1 code implementation • 30 Nov 2023 • Chantal Pellegrini, Ege Özsoy, Benjamin Busam, Nassir Navab, Matthias Keicher
Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology.
no code implementations • 20 Nov 2023 • Mayar Lotfy, Anna Alperovich, Tommaso Giannantonio, Bjorn Barz, Xiaohan Zhang, Felix Holm, Nassir Navab, Felix Boehm, Carolin Schwamborn, Thomas K. Hoffmann, Patrick J. Schuler
Despite the limited dataset, the GNN-based model significantly outperforms context-agnostic approaches, accurately distinguishing between healthy and tumor tissues, even in images from previously unseen patients.
no code implementations • 18 Nov 2023 • Yamei Chen, Yan Di, Guangyao Zhai, Fabian Manhardt, Chenyangguang Zhang, Ruida Zhang, Federico Tombari, Nassir Navab, Benjamin Busam
These geometric features are then point-aligned with DINOv2 features to establish a consistent object representation under SE(3) transformations, facilitating the mapping from camera space to the pre-defined canonical space, thus further enhancing pose estimation.
no code implementations • 15 Nov 2023 • Junjie Yang, Zhihao Zhao, Siyuan Shen, Daniel Zapp, Mathias Maier, Kai Huang, Nassir Navab, M. Ali Nasseri
Robotic ophthalmic surgery is an emerging technology to facilitate high-precision interventions such as retina penetration in subretinal injection and removal of floating tissues in retinal detachment depending on the input imaging modalities such as microscopy and intraoperative OCT (iOCT).
no code implementations • 9 Nov 2023 • Sen Wang, Wei zhang, Stefano Gasperini, Shun-Cheng Wu, Nassir Navab
Creating high-quality view synthesis is essential for immersive applications but continues to be problematic, particularly in indoor environments and for real-time deployment.
no code implementations • 3 Nov 2023 • Pavel Jahoda, Azade Farshad, Yousef Yeganeh, Ehsan Adeli, Nassir Navab
We take advantage of the outer part of the masked area as they have a direct correlation with the context of the scene.
no code implementations • 25 Sep 2023 • Alex Ranne, Yordanka Velikova, Nassir Navab, Ferdinando Rodriguez y Baena
To date, endovascular surgeries are performed using the golden standard of Fluoroscopy, which uses ionising radiation to visualise catheters and vasculature.
no code implementations • 25 Sep 2023 • Felix Holm, Ghazal Ghazaei, Tobias Czempiel, Ege Özsoy, Stefan Saur, Nassir Navab
Surgical videos captured from microscopic or endoscopic imaging devices are rich but complex sources of information, depicting different tools and anatomical structures utilized during an extended amount of time.
no code implementations • 21 Sep 2023 • Guangyao Zhai, Xiaoni Cai, Dianye Huang, Yan Di, Fabian Manhardt, Federico Tombari, Nassir Navab, Benjamin Busam
In this paper, we present SG-Bot, a novel rearrangement framework that utilizes a coarse-to-fine scheme with a scene graph as the scene representation.
no code implementations • 18 Sep 2023 • Mert Asim Karaoglu, Viktoria Markova, Nassir Navab, Benjamin Busam, Alexander Ladikos
While most classical methods achieve rotation-equivariant detection and invariant description by design, many learning-based approaches learn to be robust only up to a certain degree.
no code implementations • 16 Sep 2023 • Mert Asim Karaoglu, Hannah Schieber, Nicolas Schischka, Melih Görgülü, Florian Grötzner, Alexander Ladikos, Daniel Roth, Nassir Navab, Benjamin Busam
Dynamic reconstruction with neural radiance fields (NeRF) requires accurate camera poses.
no code implementations • ICCV 2023 • Zhiying Leng, Shun-Cheng Wu, Mahdi Saleh, Antonio Montanaro, Hao Yu, Yin Wang, Nassir Navab, Xiaohui Liang, Federico Tombari
In this work, we propose the first precise hand-object reconstruction method in hyperbolic space, namely Dynamic Hyperbolic Attention Network (DHANet), which leverages intrinsic properties of hyperbolic space to learn representative features.
no code implementations • 5 Sep 2023 • Yu Liu, Gesine Muller, Nassir Navab, Carsten Marr, Jan Huisken, Tingying Peng
Light-sheet fluorescence microscopy (LSFM), a planar illumination technique that enables high-resolution imaging of samples, experiences defocused image quality caused by light scattering when photons propagate through thick tissues.
1 code implementation • 1 Sep 2023 • Lennart Bastian, Vincent Bürgin, Ha Young Kim, Alexander Baumann, Benjamin Busam, Mahdi Saleh, Nassir Navab
We demonstrate that our multi-modal registration framework can localize images on the 3D surface topology of a patient-specific organ and the mean shape of an SSM.
no code implementations • 29 Aug 2023 • Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Nassir Navab, Benjamin Busam, Federico Tombari
We conduct extensive experiments across a variety of scenarios on data from KITTI, Waymo, and CrashD for 3D object detection, and on data from SemanticKITTI, Waymo, and nuScenes for 3D semantic segmentation.
no code implementations • 24 Aug 2023 • Ario Sadafi, Raheleh Salehi, Armin Gruber, Sayedali Shetab Boushehri, Pascal Giehr, Nassir Navab, Carsten Marr
Here, we propose a rehearsal-based continual learning approach for class incremental and domain incremental scenarios in white blood cell classification.
