1,356 results match your criteria International Journal of Computer Assisted Radiology and Surgery [Journal]


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

Int J Comput Assist Radiol Surg 2019 Feb 21. 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
February 2019

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 Feb 21. 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
February 2019

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

Int J Comput Assist Radiol Surg 2019 Feb 20. 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
February 2019

Automatic and near real-time stylistic behavior assessment in robotic surgery.

Int J Comput Assist Radiol Surg 2019 Feb 18. 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
February 2019

An analytical approach for the simulation of realistic low-dose fluoroscopic images.

Int J Comput Assist Radiol Surg 2019 Feb 18. 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
February 2019

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 Feb 16. 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
February 2019

A novel robotic system for vascular intervention: principles, performances, and applications.

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

Peking Union Medical College Hospital, Beijing, China.

Purpose: This paper describes the design, principles, performances, and applications of a novel image-guided master-slave robotic system for vascular intervention (VI), including the performance evaluation and in vivo trials.

Methods: Based on the peer-to-peer (P2P) remote communication system, the kinetics analysis, the sliding-mode neural network self-adaptive control model and the feedback system, this new robotic system can accomplish in real time a number of VI operations, including guidewire translation and rotation, balloon catheter translation, and contrast agent injection. The master-slave design prevents surgeons from being exposed to X-ray radiation, which means that they are not required to wear a heavy lead suit. Read More

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http://dx.doi.org/10.1007/s11548-018-01906-wDOI Listing
February 2019

A review on lung boundary detection in chest X-rays.

Int J Comput Assist Radiol Surg 2019 Feb 7. Epub 2019 Feb 7.

Lister Hill National Center for Biomedical Communications, Communications Engineering Branch, National Library of Medicine, National Institutes of Health, Bethesda, USA.

Purpose: Chest radiography is the most common imaging modality for pulmonary diseases. Due to its wide usage, there is a rich literature addressing automated detection of cardiopulmonary diseases in digital chest X-rays (CXRs). One of the essential steps for automated analysis of CXRs is localizing the relevant region of interest, i. Read More

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http://dx.doi.org/10.1007/s11548-019-01917-1DOI Listing
February 2019

Wearable technology-based metrics for predicting operator performance during cardiac catheterisation.

Int J Comput Assist Radiol Surg 2019 Feb 7. Epub 2019 Feb 7.

Application of Science to Simulation Based Education and Research on Training (ASSERT) Centre, University College Cork, Cork, Ireland.

Introduction: Unobtrusive metrics that can auto-assess performance during clinical procedures are of value. Three approaches to deriving wearable technology-based metrics are explored: (1) eye tracking, (2) psychophysiological measurements [e.g. Read More

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http://link.springer.com/10.1007/s11548-019-01918-0
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http://dx.doi.org/10.1007/s11548-019-01918-0DOI Listing
February 2019
2 Reads

Robotic laser osteotomy through penscriptive structured light visual servoing.

Int J Comput Assist Radiol Surg 2019 Feb 7. Epub 2019 Feb 7.

Biophotonics & Bioengineering Laboratory, Department of Electrical & Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, ON, Canada.

Purpose: Planning osteotomies is a task that surgeons do as part of standard surgical workflow. This task, however, becomes more difficult and less intuitive when a robot is tasked with performing the osteotomy. In this study, we aim to provide a new method for surgeons to allow for highly intuitive trajectory planning, similar to the way an attending surgeon would instruct a junior. Read More

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http://link.springer.com/10.1007/s11548-018-01905-x
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http://dx.doi.org/10.1007/s11548-018-01905-xDOI Listing
February 2019
2 Reads

Improving target localization during trans-oral surgery with use of intraoperative imaging.

Int J Comput Assist Radiol Surg 2019 Feb 7. Epub 2019 Feb 7.

Geisel School of Medicine at Dartmouth, Hanover, NH, USA.

Purpose: Trans-oral surgery provides a less invasive means for the surgical management of upper aerodigestive tract malignancies but is limited in its ability to readily assess submucosal tumor extent and location of critical structures intraoperatively. We sought to determine surgeons' baseline target localization accuracy during operative laryngoscopy with preoperative imaging alone and then assess for improvement in localization accuracy when presented with intraoperative CT imaging capturing soft tissue deformation.

