the reality. In AR surgical navigation, the performance of image registration is vital to the surgical outcome.

Methods: This paper presents a practical marker-less image registration method for AR-guided oral and maxillofacial surgery where a virtual scene is generated and mixed with reality to guide surgical operation or provide surgical outcome visualization in the manner of video see-through overlay. Read More

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http://link.springer.com/10.1007/s11548-019-01921-5
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http://dx.doi.org/10.1007/s11548-019-01921-5DOI Listing
May 2019
5 Reads

Temporal enhancement of 2D color Doppler echocardiography sequences by fragment-based frame reordering and refinement.

Int J Comput Assist Radiol Surg 2019 Apr 23;14(4):577-586. Epub 2019 Feb 23.

Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.

Purpose: The goal of this study was to develop an algorithm that enhances the temporal resolution of two-dimensional color Doppler echocardiography (2D CDE) by reordering all the acquired frames and filtering out the frames corrupted by out-of-plane motion and arrhythmia.

Methods: The algorithm splits original frame sequence into the fragments based on the correlation with a reference frame. Then, the fragments are aligned temporally and merged into a resulting sequence that has higher temporal resolution. Read More

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http://dx.doi.org/10.1007/s11548-019-01926-0DOI Listing
April 2019
3 Reads

EyeSAM: graph-based localization and mapping of retinal vasculature during intraocular microsurgery.

Int J Comput Assist Radiol Surg 2019 May 21;14(5):819-828. Epub 2019 Feb 21.

The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.

Purpose: Robot-assisted intraocular microsurgery can improve performance by aiding the surgeon in operating on delicate micron-scale anatomical structures of the eye. In order to account for the eyeball motion that is typical in intraocular surgery, there is a need for fast and accurate algorithms that map the retinal vasculature and localize the retina with respect to the microscope.

Methods: This work extends our previous work by a graph-based SLAM formulation using a sparse incremental smoothing and mapping (iSAM) algorithm. Read More

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http://dx.doi.org/10.1007/s11548-019-01925-1DOI Listing

The Adaptive Hermite Fractal Tree (AHFT): a novel surgical 3D path planning approach with curvature and heading constraints.

Int J Comput Assist Radiol Surg 2019 Apr 21;14(4):659-670. Epub 2019 Feb 21.

Mechatronics in Medicine Laboratory, Department of Mechanical Engineering, Imperial College, London, UK.

Purpose: In the context of minimally invasive neurosurgery, steerable needles such as the one developed within the Horizon2020-funded EDEN2020 project (Frasson et al. in Proc Inst Mech Eng Part H J Eng Med 224(6):775-88, 2010. https://doi. Read More

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http://dx.doi.org/10.1007/s11548-019-01923-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420904PMC

Subject-specific modelling of pneumoperitoneum: model implementation, validation and human feasibility assessment.

Int J Comput Assist Radiol Surg 2019 May 20;14(5):841-850. Epub 2019 Feb 20.

Department of Surgery and Cancer, Imperial College London, London, UK.

Purpose: The aim of this study is to propose a model that simulates patient-specific anatomical changes resulting from pneumoperitoneum, using preoperative data as input. The framework can assist the surgeon through a real-time visualisation and interaction with the model. Such could further facilitate surgical planning preoperatively, by defining a surgical strategy, and intraoperatively to estimate port positions. Read More

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http://dx.doi.org/10.1007/s11548-019-01924-2DOI Listing
May 2019
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Automatic and near real-time stylistic behavior assessment in robotic surgery.

Int J Comput Assist Radiol Surg 2019 Apr 18;14(4):635-643. Epub 2019 Feb 18.

Department of Surgery, UT Southwestern Medical Center, Dallas, TX, 75390, USA.

Purpose: Automatic skill evaluation is of great importance in surgical robotic training. Extensive research has been done to evaluate surgical skill, and a variety of quantitative metrics have been proposed. However, these methods primarily use expert selected features which may not capture latent information in movement data. Read More

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http://dx.doi.org/10.1007/s11548-019-01920-6DOI Listing
April 2019
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An analytical approach for the simulation of realistic low-dose fluoroscopic images.

Int J Comput Assist Radiol Surg 2019 Apr 18;14(4):601-610. Epub 2019 Feb 18.

Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.

Purpose: The quality of X-ray images plays an important role in computer-assisted interventions. Although learning-based denoising techniques have been shown to be successful in improving the image quality, they often rely on pairs of associated low- and high-dose X-ray images that are usually not possible to acquire at different dose levels in a clinical scenario. Moreover, since data variation is an important requirement for learning-based methods, the use of phantom data alone may not be sufficient. Read More

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http://dx.doi.org/10.1007/s11548-019-01912-6DOI Listing

Joint reconstruction and classification of tumor cells and cell interactions in melanoma tissue sections with synthesized training data.

Int J Comput Assist Radiol Surg 2019 Apr 16;14(4):587-599. Epub 2019 Feb 16.

Institute for Numerical Simulation, University of Bonn, Bonn, Germany.

Purpose: Cancers are almost always diagnosed by morphologic features in tissue sections. In this context, machine learning tools provide new opportunities to describe tumor immune cell interactions within the tumor microenvironment and thus provide phenotypic information that might be predictive for the response to immunotherapy.

Methods: We develop a machine learning approach using variational networks for joint image denoising and classification of tissue sections for melanoma, which is an established model tumor for immuno-oncology research. Read More

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http://dx.doi.org/10.1007/s11548-019-01919-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420907PMC
April 2019
1 Read