no code implementations • 24 Aug 2023 • Ario Sadafi, Matthias Hehr, Nassir Navab, Carsten Marr
To that end, we train multiple MIL models using different levels of sex imbalance in the training set and excluding certain age groups.
no code implementations • 21 Aug 2023 • HyunJun Jung, Patrick Ruhkamp, Nassir Navab, Benjamin Busam
This paper addresses the limitations of current datasets for 3D vision tasks in terms of accuracy, size, realism, and suitable imaging modalities for photometrically challenging objects.
no code implementations • 21 Aug 2023 • Patrick Ruhkamp, Daoyi Gao, HyunJun Jung, Nassir Navab, Benjamin Busam
6D pose estimation pipelines that rely on RGB-only or RGB-D data show limitations for photometrically challenging objects with e. g. textureless surfaces, reflections or transparency.
no code implementations • 18 Aug 2023 • Vanessa Gonzalez Duque, Leonhard Zirus, Yordanka Velikova, Nassir Navab, Diana Mateus
Therefore, we propose to give the confidence maps as additional information to the networks.
no code implementations • ICCV 2023 • Stefano Gasperini, Nils Morbitzer, HyunJun Jung, Nassir Navab, Federico Tombari
While state-of-the-art monocular depth estimation approaches achieve impressive results in ideal settings, they are highly unreliable under challenging illumination and weather conditions, such as at nighttime or in the presence of rain.
no code implementations • 14 Aug 2023 • Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter Schüffler, Nassir Navab
Leveraging this, we introduce DISBELIEVE, a local model poisoning attack that creates malicious parameters or gradients such that their distance to benign clients' parameters or gradients is low respectively but at the same time their adverse effect on the global model's performance is high.
no code implementations • 7 Aug 2023 • Ardit Ramadani, Peter Ewert, Heribert Schunkert, Nassir Navab
Accurate catheter tracking is crucial during minimally invasive endovascular procedures (MIEP), and electromagnetic (EM) tracking is a widely used technology that serves this purpose.
1 code implementation • 7 Aug 2023 • Zhongliang Jiang, Yue Zhou, Dongliang Cao, Nassir Navab
The recovery of morphologically accurate anatomical images from deformed ones is challenging in ultrasound (US) image acquisition, but crucial to accurate and consistent diagnosis, particularly in the emerging field of computer-assisted diagnosis.
1 code implementation • 29 Jul 2023 • Yordanka Velikova, Mohammad Farid Azampour, Walter Simson, Vanessa Gonzalez Duque, Nassir Navab
Anatomical segmentation of organs in ultrasound images is essential to many clinical applications, particularly for diagnosis and monitoring.
1 code implementation • 27 Jul 2023 • Kun Yuan, Vinkle Srivastav, Tong Yu, Joel Lavanchy, Pietro Mascagni, Nassir Navab, Nicolas Padoy
SurgVLP constructs a new contrastive learning objective to align video clip embeddings with the corresponding multiple text embeddings by bringing them together within a joint latent space.
1 code implementation • 26 Jul 2023 • Lennart Bastian, Tony Danjun Wang, Tobias Czempiel, Benjamin Busam, Nassir Navab
Methods: RGB and depth images from multiple cameras are fused into a 3D point cloud representation of the scene.
1 code implementation • 19 Jul 2023 • Matteo Ronchetti, Wolfgang Wein, Nassir Navab, Oliver Zettinig, Raphael Prevost
Our method is several orders of magnitude faster than local patch-based metrics and can be directly applied in clinical settings by replacing the similarity measure with the proposed one.
1 code implementation • 11 Jul 2023 • Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Nassir Navab
However, there is limited research on automating structured reporting, and no public benchmark is available for evaluating and comparing different methods.
Ranked #1 on
Structured Report Generation
on Rad-ReStruct
1 code implementation • 7 Jul 2023 • Zhongliang Jiang, Yuan Bi, Mingchuan Zhou, Ying Hu, Michael Burke, Nassir Navab
The results demonstrated that the proposed advanced framework can robustly work on a variety of seen and unseen phantoms as well as in-vivo human carotid data.
1 code implementation • 7 Jul 2023 • Zhongliang Jiang, Chenyang Li, Xuesong Li, Nassir Navab
To address this challenge, a graph-based non-rigid registration is proposed to enable transferring planned paths from the atlas to the current setup by explicitly considering subcutaneous bone surface features instead of the skin surface.
1 code implementation • 7 Jul 2023 • Dianye Huang, Yuan Bi, Nassir Navab, Zhongliang Jiang
To validate the proposed robotic US system for imaging arteries, experiments are carried out on volunteers' carotid and radial arteries.
no code implementations • 21 May 2023 • Mehdi Astaraki, Francesca De Benetti, Yousef Yeganeh, Iuliana Toma-Dasu, Örjan Smedby, Chunliang Wang, Nassir Navab, Thomas Wendler
This work intends to, first, propose a robust inpainting model to learn the details of healthy anatomies and reconstruct high-resolution images by preserving anatomical constraints.
no code implementations • 17 May 2023 • Francesca De Benetti, Walter Simson, Magdalini Paschali, Hasan Sari, Axel Romiger, Kuangyu Shi, Nassir Navab, Thomas Wendler
Dynamic positron emission tomography imaging (dPET) provides temporally resolved images of a tracer enabling a quantitative measure of physiological processes.