Methods: Fiducial beads were placed submucosally in four cadaver heads. Read More

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http://dx.doi.org/10.1007/s11548-018-01907-9DOI Listing
February 2019

Gain determination of feedback force for an ultrasound scanning robot using genetic algorithm.

Int J Comput Assist Radiol Surg 2019 Feb 1. Epub 2019 Feb 1.

Department of Biomedical Engineering, Gil Medical Center, School of Medicine, Gachon University, 38 3-dockjeom ro, Namdong-gu, Incheon, 21565, Korea.

Purpose: The remote medical diagnosis system (RMDS) is for providing medical diagnosis to the patients located in remote sites. To apply to RMDS and medical automation, many master-slave type ultrasound scanning robots are being developed and researched. One of the important research issue of the master-slave type ultrasound scanning robot is to determine the gains of the feedback force. Read More

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http://dx.doi.org/10.1007/s11548-019-01915-3DOI Listing
February 2019

Eddy-current-induced distortion correction using maximum reconciled mutual information in diffusion MR imaging.

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

School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.

Purpose: In diffusion tensor imaging, a large number of diffusion-weighted (DW) images with different diffusion gradient directions are attained during scanning. However, subjects' involuntary head movements and eddy current effect related to large diffusion-sensitizing gradients will cause distortions of DW images. Therefore, for tracking accurately white matter structures and tractography, the distortions have to be realigned before model fitting. Read More

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http://dx.doi.org/10.1007/s11548-018-01901-1DOI Listing
January 2019
1.659 Impact Factor

Interactive virtual 3D models of renal cancer patient anatomies alter partial nephrectomy surgical planning decisions and increase surgeon confidence compared to volume-rendered images.

Int J Comput Assist Radiol Surg 2019 Jan 24. Epub 2019 Jan 24.

Specialist Centre for Kidney Cancer, Department of Urology, The Royal Free London NHS Foundation Trust, London, UK.

Purpose: To determine whether the interactive visualisation of patient-specific virtual 3D models of the renal anatomy influences the pre-operative decision-making process of urological surgeons for complex renal cancer operations.

Methods: Five historic renal cancer patient pre-operative computed tomography (CT) datasets were retrospectively selected based on RENAL nephrectomy score and variety of anatomy. Interactive virtual 3D models were generated for each dataset using image segmentation software and were made available for online visualisation and manipulation. Read More

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http://dx.doi.org/10.1007/s11548-019-01913-5DOI Listing
January 2019
1 Read

A computer-assisted system for handheld whole-breast ultrasonography.

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

Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, 128 08, Prague 2, Czech Republic.

Purpose: Breast ultrasonography (US) presents an alternative to mammography in young asymptomatic individuals and a complementary examination in screening of women with dense breasts. Handheld US is the standard-of-care, yet when used in whole-breast examination, no effort has been devoted to monitoring breast coverage and missed regions, which is the purpose of this study.

Methods: We introduce a computer-aided system assisting radiologists and US technologists in covering the whole breast with minimum alteration to the standard workflow. Read More

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http://dx.doi.org/10.1007/s11548-018-01909-7DOI Listing
January 2019

Early esophageal adenocarcinoma detection using deep learning methods.

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

University of Lincoln, Lincoln, UK.

Purpose: This study aims to adapt and evaluate the performance of different state-of-the-art deep learning object detection methods to automatically identify esophageal adenocarcinoma (EAC) regions from high-definition white light endoscopy (HD-WLE) images.

Method: Several state-of-the-art object detection methods using Convolutional Neural Networks (CNNs) were adapted to automatically detect abnormal regions in the esophagus HD-WLE images, utilizing VGG'16 as the backbone architecture for feature extraction. Those methods are Regional-based Convolutional Neural Network (R-CNN), Fast R-CNN, Faster R-CNN and Single-Shot Multibox Detector (SSD). Read More

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http://dx.doi.org/10.1007/s11548-019-01914-4DOI Listing
January 2019
3 Reads

A direct volume rendering visualization approach for serial PET-CT scans that preserves anatomical consistency.

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

Sydney Medical School, The University of Sydney, Sydney, Australia.

