1. Articles from Alexander Schlaefer

    1-11 of 11
    1. Deep learning with 4D spatio-temporal data representations for OCT-based force estimation

      Deep learning with 4D spatio-temporal data representations for OCT-based force estimation

      Estimating the forces acting between instruments and tissue is a challenging problem for robot-assisted minimally-invasive surgery. Recently, numerous vision-based methods have been proposed to replace electro-mechanical approaches. Moreover, optical coherence tomography (OCT) and deep learning have been used for estimating forces based on deformation observed in volumetric image data. The method demonstrated the advantage of deep learning with 3D volumetric data over 2D depth images for force estimation. In this work, we extend the problem of deep learning-based force estimation to 4D spatio-temporal data with streams of 3D OCT volumes. For this purpose, we design and evaluate several methods extending ...

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    2. Spatio-temporal deep learning methods for motion estimation using 4D OCT image data

      Spatio-temporal deep learning methods for motion estimation using 4D OCT image data

      Purpose Localizing structures and estimating the motion of a specific target region are common problems for navigation during surgical interventions. Optical coherence tomography (OCT) is an imaging modality with a high spatial and temporal resolution that has been used for intraoperative imaging and also for motion estimation, for example, in the context of ophthalmic surgery or cochleostomy. Recently, motion estimation between a template and a moving OCT image has been studied with deep learning methods to overcome the shortcomings of conventional, feature-based methods. Methods We investigate whether using a temporal stream of OCT image volumes can improve deep learning-based motion ...

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    3. In-Vitro MPI-guided IVOCT catheter tracking in real time for motion artifact compensation

      In-Vitro MPI-guided IVOCT catheter tracking in real time for motion artifact compensation

      Purpose Using 4D magnetic particle imaging (MPI), intravascular optical coherence tomography (IVOCT) catheters are tracked in real time in order to compensate for image artifacts related to relative motion. Our approach demonstrates the feasibility for bimodal IVOCT and MPI in-vitro experiments. Material and methods During IVOCT imaging of a stenosis phantom the catheter is tracked using MPI. A 4D trajectory of the catheter tip is determined from the MPI data using center of mass sub-voxel strategies. A custom built IVOCT imaging adapter is used to perform different catheter motion profiles: no motion artifacts, motion artifacts due to catheter bending, and ...

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      Mentions: Thorlabs
    4. Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks

      Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks

      Coronary heart disease is a common cause of death despite being preventable. To treat the underlying plaque deposits in the arterial walls, intravascular optical coherence tomography can be used by experts to detect and characterize the lesions. In clinical routine, hundreds of images are acquired for each patient, which require automatic plaque detection for fast and accurate decision support. So far, automatic approaches rely on classic machine learning methods and deep learning solutions have rarely been studied. Given the success of deep learning methods with other imaging modalities, a thorough understanding of deep learning-based plaque detection for future clinical decision ...

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    5. Feasibility of a markerless tracking system based on optical coherence tomography

      Feasibility of a markerless tracking system based on optical coherence tomography

      Clinical tracking systems are popular but typically require specific tracking markers. During the last years, scanning speed of optical coherence tomography (OCT) has increased to A-scan rates above 1 MHz allowing to acquire volume scans of moving objects. Thorefore, we propose a markerless tracking system based on OCT to obtain small volumetric images including information of sub-surface structures at high spatio-temporal resolution. In contrast to conventional vision based approaches, this allows identifying natural landmarks even for smooth and homogeneous surfaces. We describe the optomechanical setup and process flow to evaluate OCT volumes for translations and accordingly adjust the position of ...

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    6. Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation

      Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation

      Automatic motion compensation and adjustment of an intraoperative imaging modality’s field of view is a common problem during interventions. Optical coherence tomography (OCT) is an imaging modality which is used in interventions due to its high spatial resolution of few micrometers and its temporal resolution of potentially several hundred volumes per second. However, performing motion compensation with OCT is problematic due to its small field of view which might lead to tracked objects being lost quickly. We propose a novel deep learning-based approach that directly learns input parameters of motors that move the scan area for motion compensation from ...

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    7. A Deep Learning Approach for Pose Estimation from Volumetric OCT Data

      A Deep Learning Approach for Pose Estimation from Volumetric OCT Data

      Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view. However, OCT image processing is challenging due to speckle noise and reflection artifacts in addition to the images’ 3D nature. We address pose estimation from OCT volume data with a new deep learning-based tracking framework. For this purpose, we design a new 3D convolutional neural network (CNN) architecture to directly predict the 6D pose of a ...