1 code implementation • 15 May 2023 • Zhongliang Jiang, Felix Duelmer, Nassir Navab
The experimental results demonstrate that the proposed approach with the re-identification process can significantly improve the accuracy and robustness of the segmentation results (dice score: from 0:54 to 0:86; intersection over union: from 0:47 to 0:78).
no code implementations • 14 May 2023 • Zhongliang Jiang, Xuesong Li, Chenyu Zhang, Yuan Bi, Walter Stechele, Nassir Navab
Autonomous ultrasound (US) scanning has attracted increased attention, and it has been seen as a potential solution to overcome the limitations of conventional US examinations, such as inter-operator variations.
no code implementations • 5 May 2023 • Jonas Hein, Nicola Cavalcanti, Daniel Suter, Lukas Zingg, Fabio Carrillo, Mazda Farshad, Marc Pollefeys, Nassir Navab, Philipp Fürnstahl
A particular focus in computer-assisted surgery is to replace marker-based tracking systems for instrument localization with pure image-based 6DoF pose estimation.
no code implementations • CVPR 2023 • Shun-Cheng Wu, Keisuke Tateno, Nassir Navab, Federico Tombari
Our method consists of a novel incremental entity estimation pipeline and a scene graph prediction network.
no code implementations • 28 Apr 2023 • Yousef Yeganeh, Azade Farshad, Goktug Guevercin, Amr Abu-zer, Rui Xiao, Yongjian Tang, Ehsan Adeli, Nassir Navab
Although the preservation of shape continuity and physiological anatomy is a natural assumption in the segmentation of medical images, it is often neglected by deep learning methods that mostly aim for the statistical modeling of input data as pixels rather than interconnected structures.
no code implementations • 28 Apr 2023 • Yousef Yeganeh, Azade Farshad, Peter Weinberger, Seyed-Ahmad Ahmadi, Ehsan Adeli, Nassir Navab
Although purely transformer-based architectures showed promising performance in many computer vision tasks, many hybrid models consisting of CNN and transformer blocks are introduced to fit more specialized tasks.
no code implementations • 28 Apr 2023 • Azade Farshad, Yousef Yeganeh, Yu Chi, Chengzhi Shen, Björn Ommer, Nassir Navab
To address this limitation, we propose a novel guidance approach for the sampling process in the diffusion model that leverages bounding box and segmentation map information at inference time without additional training data.
1 code implementation • 15 Apr 2023 • Lennart Bastian, Alexander Baumann, Emily Hoppe, Vincent Bürgin, Ha Young Kim, Mahdi Saleh, Benjamin Busam, Nassir Navab
Statistical shape models (SSMs) are an established way to represent the anatomy of a population with various clinically relevant applications.
no code implementations • 30 Mar 2023 • Dominik Batić, Felix Holm, Ege Özsoy, Tobias Czempiel, Nassir Navab
In this work, we investigate the need for endoscopy domain-specific pretraining based on downstream objectives.
1 code implementation • CVPR 2023 • HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai, Nikolas Brasch, Yitong Li, Yannick Verdie, Jifei Song, Yiren Zhou, Anil Armagan, Slobodan Ilic, Ales Leonardis, Nassir Navab, Benjamin Busam
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data.
1 code implementation • 24 Mar 2023 • Yiheng Xiong, Jingsong Liu, Kamilia Zaripova, Sahand Sharifzadeh, Matthias Keicher, Nassir Navab
The extraction of structured clinical information from free-text radiology reports in the form of radiology graphs has been demonstrated to be a valuable approach for evaluating the clinical correctness of report-generation methods.
no code implementations • 23 Mar 2023 • Ege Özsoy, Tobias Czempiel, Felix Holm, Chantal Pellegrini, Nassir Navab
The holistic representation of surgical scenes as semantic scene graphs (SGG), where entities are represented as nodes and relations between them as edges, is a promising direction for fine-grained semantic OR understanding.
Ranked #2 on
Scene Graph Generation
on 4D-OR
1 code implementation • 23 Mar 2023 • Chantal Pellegrini, Matthias Keicher, Ege Özsoy, Petra Jiraskova, Rickmer Braren, Nassir Navab
Automated diagnosis prediction from medical images is a valuable resource to support clinical decision-making.
2 code implementations • 22 Mar 2023 • Yuan Bi, Zhongliang Jiang, Ricarda Clarenbach, Reza Ghotbi, Angelos Karlas, Nassir Navab
We validate the generalizability of the proposed domain-independent segmentation approach on several datasets with varying parameters and machines.
no code implementations • 21 Mar 2023 • Matthias Keicher, Matan Atad, David Schinz, Alexandra S. Gersing, Sarah C. Foreman, Sophia S. Goller, Juergen Weissinger, Jon Rischewski, Anna-Sophia Dietrich, Benedikt Wiestler, Jan S. Kirschke, Nassir Navab
We then regress the severity of the fracture as a function of the distance to this hyperplane, calibrating the results to the Genant scale.
no code implementations • 20 Mar 2023 • Ege Özsoy, Felix Holm, Tobias Czempiel, Nassir Navab, Benjamin Busam
Although using significantly fewer labels during training, we achieve 74. 12\% of the location-supervised SOTA performance on Visual Genome and even outperform the best method on 4D-OR.