Purpose: Our aim was to develop an interactive 3D direct volume rendering (DVR) visualization solution to interpret and analyze complex, serial multi-modality imaging datasets from positron emission tomography-computed tomography (PET-CT).

Methods: Our approach uses: (i) a serial transfer function (TF) optimization to automatically depict particular regions of interest (ROIs) over serial datasets with consistent anatomical structures; (ii) integration of a serial segmentation algorithm to interactively identify and track ROIs on PET; and (iii) parallel graphics processing unit (GPU) implementation for interactive visualization.

Results: Our DVR visualization more easily identifies changes in ROIs in serial scans in an automated fashion and parallel GPU computation which enables interactive visualization. Read More

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http://dx.doi.org/10.1007/s11548-019-01916-2DOI Listing
January 2019
1 Read

A dataset of laryngeal endoscopic images with comparative study on convolution neural network-based semantic segmentation.

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

Leibniz Universität Hannover, Appelstraße 11A, 30167, Hannover, Germany.

Purpose: Automated segmentation of anatomical structures in medical image analysis is a prerequisite for autonomous diagnosis as well as various computer- and robot-aided interventions. Recent methods based on deep convolutional neural networks (CNN) have outperformed former heuristic methods. However, those methods were primarily evaluated on rigid, real-world environments. Read More

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http://link.springer.com/10.1007/s11548-018-01910-0
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http://dx.doi.org/10.1007/s11548-018-01910-0DOI Listing
January 2019
3 Reads

A novel multiple communication paths for surgical telepresence videos delivery of the maxilla area in oral and maxillofacial surgery.

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

Faculty of Medicine and Health Service, Macquarie University, Sydney, Australia.

Purpose: A surgical telepresence between two surgical sites where a local surgeon in the surgery site, who is less experienced, needs help from the expert surgeon located at a remote site. Furthermore, the primary aim of this paper is to improve the quality of surgical video sent and received to-and-from both surgical sites, which has been a major quality issue so far.

Method: This work considers flow rate allocation and resource availability to determine the network path quality. Read More

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http://dx.doi.org/10.1007/s11548-018-01904-yDOI Listing
January 2019
1 Read

Guest editorial of the IJCARS-BVM 2018 special issue.

Int J Comput Assist Radiol Surg 2019 Jan;14(1):1-2

Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Hindenburgdamm 30, 12200, Berlin, Germany.

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http://link.springer.com/10.1007/s11548-018-01902-0
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http://dx.doi.org/10.1007/s11548-018-01902-0DOI Listing
January 2019
1 Read

Breast tumor classification using different features of quantitative ultrasound parametric images.

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

Department of Biomedical Engineering, Hungkuang University, 1018, Section 6, Taiwan Boulevard Road, Taichung, 43302, Taiwan, ROC.

Rationale And Objectives: The ultrasound B-mode-based morphological and texture analysis and Nakagami parametric imaging have been proposed to characterize breast tumors. Since these three feature categories of ultrasonic tissue characterization supply information on different physical characteristics of breast tumors, by combining the above methods is expected to provide more clues for classifying breast tumors.

Materials And Methods: To verify the validity of the concept, raw data were obtained from 160 clinical cases. Read More

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http://dx.doi.org/10.1007/s11548-018-01908-8DOI Listing
January 2019

FCNN-based axon segmentation for convection-enhanced delivery optimization.

Int J Comput Assist Radiol Surg 2019 Jan 7. Epub 2019 Jan 7.

Department of Advanced Robotics (ADVR), Istituto Italiano di Tecnologia, Via Morego 30, 16136, Genoa, GE, Italy.

Purpose: Glioblastoma multiforme treatment is a challenging task in clinical oncology. Convection- enhanced delivery (CED) is showing encouraging but still suboptimal results due to drug leakages. Numerical models can predict drug distribution within the brain, but require retrieving brain physical properties, such as the axon diameter distribution (ADD), through axon architecture analysis. Read More

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http://dx.doi.org/10.1007/s11548-018-01911-zDOI Listing
January 2019

Segmentation of the proximal femur in radial MR scans using a random forest classifier and deformable model registration.

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

School of Health Sciences - Geneva, HES-SO University of Applied Sciences and Arts Western Switzerland, Avenue de Champel 47, 1206, Geneva, Switzerland.