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    8. An Approach for Needle Based Optical Coherence Elastography Measurements

      An Approach for Needle Based Optical Coherence Elastography Measurements

      While navigation and interventional guidance are typically based on image data, the images do not necessarily reflect mechanical tissue properties. Optical coherence elastography (OCE) presents a modality with high sensitivity and very high spatial and temporal resolution. However, OCE has a limited field of view of only 2–5 mm depth. We present a side-facing needle probe to image externally induced shear waves from within soft tissue. A first method of quantitative needle-based OCE is provided. Using a time of flight setup, we establish the shear wave velocity and estimate the tissue elasticity. For comparison, an external scan head is ...

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    9. Development of a new catheter prototype for laser thrombolysis under guidance of optical coherence tomography (OCT): validation of feasibility and efficacy in a preclinical model

      Development of a new catheter prototype for laser thrombolysis under guidance of optical coherence tomography (OCT): validation of feasibility and efficacy in a preclinical model

      In this feasibility study, a novel catheter prototype for laser thrombolysis under the guidance of optical coherence tomography (OCT) was designed and evaluated in a preclinical model. Human arteries and veins were integrated into a physiological flow model and occluded with thrombi made from the Chandler Loop. There were four experimental groups: placebo, 20 mg alteplase, laser, 20 mg alteplase + laser. The extent of thrombolysis was analyzed by weighing, OCT imaging and relative thrombus size. In the alteplase group, thrombus size decreased to 0.250 ± 0.036 g (p < 0.0001) and 14.495 ± 0.526 mm 2 (p < 0 ...

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    10. Towards contactless optical coherence elastography with acoustic tissue excitation

      Towards contactless optical coherence elastography with acoustic tissue excitation

      Elastography presents an interesting approach to complement image data with mechanical tissue properties. Typically, the tissue is excited by direct contact to a probe. We study contactless elastography based on optical coherence tomography (OCT) and dynamic acoustic tissue excitation with airborne sound. We illustrate the principle and an implementation using sound waves of 135 Hz to excite the tissue. The displacement is measured and results of several tests indicate the feasibility to obtain a qualitative measure of the mechanical tissue properties. The approach is interesting for optical palpation, e.g., to enhance navigation and tissue characterization in minimally invasive and ...

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    11. Feasibiliy of optical detection of soft tissue deformation during needle insertion

      Feasibiliy of optical detection of soft tissue deformation during needle insertion

      Needles provide an effective way to reach lesions in soft tissue and are frequently used for diagnosis and treatment. Examples include biopsies, tumor ablation, and brachytherapy. Yet, precise localization of the needle with respect to the target is complicated by motion and deformation of the tissue during insertion. We have developed a prototypical needle with an embedded optical fiber allowing to obtain optical coherence tomography images of the tissue in front of the needle tip. Using the data and particularly the Doppler information it is possible to estimate the motion of the needle tip with respect to the surrounding soft ...

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    1-11 of 11
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  2. Topics in the News

    1. (2 articles) University of Lübeck
    2. (2 articles) Gereon Hüttmann
    3. (1 articles) Thorlabs
    4. (1 articles) Jikei University School of Medicine
    5. (1 articles) Macquarie University
    6. (1 articles) Medical University of Vienna
    7. (1 articles) University of Florence
    8. (1 articles) National Institutes of Health
    9. (1 articles) Beth Israel Deaconess Medical Center
    10. (1 articles) Giacomo Savini
    11. (1 articles) Bernhard Baumann
    12. (1 articles) Antonia Lichtenegger
    13. (1 articles) Movu
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    Feasibiliy of optical detection of soft tissue deformation during needle insertion Towards contactless optical coherence elastography with acoustic tissue excitation Development of a new catheter prototype for laser thrombolysis under guidance of optical coherence tomography (OCT): validation of feasibility and efficacy in a preclinical model An Approach for Needle Based Optical Coherence Elastography Measurements A Deep Learning Approach for Pose Estimation from Volumetric OCT Data Two-path 3D CNNs for calibration of system parameters for OCT-based motion compensation Feasibility of a markerless tracking system based on optical coherence tomography Automatic Plaque Detection in IVOCT Pullbacks Using Convolutional Neural Networks In-Vitro MPI-guided IVOCT catheter tracking in real time for motion artifact compensation Spatio-temporal deep learning methods for motion estimation using 4D OCT image data Heterogeneity of Neointimal Healing Following Biodegradable-polymer Drug-Eluting Coronary Stent Implantation Swept-source and multimodal OCT technologies offer clinical advantages