Ranked #1 on
Scene Graph Generation
on 4D-OR
no code implementations • 15 Mar 2023 • Artem Savkin, Rachid Ellouze, Nassir Navab, Federico Tombari
Image synthesis driven by computer graphics achieved recently a remarkable realism, yet synthetic image data generated this way reveals a significant domain gap with respect to real-world data.
1 code implementation • 15 Mar 2023 • Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr
Explainability is a key requirement for computer-aided diagnosis systems in clinical decision-making.
no code implementations • 2 Mar 2023 • Ario Sadafi, Nassir Navab, Carsten Marr
Querying the expert to annotate regions of interest in a WSI guides the formation of high-attention regions for MIL.
no code implementations • 2 Mar 2023 • Daniel Sens, Ario Sadafi, Francesco Paolo Casale, Nassir Navab, Carsten Marr
Recent MIL approaches produce highly informative bag level representations by utilizing the transformer architecture's ability to model the dependencies between instances.
no code implementations • CVPR 2023 • Dekai Zhu, Guangyao Zhai, Yan Di, Fabian Manhardt, Hendrik Berkemeyer, Tuan Tran, Nassir Navab, Federico Tombari, Benjamin Busam
Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems.
2 code implementations • 13 Feb 2023 • Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma, Aditya Murali, Deepak Alapatt, Armine Vardazaryan, Kun Yuan, Jonas Hajek, Wolfgang Reiter, Amine Yamlahi, Finn-Henri Smidt, Xiaoyang Zou, Guoyan Zheng, Bruno Oliveira, Helena R. Torres, Satoshi Kondo, Satoshi Kasai, Felix Holm, Ege Özsoy, Shuangchun Gui, Han Li, Sista Raviteja, Rachana Sathish, Pranav Poudel, Binod Bhattarai, Ziheng Wang, Guo Rui, Melanie Schellenberg, João L. Vilaça, Tobias Czempiel, Zhenkun Wang, Debdoot Sheet, Shrawan Kumar Thapa, Max Berniker, Patrick Godau, Pedro Morais, Sudarshan Regmi, Thuy Nuong Tran, Jaime Fonseca, Jan-Hinrich Nölke, Estevão Lima, Eduard Vazquez, Lena Maier-Hein, Nassir Navab, Pietro Mascagni, Barbara Seeliger, Cristians Gonzalez, Didier Mutter, Nicolas Padoy
This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection.
Ranked #1 on
Action Triplet Detection
on CholecT50 (Challenge)
no code implementations • 6 Feb 2023 • Walter A. Simson, Magdalini Paschali, Vasiliki Sideri-Lampretsa, Nassir Navab, Jeremy J. Dahl
However, the various types of breast tissue, such as glandular, fat, and lesions, differ in sound speed.
1 code implementation • 2 Feb 2023 • Masahiro Oda, Kazuhiro Furukawa, Nassir Navab, Kensaku MORI
Kinematic data of a colonoscope and the colon, including positions and directions of their centerlines, are obtained using electromagnetic and depth sensors.
no code implementations • 31 Jan 2023 • Artem Savkin, Yida Wang, Sebastian Wirkert, Nassir Navab, Federico Tombar
This in turn enables our method to employ a one-stage upsampling paradigm without the need for coarse and fine reconstruction.
no code implementations • 25 Jan 2023 • Magdalena Wysocki, Mohammad Farid Azampour, Christine Eilers, Benjamin Busam, Mehrdad Salehi, Nassir Navab
In our work, we discuss direction-dependent changes in the scene and show that a physics-inspired rendering improves the fidelity of US image synthesis.
no code implementations • 17 Jan 2023 • Shervin Dehghani, Michael Sommersperger, Peiyao Zhang, Alejandro Martin-Gomez, Benjamin Busam, Peter Gehlbach, Nassir Navab, M. Ali Nasseri, Iulian Iordachita
In this work, we propose a framework for autonomous robotic navigation for subretinal injection, based on intelligent real-time processing of iOCT volumes.
no code implementations • CVPR 2023 • Hanzhi Chen, Fabian Manhardt, Nassir Navab, Benjamin Busam
In this paper, we introduce neural texture learning for 6D object pose estimation from synthetic data and a few unlabelled real images.
1 code implementation • 22 Dec 2022 • Evin Pınar Örnek, Aravindhan K Krishnan, Shreekant Gayaka, Cheng-Hao Kuo, Arnie Sen, Nassir Navab, Federico Tombari
We introduce a zero-shot split for Tabletop Objects Dataset (TOD-Z) to enable this study and present a method that uses annotated objects to learn the ``objectness'' of pixels and generalize to unseen object categories in cluttered indoor environments.
no code implementations • 20 Dec 2022 • HyunJun Jung, Shun-Cheng Wu, Patrick Ruhkamp, Guangyao Zhai, Hannah Schieber, Giulia Rizzoli, Pengyuan Wang, Hongcheng Zhao, Lorenzo Garattoni, Sven Meier, Daniel Roth, Nassir Navab, Benjamin Busam
Estimating the 6D pose of objects is a major 3D computer vision problem.
