Nassir Navab

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TU München ∙ Technische Universität München ∙ Johns Hopkins University

Head of Computer Aided Medical Procedures & Augmented Reality , Faculty of Computer Science at Technical University of Munich.

Graphite: GRAPH-Induced feaTure Extraction for Point Cloud Registration

3D Point clouds are a rich source of information that enjoy growing popu...
10/18/2020 ∙ by Mahdi Saleh, et al. ∙ 0 ∙ share

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RGB-D SLAM with Structural Regularities

This work proposes a RGB-D SLAM system specifically designed for structu...
10/15/2020 ∙ by Yanyan Li, et al. ∙ 0 ∙ share

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I Like to Move It: 6D Pose Estimation as an Action Decision Process

Object pose estimation is an integral part of robot vision and augmented...
09/26/2020 ∙ by Benjamin Busam, et al. ∙ 0 ∙ share

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Polyp-artifact relationship analysis using graph inductive learned representations

The diagnosis process of colorectal cancer mainly focuses on the localiz...
09/15/2020 ∙ by Roger D. Soberanis-Mukul, et al. ∙ 0 ∙ share

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Inverse Distance Aggregation for Federated Learning with Non-IID Data

Federated learning (FL) has been a promising approach in the field of me...
08/17/2020 ∙ by Yousef Yeganeh, et al. ∙ 0 ∙ share

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SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification

Point clouds are often the default choice for many applications as they ...
08/17/2020 ∙ by Yida Wang, et al. ∙ 24 ∙ share

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Continual Class Incremental Learning for CT Thoracic Segmentation

Deep learning organ segmentation approaches require large amounts of ann...
08/12/2020 ∙ by Abdelrahman Elskhawy, et al. ∙ 13 ∙ share

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Structure-SLAM: Low-Drift Monocular SLAM in Indoor Environments

In this paper a low-drift monocular SLAM method is proposed targeting in...
08/05/2020 ∙ by Yanyan Li, et al. ∙ 0 ∙ share

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DynaMiTe: A Dynamic Local Motion Model with Temporal Constraints for Robust Real-Time Feature Matching

Feature based visual odometry and SLAM methods require accurate and fast...
07/31/2020 ∙ by Patrick Ruhkamp, et al. ∙ 0 ∙ share

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Attention based Multiple Instance Learning for Classification of Blood Cell Disorders

Red blood cells are highly deformable and present in various shapes. In ...
07/22/2020 ∙ by Ario Sadafi, et al. ∙ 0 ∙ share

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Towards Unsupervised Learning for Instrument Segmentation in Robotic Surgery with Cycle-Consistent Adversarial Networks

Surgical tool segmentation in endoscopic images is an important problem:...
07/09/2020 ∙ by Daniil Pakhomov, et al. ∙ 13 ∙ share

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Searching for Efficient Architecture for Instrument Segmentation in Robotic Surgery

Segmentation of surgical instruments is an important problem in robot-as...
07/08/2020 ∙ by Daniil Pakhomov, et al. ∙ 0 ∙ share

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Augment Yourself: Mixed Reality Self-Augmentation Using Optical See-through Head-mounted Displays and Physical Mirrors

Optical see-though head-mounted displays (OST HMDs) are one of the key t...
07/06/2020 ∙ by Mathias Unberath, et al. ∙ 5 ∙ share

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Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI

Brain pathologies can vary greatly in size and shape, ranging from few p...
06/23/2020 ∙ by Christoph Baur, et al. ∙ 0 ∙ share

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Model-Based Compensation of Moving Tissue for State Recognition in Robotic-Assisted Pedicle Drilling

Drilling is one of the hardest parts of pedicle screw fixation, and it i...
06/02/2020 ∙ by Zhongliang Jiang, et al. ∙ 0 ∙ share

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Simultaneous imputation and disease classification in incomplete medical datasets using Multigraph Geometric Matrix Completion (MGMC)