Background: Radial 2D MRI scans of the hip are routinely used for the diagnosis of the cam type of femoroacetabular impingement (FAI) and of avascular necrosis (AVN) of the femoral head, both considered causes of hip joint osteoarthritis in young and active patients. A method for automated and accurate segmentation of the proximal femur from radial MRI scans could be very useful in both clinical routine and biomechanical studies. However, to our knowledge, no such method has been published before. Read More

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http://link.springer.com/10.1007/s11548-018-1899-z
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http://dx.doi.org/10.1007/s11548-018-1899-zDOI Listing
January 2019
11 Reads

Predicting underestimation of ductal carcinoma in situ: a comparison between radiomics and conventional approaches.

Int J Comput Assist Radiol Surg 2018 Dec 19. Epub 2018 Dec 19.

Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou, People's Republic of China.

Purpose: We aimed to investigate the feasibility of predicting invasion carcinoma from ductal carcinoma in situ (DCIS) lesions diagnosed by preoperative core needle biopsy using radiomics signatures, clinical imaging characteristics, and breast imaging reporting and data system (BI-RADS) descriptors on mammography.

Methods: Retrospectively, we enrolled 362 DCIS patients diagnosed by core needle biopsy, 110 (30.4%) of which had invasive carcinoma confirmed by operation and pathology. Read More

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http://link.springer.com/10.1007/s11548-018-1900-x
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http://dx.doi.org/10.1007/s11548-018-1900-xDOI Listing
December 2018
1 Read
1.659 Impact Factor

Patient 3D body pose estimation from pressure imaging.

Int J Comput Assist Radiol Surg 2018 Dec 14. Epub 2018 Dec 14.

Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr 3, 85748, Garching, Germany.

Purpose: In-bed motion monitoring has become of great interest for a variety of clinical applications. Image-based approaches could be seen as a natural non-intrusive approach for this purpose; however, video devices require special challenging settings for a clinical environment. We propose to estimate the patient's posture from pressure sensors' data mapped to images. Read More

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http://link.springer.com/10.1007/s11548-018-1895-3
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http://dx.doi.org/10.1007/s11548-018-1895-3DOI Listing
December 2018
5 Reads

Unsupervised pathology detection in medical images using conditional variational autoencoders.

Int J Comput Assist Radiol Surg 2018 Dec 12. Epub 2018 Dec 12.

Institute of Medical Informatics, University of Lübeck, Lübeck, Germany.

Purpose: Pathology detection in medical image data is an important but a rather complicated task. In particular, the big variability of the pathologies is a challenge to automatic detection methods and even to machine learning methods. Supervised algorithms would usually learn the appearance of a single pathological structure based on a large annotated dataset. Read More

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http://dx.doi.org/10.1007/s11548-018-1898-0DOI Listing
December 2018

Surgineering: a new type of collaboration among surgeons and engineers.

Int J Comput Assist Radiol Surg 2019 Feb 11;14(2):187-190. Epub 2018 Dec 11.

Chair of Micro Technology and Medical Device Technology, TUM Department of Mechanical Engineering, Technische Universität München, Boltzmannstraße 3, 85748, Garching bei München, Germany.

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http://dx.doi.org/10.1007/s11548-018-1893-5DOI Listing
February 2019
1 Read

Implementation of a semiautomatic method to design patient-specific instruments for corrective osteotomy of the radius.

Int J Comput Assist Radiol Surg 2018 Dec 10. Epub 2018 Dec 10.

Amsterdam UMC, Department of Biomedical Engineering and Physics, University of Amsterdam, Amsterdam Movement Sciences, 1105 AZ, Amsterdam, The Netherlands.

Purpose: 3D-printed patient-specific instruments (PSIs), such as surgical guides and implants, show great promise for accurate navigation in surgical correction of post-traumatic deformities of the distal radius. However, existing costs of computer-aided design and manufacturing process prevent everyday surgical use. In this paper, we propose an innovative semiautomatic methodology to streamline the PSIs design. Read More

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http://dx.doi.org/10.1007/s11548-018-1896-2DOI Listing
December 2018
1 Read

ARENA: Inter-modality affine registration using evolutionary strategy.

Int J Comput Assist Radiol Surg 2018 Dec 10. Epub 2018 Dec 10.