no code implementations • 10 Nov 2022 • Azade Farshad, Yousef Yeganeh, Helisa Dhamo, Federico Tombari, Nassir Navab
Graph representation of objects and their relations in a scene, known as a scene graph, provides a precise and discernible interface to manipulate a scene by modifying the nodes or the edges in the graph.
no code implementations • 5 Nov 2022 • Mane Margaryan, Matthias Seibold, Indu Joshi, Mazda Farshad, Philipp Fürnstahl, Nassir Navab
In contrast to previously proposed fully convolutional models, the proposed model implements residual Squeeze and Excitation modules in the generator architecture.
no code implementations • 12 Oct 2022 • Agnieszka Tomczak, Aarushi Gupta, Slobodan Ilic, Nassir Navab, Shadi Albarqouni
The purpose of this work is to investigate the hypothesis that we can predict image quality based on its latent representation in the GANs bottleneck.
no code implementations • 26 Sep 2022 • Guangyao Zhai, Dianye Huang, Shun-Cheng Wu, HyunJun Jung, Yan Di, Fabian Manhardt, Federico Tombari, Nassir Navab, Benjamin Busam
6-DoF robotic grasping is a long-lasting but unsolved problem.
no code implementations • ICCV 2023 • Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Nassir Navab, Benjamin Busam, Federico Tombari
By doing so, for the first time in panoptic segmentation with unknown objects, our U3HS is trained without unknown categories, reducing assumptions and leaving the settings as unconstrained as in real-life scenarios.
1 code implementation • 10 Aug 2022 • Zhongliang Jiang, Yuan Gao, Le Xie, Nassir Navab
Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e. g. difficulty in guaranteeing intra- and inter-operator repeatability.
1 code implementation • 31 Jul 2022 • Rüdiger Göbl, Christoph Hennersperger, Nassir Navab
To enable this, we make use of realistic ultrasound simulation techniques that allow for instantiation of several independent speckle realizations that represent the exact same tissue, thus allowing for the application of image reconstruction techniques that work with pairs of differently corrupted data.
no code implementations • 31 Jul 2022 • Guangyao Zhai, Yu Zheng, Ziwei Xu, Xin Kong, Yong liu, Benjamin Busam, Yi Ren, Nassir Navab, Zhengyou Zhang
In this paper, we introduce DA$^2$, the first large-scale dual-arm dexterity-aware dataset for the generation of optimal bimanual grasping pairs for arbitrary large objects.
no code implementations • 31 Jul 2022 • Mahdi Saleh, Yige Wang, Nassir Navab, Benjamin Busam, Federico Tombari
The proposed hierarchical model achieves state-of-the-art shape classification in mean accuracy and yields results on par with the previous segmentation methods while requiring significantly fewer computations.
no code implementations • 28 Jul 2022 • Dominik Jüstel, Hedwig Irl, Florian Hinterwimmer, Christoph Dehner, Walter Simson, Nassir Navab, Gerhard Schneider, Vasilis Ntziachristos
Various morphological and functional parameters of peripheral nerves and their vascular supply are indicative of pathological changes due to injury or disease.
no code implementations • 25 Jul 2022 • Felix Buchert, Nassir Navab, Seong Tae Kim
By considering the consistency information with the diversity in the consistency-based embedding scheme, the proposed method could select more informative samples for labeling in the semi-supervised learning setting.
2 code implementations • 21 Jul 2022 • Chantal Pellegrini, Nassir Navab, Anees Kazi
We find that our proposed pre-training methods help in modeling the data at a patient and population level and improve performance in different fine-tuning tasks on all datasets.
1 code implementation • 18 Jul 2022 • Yordanka Velikova, Walter Simson, Mehrdad Salehi, Mohammad Farid Azampour, Philipp Paprottka, Nassir Navab
Abdominal aortic aneurysm (AAA) is a vascular disease in which a section of the aorta enlarges, weakening its walls and potentially rupturing the vessel.
1 code implementation • 15 Jul 2022 • Matan Atad, Vitalii Dmytrenko, Yitong Li, Xinyue Zhang, Matthias Keicher, Jan Kirschke, Bene Wiestler, Ashkan Khakzar, Nassir Navab
Deep learning models used in medical image analysis are prone to raising reliability concerns due to their black-box nature.
no code implementations • 12 Jul 2022 • Yousef Yeganeh, Azade Farshad, Nassir Navab
Inpainting has recently been proposed as a successful deep learning technique for unsupervised medical image model discovery.
no code implementations • 7 Jul 2022 • Yousef Yeganeh, Azade Farshad, Johann Boschmann, Richard Gaus, Maximilian Frantzen, Nassir Navab
Although most medical centers conduct similar medical imaging tasks, their differences, such as specializations, number of patients, and devices, lead to distinctive data distributions.