Large-scale population-based studies in medicine are a key resource towa...
05/14/2020 ∙ by Gerome Vivar, et al. ∙ 11 ∙ share

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Domain-specific loss design for unsupervised physical training: A new approach to modeling medical ML solutions

Today, cataract surgery is the most frequently performed ophthalmic surg...
05/09/2020 ∙ by Hendrik Burwinkel, et al. ∙ 0 ∙ share

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Decision Support for Intoxication Prediction Using Graph Convolutional Networks

Every day, poison control centers (PCC) are called for immediate classif...
05/02/2020 ∙ by Hendrik Burwinkel, et al. ∙ 8 ∙ share

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Explicit Domain Adaptation with Loosely Coupled Samples

Transfer learning is an important field of machine learning in general, ...
04/24/2020 ∙ by Oliver Scheel, et al. ∙ 0 ∙ share

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Colonoscope tracking method based on shape estimation network

This paper presents a colonoscope tracking method utilizing a colon shap...
04/20/2020 ∙ by Masahiro Oda, et al. ∙ 9 ∙ share

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Self6D: Self-Supervised Monocular 6D Object Pose Estimation

Estimating the 6D object pose is a fundamental problem in computer visio...
04/14/2020 ∙ by Gu Wang, et al. ∙ 8 ∙ share

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6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference

We present a multimodal camera relocalization framework that captures am...
04/09/2020 ∙ by Mai Bui, et al. ∙ 10 ∙ share

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Learning 3D Semantic Scene Graphs from 3D Indoor Reconstructions

Scene understanding has been of high interest in computer vision. It enc...
04/08/2020 ∙ by Johanna Wald, et al. ∙ 0 ∙ share

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Semantic Image Manipulation Using Scene Graphs

Image manipulation can be considered a special case of image generation ...
04/07/2020 ∙ by Helisa Dhamo, et al. ∙ 0 ∙ share

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Spatio-temporal Learning from Longitudinal Data for Multiple Sclerosis Lesion Segmentation

Segmentation of Multiple Sclerosis (MS) lesions in longitudinal brain MR...
04/07/2020 ∙ by Stefan Denner, et al. ∙ 9 ∙ share

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Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study

Deep unsupervised representation learning has recently led to new approa...
04/07/2020 ∙ by Christoph Baur, et al. ∙ 0 ∙ share

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Confident Coreset for Active Learning in Medical Image Analysis

Recent advances in deep learning have resulted in great successes in var...
04/05/2020 ∙ by Seong Tae Kim, et al. ∙ 0 ∙ share

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Peri-Diagnostic Decision Support Through Cost-Efficient Feature Acquisition at Test-Time

Computer-aided diagnosis (CADx) algorithms in medicine provide patient-s...
03/31/2020 ∙ by Gerome Vivar, et al. ∙ 4 ∙ share

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Ultrasound-Guided Robotic Navigation with Deep Reinforcement Learning

In this paper we introduce the first reinforcement learning (RL) based r...
03/30/2020 ∙ by Hannes Hase, et al. ∙ 11 ∙ share

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Latent Patient Network Learning for Automatic Diagnosis

Recently, Graph Convolutional Networks (GCNs) has proven to be a powerfu...
03/27/2020 ∙ by Luca Cosmo, et al. ∙ 0 ∙ share

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ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging

Medical image segmentation is one of the major challenges addressed by m...
03/20/2020 ∙ by Tariq Bdair, et al. ∙ 0 ∙ share

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CPS: Class-level 6D Pose and Shape Estimation From Monocular Images

Contemporary monocular 6D pose estimation methods can only cope with a h...
03/12/2020 ∙ by Fabian Manhardt, et al. ∙ 10 ∙ share

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Fairness by Learning Orthogonal Disentangled Representations

Learning discriminative powerful representations is a crucial step for m...
03/12/2020 ∙ by Mhd Hasan Sarhan, et al. ∙ 0 ∙ share