PERFORM Centre, Concordia University, Montreal, Canada.

Purpose: Image fusion of different imaging modalities renders valuable information to clinicians. In this paper, we proposed an automatic multimodal registration method to register intra-operative ultrasound images (US) to preoperative magnetic resonance images (MRI) in the context of image-guided neurosurgery.

Methods: We employed refined correlation ratio as a similarity metric for our intensity-based image registration method. Read More

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http://dx.doi.org/10.1007/s11548-018-1897-1DOI Listing
December 2018

Reconstruction and positional accuracy of 3D ultrasound on vertebral phantoms for adolescent idiopathic scoliosis spinal surgery.

Int J Comput Assist Radiol Surg 2018 Dec 5. Epub 2018 Dec 5.

Department of Biomedical Engineering, University of Alberta, 1098 Research Transition Facility, 8308-114 Street, Edmonton, AB, T6G 2V2, Canada.

Purpose: Determine the positional, rotational and reconstruction accuracy of a 3D ultrasound system to be used for image registration in navigation surgery.

Methods: A custom 3D ultrasound for spinal surgery image registration was developed using Optitrack Prime 13-W motion capture cameras and a SonixTablet Ultrasound System. Temporal and spatial calibration was completed to account for time latencies between the two systems and to ensure accurate motion tracking of the ultrasound transducer. Read More

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http://link.springer.com/10.1007/s11548-018-1894-4
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http://dx.doi.org/10.1007/s11548-018-1894-4DOI Listing
December 2018
8 Reads

Automatic detection of perforator vessels using infrared thermography in reconstructive surgery.

Int J Comput Assist Radiol Surg 2018 Dec 5. Epub 2018 Dec 5.

Innovation Center Computer Assisted Surgery, University Leipzig, Semmelweisstr. 14, 04103, Leipzig, Germany.

Purpose: Knowing the location of the blood vessels supplying the skin and subcutaneous tissue is a requirement during the planning of tissue transfer in reconstructive surgery. Commonly used imaging techniques such as computed tomography angiography and indocyanine green angiography expose the patient to radiation or a contrast agent, respectively. Infrared thermal imaging was evaluated with success as a non-invasive alternative. Read More

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http://link.springer.com/10.1007/s11548-018-1892-6
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http://dx.doi.org/10.1007/s11548-018-1892-6DOI Listing
December 2018
8 Reads

A model-guided method for improving coronary artery tree extractions from CCTA images.

Int J Comput Assist Radiol Surg 2019 Feb 28;14(2):373-383. Epub 2018 Nov 28.

Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Purpose: Automatically extracted coronary artery trees (CATs) from coronary computed tomography angiography images could contain incorrect extractions which require manual corrections before they can be used in clinical practice. A model-guided method for improving the extracted CAT is described to automatically detect potential incorrect extractions and improve them.

Methods: The proposed method is a coarse-to-fine approach. Read More

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http://dx.doi.org/10.1007/s11548-018-1891-7DOI Listing
February 2019
6 Reads

Automated anatomical labeling of coronary arteries via bidirectional tree LSTMs.

Int J Comput Assist Radiol Surg 2019 Feb 27;14(2):271-280. Epub 2018 Nov 27.

CuraCloud Corporation, 999 3rd Ave, Ste 700, Seattle, WA, 98004, USA.

Purpose: Automated anatomical labeling facilitates the diagnostic process for physicians and radiologists. One of the challenges in automated anatomical labeling problems is the robustness to handle the large individual variability inherited in human anatomy. A novel deep neural network framework, referred to Tree Labeling Network (TreeLab-Net), is proposed to resolve this problem in this work. Read More

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http://dx.doi.org/10.1007/s11548-018-1884-6DOI Listing
February 2019
10 Reads

Deep-learned placental vessel segmentation for intraoperative video enhancement in fetoscopic surgery.

Int J Comput Assist Radiol Surg 2019 Feb 27;14(2):227-235. Epub 2018 Nov 27.

Yale University School of Medicine, New Haven, USA.