1 code implementation • 1 Jul 2022 • Raheleh Salehi, Ario Sadafi, Armin Gruber, Peter Lienemann, Nassir Navab, Shadi Albarqouni, Carsten Marr
Here, we propose a cross-domain adapted autoencoder to extract features in an unsupervised manner on three different datasets of single white blood cells scanned from peripheral blood smears.
no code implementations • 27 Jun 2022 • Yu Liu, Kurt Weiss, Nassir Navab, Carsten Marr, Jan Huisken, Tingying Peng
Light-sheet fluorescence microscopy (LSFM) is a cutting-edge volumetric imaging technique that allows for three-dimensional imaging of mesoscopic samples with decoupled illumination and detection paths.
no code implementations • 16 Jun 2022 • Marcel Kollovieh, Matthias Keicher, Stephan Wunderlich, Hendrik Burwinkel, Thomas Wendler, Nassir Navab
To this end, we propose a multi-task method based on U-Net that takes T1-weighted MR images as an input to generate synthetic FDG-PET images and classifies the dementia progression of the patient into cognitive normal (CN), cognitive impairment (MCI), and AD.
no code implementations • 13 Jun 2022 • Tariq Bdair, Hossam Abdelhamid, Nassir Navab, Shadi Albarqouni
We validate TriMix on eight benchmark datasets consisting of natural and medical images with an improvement of 2. 71% and 0. 41% better than the second-best models for both data types.
1 code implementation • 13 Jun 2022 • Matteo Ronchetti, Julia Rackerseder, Maria Tirindelli, Mehrdad Salehi, Nassir Navab, Wolfgang Wein, Oliver Zettinig
We propose a novel method to automatically calibrate tracked ultrasound probes.
no code implementations • 9 Jun 2022 • Shervin Dehghani, Benjamin Busam, Nassir Navab, Ali Nasseri
Despite its broad availability, volumetric information acquisition from Bright-Field Microscopy (BFM) is inherently difficult due to the projective nature of the acquisition process.
no code implementations • CVPR 2022 • Pengyuan Wang, HyunJun Jung, Yitong Li, Siyuan Shen, Rahul Parthasarathy Srikanth, Lorenzo Garattoni, Sven Meier, Nassir Navab, Benjamin Busam
Object pose estimation is crucial for robotic applications and augmented reality.
no code implementations • 16 May 2022 • Bailiang Jian, Mohammad Farid Azampour, Francesca De Benetti, Johannes Oberreuter, Christina Bukas, Alexandra S. Gersing, Sarah C. Foreman, Anna-Sophia Dietrich, Jon Rischewski, Jan S. Kirschke, Nassir Navab, Thomas Wendler
We specifically design these losses to depend only on the CT label maps since automatic vertebra segmentation in CT gives more accurate results contrary to MRI.
1 code implementation • 10 May 2022 • Yuan Bi, Zhongliang Jiang, Yuan Gao, Thomas Wendler, Angelos Karlas, Nassir Navab
The results demonstrate that proposed approach can effectively and accurately navigate the probe towards the longitudinal view of vessels.
1 code implementation • 9 May 2022 • Mohammad Eslami, Solale Tabarestani, Ehsan Adeli, Glyn Elwyn, Tobias Elze, Mengyu Wang, Nazlee Zebardast, Nassir Navab, Malek Adjouadi
With the advent of sophisticated machine learning (ML) techniques and the promising results they yield, especially in medical applications, where they have been investigated for different tasks to enhance the decision-making process.
no code implementations • 8 May 2022 • Yida Wang, David Joseph Tan, Nassir Navab, Federico Tombari
We propose a novel convolutional operator for the task of point cloud completion.
1 code implementation • 15 Apr 2022 • Azade Farshad, Yousef Yeganeh, Peter Gehlbach, Nassir Navab
Automated segmentation of retinal optical coherence tomography (OCT) images has become an important recent direction in machine learning for medical applications.
Ranked #1 on
Retinal OCT Layer Segmentation
on Duke SD-OCT
(using extra training data)
no code implementations • 4 Apr 2022 • Ashkan Khakzar, Yawei Li, Yang Zhang, Mirac Sanisoglu, Seong Tae Kim, Mina Rezaei, Bernd Bischl, Nassir Navab
One challenging property lurking in medical datasets is the imbalanced data distribution, where the frequency of the samples between the different classes is not balanced.
no code implementations • 1 Apr 2022 • Kamilia Mullakaeva, Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein
In this work, we propose Graph-in-Graph (GiG), a neural network architecture for protein classification and brain imaging applications that exploits the graph representation of the input data samples and their latent relation.
no code implementations • CVPR 2022 • Yida Wang, David Joseph Tan, Nassir Navab, Federico Tombari
To this aim, we introduce a second model that assembles our layers within a transformer architecture.
1 code implementation • 30 Mar 2022 • Paul Engstler, Matthias Keicher, David Schinz, Kristina Mach, Alexandra S. Gersing, Sarah C. Foreman, Sophia S. Goller, Juergen Weissinger, Jon Rischewski, Anna-Sophia Dietrich, Benedikt Wiestler, Jan S. Kirschke, Ashkan Khakzar, Nassir Navab
Do black-box neural network models learn clinically relevant features for fracture diagnosis?
no code implementations • 29 Mar 2022 • Matthias Keicher, Kamilia Zaripova, Tobias Czempiel, Kristina Mach, Ashkan Khakzar, Nassir Navab
The automation of chest X-ray reporting has garnered significant interest due to the time-consuming nature of the task.
1 code implementation • 25 Mar 2022 • Mojtaba Bahrami, Mahsa Ghorbani, Nassir Navab
We show that training the agent against the prediction model can significantly improve the semantic features extracted for downstream classification tasks.