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From Perspective X-ray Imaging to Parallax-Robust Orthographic Stitching

Stitching images acquired under perspective projective geometry is a rel...
03/05/2020 ∙ by Javad Fotouhi, et al. ∙ 6 ∙ share

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Exploring Partial Intrinsic and Extrinsic Symmetry in 3D Medical Imaging

We present a novel methodology to detect imperfect bilateral symmetry in...
03/04/2020 ∙ by Javad Fotouhi, et al. ∙ 6 ∙ share

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Spatiotemporal-Aware Augmented Reality: Redefining HCI in Image-Guided Therapy

Suboptimal interaction with patient data and challenges in mastering 3D ...
03/04/2020 ∙ by Javad Fotouhi, et al. ∙ 9 ∙ share

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On the Effectiveness of Virtual Reality-based Training for Robotic Setup

Virtual Reality (VR) is rapidly increasing in popularity as a teaching t...
03/03/2020 ∙ by Arian Mehrfard, et al. ∙ 0 ∙ share

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Force-Ultrasound Fusion: Bringing Spine Robotic-US to the Next "Level"

Spine injections are commonly performed in several clinical procedures. ...
02/26/2020 ∙ by Maria Tirindelli, et al. ∙ 9 ∙ share

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Differentiable Graph Module (DGM) Graph Convolutional Networks

Graph deep learning has recently emerged as a powerful ML concept allowi...
02/11/2020 ∙ by Anees Kazi, et al. ∙ 36 ∙ share

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A learning without forgetting approach to incorporate artifact knowledge in polyp localization tasks

Colorectal polyps are abnormalities in the colon tissue that can develop...
02/07/2020 ∙ by Roger D. Soberanis-Mukul, et al. ∙ 0 ∙ share

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Pivot calibration concept for sensor attached mobile c-arms

Medical augmented reality has been actively studied for decades and many...
01/09/2020 ∙ by Sing Chun Lee, et al. ∙ 0 ∙ share

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Animals in Virtual Environments

The core idea in an XR (VR/MR/AR) application is to digitally stimulate ...
12/30/2019 ∙ by Hemal Naik, et al. ∙ 0 ∙ share

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A Comparative Analysis of Virtual Reality Head-Mounted Display Systems

With recent advances of Virtual Reality (VR) technology, the deployment ...
12/05/2019 ∙ by Arian Mehrfard, et al. ∙ 25 ∙ share

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Explaining Neural Networks via Perturbing Important Learned Features

Attributing the output of a neural network to the contribution of given ...
11/25/2019 ∙ by Ashkan Khakzar, et al. ∙ 54 ∙ share

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Real-Time 3D Model Tracking in Color and Depth on a Single CPU Core

We present a novel method to track 3D models in color and depth data. To...
11/22/2019 ∙ by Wadim Kehl, et al. ∙ 63 ∙ share

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Radar Emitter Classification with Attribute-specific Recurrent Neural Networks

Radar pulse streams exhibit increasingly complex temporal patterns and c...
11/18/2019 ∙ by Paolo Notaro, et al. ∙ 0 ∙ share

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Signal Clustering with Class-independent Segmentation

Radar signals have been dramatically increasing in complexity, limiting ...
11/18/2019 ∙ by Stefano Gasperini, et al. ∙ 0 ∙ share

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CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions

Data-driven computational approaches have evolved to enable extraction o...
10/20/2019 ∙ by Tom Vercauteren, et al. ∙ 18 ∙ share

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Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories

Metal artifacts in computed tomography (CT) arise from a mismatch betwee...
09/19/2019 ∙ by Jan-Nico Zaech, et al. ∙ 20 ∙ share

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Learn to Estimate Labels Uncertainty for Quality Assurance

Deep Learning sets the state-of-the-art in many challenging tasks showin...
09/17/2019 ∙ by Agnieszka Tomczack, et al. ∙ 0 ∙ share

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Nassir Navab

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