Introduction: Twin-to-twin transfusion syndrome (TTTS) is a potentially lethal condition that affects pregnancies in which twins share a single placenta. The definitive treatment for TTTS is fetoscopic laser photocoagulation, a procedure in which placental blood vessels are selectively cauterized. Challenges in this procedure include difficulty in quickly identifying placental blood vessels due to the many artifacts in the endoscopic video that the surgeon uses for navigation. Read More

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http://link.springer.com/10.1007/s11548-018-1886-4
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http://dx.doi.org/10.1007/s11548-018-1886-4DOI Listing
February 2019
3 Reads

Computer-assisted planning for a concentric tube robotic system in neurosurgery.

Int J Comput Assist Radiol Surg 2019 Feb 27;14(2):335-344. Epub 2018 Nov 27.

Laboratory for Continuum Robotics, Leibniz Universität Hannover, Hanover, Germany.

Purpose: Laser-induced thermotherapy in the brain is a minimally invasive procedure to denature tumor tissue. However, irregularly shaped brain tumors cannot be treated using existing commercial systems. Thus, we present a new concept for laser-induced thermotherapy using a concentric tube robotic system. Read More

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http://dx.doi.org/10.1007/s11548-018-1890-8DOI Listing
February 2019

A robotic microsurgical forceps for transoral laser microsurgery.

Int J Comput Assist Radiol Surg 2019 Feb 21;14(2):321-333. Epub 2018 Nov 21.

Department of Advanced Robotics, Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genoa, Italy.

Purpose: In transoral laser microsurgery (TLM), the close curved cylindrical structure of the laryngeal region offers functional challenges to surgeons who operate on its malignancies with rigid, single degree-of-freedom (DOF) forceps. These challenges include surgeon hand tremors, poor reachability, poor tissue surface perception, and reduced ergonomy in design. The integrated robotic microsurgical forceps presented here is capable of addressing the above challenges through tele-operated tissue manipulation in TLM. Read More

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http://link.springer.com/10.1007/s11548-018-1887-3
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http://dx.doi.org/10.1007/s11548-018-1887-3DOI Listing
February 2019
9 Reads

A computer vision technique for automated assessment of surgical performance using surgeons' console-feed videos.

Int J Comput Assist Radiol Surg 2018 Nov 20. Epub 2018 Nov 20.

A.T.L.A.S (Applied Technology Laboratory for Advanced Surgery) Program, Department of Urology, Roswell Park Comprehensive Cancer Center, Elm & Carlton St, Buffalo, NY, 14263, USA.

Purpose: To develop and validate an automated assessment of surgical performance (AASP) system for objective and computerized assessment of pelvic lymph node dissection (PLND) as an integral part of robot-assisted radical cystectomy (RARC) using console-feed videos recorded during live surgery.

Methods: Video recordings of 20 PLNDs were included. The quality of lymph node clearance was assessed based on the features derived from the computer vision process which include: the number and cleared area of the vessels/nerve (N-Vs); image median color map; and mean entropy (measures the level of disorganization) in the video frame. Read More

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http://dx.doi.org/10.1007/s11548-018-1881-9DOI Listing
November 2018
6 Reads

Robotically assisted long bone biopsy under MRI: cadaver study results.

Int J Comput Assist Radiol Surg 2019 Jan 19;14(1):147-156. Epub 2018 Nov 19.

Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, 111 Michigan Avenue, Washington, DC, USA.

Rationale And Objectives: We have designed and constructed an MR-safe robot made entirely of nonmetallic components with pneumatic actuators and optical encoders. The robot was developed to enable bone biopsies to be performed under magnetic resonance imaging (MRI) guidance in pediatric patients. The purpose of this study was to show the feasibility of using the robot for biopsy of the femur and tibia in a cadaver leg. Read More

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http://link.springer.com/10.1007/s11548-018-1889-1
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http://dx.doi.org/10.1007/s11548-018-1889-1DOI Listing
January 2019
8 Reads

"Deep-Onto" network for surgical workflow and context recognition.

Int J Comput Assist Radiol Surg 2018 Nov 16. Epub 2018 Nov 16.

Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milan, Italy.

Purpose: Surgical workflow recognition and context-aware systems could allow better decision making and surgical planning by providing the focused information, which may eventually enhance surgical outcomes. While current developments in computer-assisted surgical systems are mostly focused on recognizing surgical phases, they lack recognition of surgical workflow sequence and other contextual element, e.g. Read More

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http://dx.doi.org/10.1007/s11548-018-1882-8DOI Listing
November 2018
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Combining MRF-based deformable registration and deep binary 3D-CNN descriptors for large lung motion estimation in COPD patients.