2 code implementations • 23 Mar 2022 • Chantal Pellegrini, Anees Kazi, Nassir Navab
We test our method on two medical datasets of patient records, TADPOLE and MIMIC-III, including imaging and non-imaging features and different prediction tasks.
Ranked #1 on
Length-of-Stay prediction
on MIMIC-III
no code implementations • 22 Mar 2022 • Matthias Seibold, Armando Hoch, Mazda Farshad, Nassir Navab, Philipp Fürnstahl
In this work, we propose a novel data augmentation method for clinical audio datasets based on a conditional Wasserstein Generative Adversarial Network with Gradient Penalty (cWGAN-GP), operating on log-mel spectrograms.
1 code implementation • 22 Mar 2022 • Ege Özsoy, Evin Pınar Örnek, Ulrich Eck, Tobias Czempiel, Federico Tombari, Nassir Navab
Towards this goal, for the first time, we propose using semantic scene graphs (SSG) to describe and summarize the surgical scene.
Ranked #3 on
Scene Graph Generation
on 4D-OR
no code implementations • 21 Mar 2022 • Tobias Czempiel, Coco Rogers, Matthias Keicher, Magdalini Paschali, Rickmer Braren, Egon Burian, Marcus Makowski, Nassir Navab, Thomas Wendler, Seong Tae Kim
For this purpose, longitudinal self-supervision schemes are explored on clinical longitudinal COVID-19 CT scans.
1 code implementation • CVPR 2022 • Yongzhi Su, Mahdi Saleh, Torben Fetzer, Jason Rambach, Nassir Navab, Benjamin Busam, Didier Stricker, Federico Tombari
Dense methods also improved pose estimation in the presence of occlusion.
no code implementations • 17 Mar 2022 • Tobias Czempiel, Aidean Sharghi, Magdalini Paschali, Nassir Navab, Omid Mohareri
Algorithmic surgical workflow recognition is an ongoing research field and can be divided into laparoscopic (Internal) and operating room (External) analysis.
no code implementations • 16 Mar 2022 • Lennart Bastian, Tobias Czempiel, Christian Heiliger, Konrad Karcz, Ulrich Eck, Benjamin Busam, Nassir Navab
Existing datasets from OR room cameras are thus far limited in size or modalities acquired, leaving it unclear which sensor modalities are best suited for tasks such as recognizing surgical action from videos.
2 code implementations • CVPR 2022 • Yan Di, Ruida Zhang, Zhiqiang Lou, Fabian Manhardt, Xiangyang Ji, Nassir Navab, Federico Tombari
While 6D object pose estimation has recently made a huge leap forward, most methods can still only handle a single or a handful of different objects, which limits their applications.
Ranked #1 on
6D Pose Estimation
on LineMOD
(Mean ADD-S metric)
no code implementations • 15 Mar 2022 • Evin Pınar Örnek, Shristi Mudgal, Johanna Wald, Yida Wang, Nassir Navab, Federico Tombari
There have been numerous recently proposed methods for monocular depth prediction (MDP) coupled with the equally rapid evolution of benchmarking tools.
no code implementations • CVPR 2022 • Ashkan Khakzar, Pedram Khorsandi, Rozhin Nobahari, Nassir Navab
It is a mystery which input features contribute to a neural network's output.
no code implementations • CVPR 2022 • Mahdi Saleh, Shun-Cheng Wu, Luca Cosmo, Nassir Navab, Benjamin Busam, Federico Tombari
Shape matching has been a long-studied problem for the computer graphics and vision community.
no code implementations • 14 Jan 2022 • John Ridley, Huseyin Coskun, David Joseph Tan, Nassir Navab, Federico Tombari
The video action segmentation task is regularly explored under weaker forms of supervision, such as transcript supervision, where a list of actions is easier to obtain than dense frame-wise labels.
1 code implementation • CVPR 2022 • Daniel Grzech, Mohammad Farid Azampour, Ben Glocker, Julia Schnabel, Nassir Navab, Bernhard Kainz, Loïc le Folgoc
We propose a novel variational Bayesian formulation for diffeomorphic non-rigid registration of medical images, which learns in an unsupervised way a data-specific similarity metric.
no code implementations • CVPR 2022 • Alexander Lehner, Stefano Gasperini, Alvaro Marcos-Ramiro, Michael Schmidt, Mohammad-Ali Nikouei Mahani, Nassir Navab, Benjamin Busam, Federico Tombari
Despite training only on a standard dataset, such as KITTI, augmenting with our vector fields significantly improves the generalization to differently shaped objects and scenes.
no code implementations • 7 Dec 2021 • HyunJun Jung, Nikolas Brasch, Ales Leonardis, Nassir Navab, Benjamin Busam
Indirect Time-of-Flight (I-ToF) imaging is a widespread way of depth estimation for mobile devices due to its small size and affordable price.
no code implementations • 6 Dec 2021 • Pengyuan Wang, Fabian Manhardt, Luca Minciullo, Lorenzo Garattoni, Sven Meie, Nassir Navab, Benjamin Busam
We first present a small sequence of RGB-D images displaying a human-object interaction.