Int J Comput Assist Radiol Surg 2019 Jan 14;14(1):43-52. Epub 2018 Nov 14.

Institute of Medical Informatics, University of Lübeck, Ratzeburger Allee 160, 23562, Lübeck, Germany.

Purpose: Deep convolutional neural networks in their various forms are currently achieving or outperforming state-of-the-art results on several medical imaging tasks. We aim to make these developments available to the so far unsolved task of accurate correspondence finding-especially with regard to image registration.

Methods: We propose a two-step hybrid approach to make deep learned features accessible to a discrete optimization-based registration method. Read More

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http://link.springer.com/10.1007/s11548-018-1888-2
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http://dx.doi.org/10.1007/s11548-018-1888-2DOI Listing
January 2019
17 Reads

Automatic bone segmentation in whole-body CT images.

Int J Comput Assist Radiol Surg 2019 Jan 13;14(1):21-29. Epub 2018 Nov 13.

Division of Medical Image Computing, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 581, Heidelberg, Germany.

Purpose: Many diagnostic or treatment planning applications critically depend on the successful localization of bony structures in CT images. Manual or semiautomatic bone segmentation is tedious, however, and often not practical in clinical routine. In this paper, we present a reliable and fully automatic bone segmentation in whole-body CT scans of patients suffering from multiple myeloma. Read More

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http://link.springer.com/10.1007/s11548-018-1883-7
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http://dx.doi.org/10.1007/s11548-018-1883-7DOI Listing
January 2019
22 Reads

Robotic surgical rehearsal on patient-specific 3D-printed skull models for stereoelectroencephalography (SEEG).

Int J Comput Assist Radiol Surg 2019 Jan 13;14(1):139-145. Epub 2018 Nov 13.

Department of Neurosurgery, Ichan School of Medicine at Mount Sinai, New York, NY, USA.

Purpose: Medically refractory epilepsy patients commonly require surgical alternatives for diagnosis and treatment. Stereoelectroencephalography (SEEG) is a useful diagnostic procedure in seizure focus elucidation. Modern techniques involve the use of robotics and neuronavigation for SEEG. Read More

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http://dx.doi.org/10.1007/s11548-018-1885-5DOI Listing
January 2019

Dual-modality multi-atlas segmentation of torso organs from [F]FDG-PET/CT images.

Int J Comput Assist Radiol Surg 2018 Nov 2. Epub 2018 Nov 2.

Department of Biomedical Engineering, Dalian University of Technology, Dalian, Liaoning, China.

Purpose: Automated segmentation of torso organs from positron emission tomography/computed tomography (PET/CT) images is a prerequisite step for nuclear medicine image analysis. However, accurate organ segmentation from clinical PET/CT is challenging due to the poor soft tissue contrast in the low-dose CT image and the low spatial resolution of the PET image. To overcome these challenges, we developed a multi-atlas segmentation (MAS) framework for torso organ segmentation from 2-deoxy-2-[F]fluoro-D-glucose PET/CT images. Read More

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http://link.springer.com/10.1007/s11548-018-1879-3
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http://dx.doi.org/10.1007/s11548-018-1879-3DOI Listing
November 2018
15 Reads

Learning deep similarity metric for 3D MR-TRUS image registration.

Int J Comput Assist Radiol Surg 2018 Oct 31. Epub 2018 Oct 31.

Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, 12180, USA.

Purpose: The fusion of transrectal ultrasound (TRUS) and magnetic resonance (MR) images for guiding targeted prostate biopsy has significantly improved the biopsy yield of aggressive cancers. A key component of MR-TRUS fusion is image registration. However, it is very challenging to obtain a robust automatic MR-TRUS registration due to the large appearance difference between the two imaging modalities. Read More

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http://link.springer.com/10.1007/s11548-018-1875-7
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http://dx.doi.org/10.1007/s11548-018-1875-7DOI Listing
October 2018
10 Reads

Computer-assisted delineation of hematoma from CT volume using autoencoder and Chan Vese model.

Int J Comput Assist Radiol Surg 2019 Feb 30;14(2):259-269. Epub 2018 Oct 30.

Electrical Engineering, Indian Institute of Technology, Kharagpur, India.

Purpose: To reduce the inter- and intra- rater variability as well as time and effort, a method for computer-assisted delineation of hematoma is proposed. Delineation of hematoma is done for further automated analysis such as the volume of hematoma, anatomical location of hematoma, etc. for proper surgical planning. Read More

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http://link.springer.com/10.1007/s11548-018-1873-9
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http://dx.doi.org/10.1007/s11548-018-1873-9DOI Listing
February 2019
2 Reads

Robust navigation support in lowest dose image setting.

Int J Comput Assist Radiol Surg 2019 Feb 28;14(2):291-300. Epub 2018 Oct 28.

Computer Aided Medical Procedures, Technische Universität München, Boltzmannstr 3, 85748, Garching, Germany.

Purpose: Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.

Methods: In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on [Formula: see text]-sparse coding and online robust PCA (ORPCA). Read More

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http://dx.doi.org/10.1007/s11548-018-1874-8DOI Listing
February 2019
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Classification of contrast-enhanced spectral mammography (CESM) images.

Int J Comput Assist Radiol Surg 2019 Feb 26;14(2):249-257. Epub 2018 Oct 26.

Sheba Medical Center, Ramat Gan, Israel.

Purpose: Contrast-enhanced spectral mammography (CESM) is a recently developed breast imaging technique. CESM relies on dual-energy acquisition following contrast agent injection to improve mammography sensitivity. CESM is comparable to contrast-enhanced MRI in terms of sensitivity, at a fraction of the cost. Read More

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http://link.springer.com/10.1007/s11548-018-1876-6
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http://dx.doi.org/10.1007/s11548-018-1876-6DOI Listing
February 2019
19 Reads

Multimodal image registration for liver radioembolization planning and patient assessment.

Int J Comput Assist Radiol Surg 2019 Feb 22;14(2):215-225. Epub 2018 Oct 22.

Fraunhofer Institute for Medical Image Computing, MEVIS, Lübeck, Germany.

Purpose: Multimodal imaging plays a key role in patient assessment and treatment planning in liver radioembolization. It will reach its full potential for convenient use in combination with deformable image registration methods. A registration framework is proposed for multimodal liver image registration of multi-phase CT, contrast-enhanced late-phase T1, T2, and DWI MRI sequences. Read More

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http://link.springer.com/10.1007/s11548-018-1877-5
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http://dx.doi.org/10.1007/s11548-018-1877-5DOI Listing
February 2019
6 Reads

Simulation study on X-ray phase contrast imaging with dual-phase gratings.

Int J Comput Assist Radiol Surg 2019 Jan 22;14(1):3-10. Epub 2018 Oct 22.

Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nuremberg, Martensstr. 3, 91058, Erlangen, Germany.

Purpose: Two phase gratings in an X-ray grating interferometers can solve several technical challenges for clinical use of X-ray phase contrast. In this work, we adapt and evaluate this setup design to clinical X-ray sources and detectors in a simulation study.

Methods: For a given set of gratings, we optimize the remaining parameter space of a dual-phase grating setup using a numerical wave front simulation. Read More

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http://dx.doi.org/10.1007/s11548-018-1872-xDOI Listing
January 2019

Interactive patient-customized curvilinear reformatting for improving neurosurgical planning.

Int J Comput Assist Radiol Surg 2018 Oct 20. Epub 2018 Oct 20.

School of Medical Sciences, University of Campinas, Rua Tessália Vieira de Camargo - 126, Cidade Universitária Zeferino Vaz, Campinas, São Paulo, 13083-887, Brazil.

Purpose: Visualizing a brain in its native space plays an essential role during neurosurgical planning because it allows the superficial cerebral veins and surrounding regions to be preserved. This paper describes the use of a visualization tool in which single gadolinium contrast-enhanced T1-weighted magnetic resonance imaging was applied in nondefective and nonresective skulls to promote visualization of important structures.

Methods: A curvilinear reformatting tool was applied on the supratentorial compartment to peel the tissues to the depth of the dura mater and thereby revealing cortical and vascular spatial relationships. Read More

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http://dx.doi.org/10.1007/s11548-018-1878-4DOI Listing
October 2018