1 code implementation • 2 Dec 2021 • Enis Simsar, Evin Pınar Örnek, Fabian Manhardt, Helisa Dhamo, Nassir Navab, Federico Tombari
With the advent of deep learning, estimating depth from a single RGB image has recently received a lot of attention, being capable of empowering many different applications ranging from path planning for robotics to computational cinematography.
no code implementations • 30 Nov 2021 • Shervin Dehghani, Michael Sommersperger, Junjie Yang, Benjamin Busam, Kai Huang, Peter Gehlbach, Iulian Iordachita, Nassir Navab, M. Ali Nasseri
For this purpose, we present a platform for autonomous trocar docking that combines computer vision and a robotic setup.
1 code implementation • 22 Oct 2021 • Azade Farshad, Sabrina Musatian, Helisa Dhamo, Nassir Navab
We propose MIGS (Meta Image Generation from Scene Graphs), a meta-learning based approach for few-shot image generation from graphs that enables adapting the model to different scenes and increases the image quality by training on diverse sets of tasks.
no code implementations • 15 Oct 2021 • Patrick Ruhkamp, Daoyi Gao, Hanzhi Chen, Nassir Navab, Benjamin Busam
A novel temporal attention mechanism further processes the local geometric information in a global context across consecutive images.
no code implementations • 8 Oct 2021 • Markus Herb, Matthias Lemberger, Marcel M. Schmitt, Alexander Kurz, Tobias Weiherer, Nassir Navab, Federico Tombari
Accurate and reliable localization is a fundamental requirement for autonomous vehicles to use map information in higher-level tasks such as navigation or planning.
no code implementations • 4 Oct 2021 • Stefano Gasperini, Jan Haug, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Benjamin Busam, Federico Tombari
Estimating the uncertainty of a neural network plays a fundamental role in safety-critical settings.
1 code implementation • NeurIPS 2021 • Yang Zhang, Ashkan Khakzar, Yawei Li, Azade Farshad, Seong Tae Kim, Nassir Navab
We propose a method to identify features with predictive information in the input domain.
no code implementations • 3 Oct 2021 • Michelle Xiao-Lin Foo, Seong Tae Kim, Magdalini Paschali, Leili Goli, Egon Burian, Marcus Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
Existing automatic and interactive segmentation models for medical images only use data from a single time point (static).
no code implementations • 24 Sep 2021 • Mert Asim Karaoglu, Nikolas Brasch, Marijn Stollenga, Wolfgang Wein, Nassir Navab, Federico Tombari, Alexander Ladikos
The results of our experiments show that the proposed method improves the network's performance on real images by a considerable margin and can be employed in 3D reconstruction pipelines.
no code implementations • 18 Sep 2021 • Anastasia Makarevich, Azade Farshad, Vasileios Belagiannis, Nassir Navab
In this work, we present MetaMedSeg, a gradient-based meta-learning algorithm that redefines the meta-learning task for the volumetric medical data with the goal to capture the variety between the slices.
no code implementations • 11 Sep 2021 • Ario Sadafi, Asya Makhro, Leonid Livshits, Nassir Navab, Anna Bogdanova, Shadi Albarqouni, Carsten Marr
Sickle cell disease (SCD) is a severe genetic hemoglobin disorder that results in premature destruction of red blood cells.
1 code implementation • ICCV 2021 • Helisa Dhamo, Fabian Manhardt, Nassir Navab, Federico Tombari
Scene graphs are representations of a scene, composed of objects (nodes) and inter-object relationships (edges), proven to be particularly suited for this task, as they allow for semantic control on the generated content.
2 code implementations • ICCV 2021 • Yan Di, Fabian Manhardt, Gu Wang, Xiangyang Ji, Nassir Navab, Federico Tombari
Directly regressing all 6 degrees-of-freedom (6DoF) for the object pose (e. g. the 3D rotation and translation) in a cluttered environment from a single RGB image is a challenging problem.
Ranked #1 on
6D Pose Estimation using RGB
on Occlusion LineMOD
no code implementations • ICCV 2021 • Sarthak Garg, Helisa Dhamo, Azade Farshad, Sabrina Musatian, Nassir Navab, Federico Tombari
Scene graphs, composed of nodes as objects and directed-edges as relationships among objects, offer an alternative representation of a scene that is more semantically grounded than images.
no code implementations • 10 Aug 2021 • Markus Krönke, Christine Eilers, Desislava Dimova, Melanie Köhler, Gabriel Buschner, Lilit Mirzojan, Lemonia Konstantinidou, Marcus R. Makowski, James Nagarajah, Nassir Navab, Wolfgang Weber, Thomas Wendler
Conclusion: Tracked 3D ultrasound combined with a CNN segmentation significantly reduces interobserver variability in thyroid volumetry and increases the accuracy of the measurements with shorter acquisition times.
no code implementations • 10 Aug 2021 • Stefano Gasperini, Patrick Koch, Vinzenz Dallabetta, Nassir Navab, Benjamin Busam, Federico Tombari
While self-supervised monocular depth estimation in driving scenarios has achieved comparable performance to supervised approaches, violations of the static world assumption can still lead to erroneous depth predictions of traffic participants, posing a potential safety issue.
no code implementations • 29 Jul 2021 • Matthias Keicher, Hendrik Burwinkel, David Bani-Harouni, Magdalini Paschali, Tobias Czempiel, Egon Burian, Marcus R. Makowski, Rickmer Braren, Nassir Navab, Thomas Wendler
Specifically, we introduce a multimodal similarity metric to build a population graph for clustering patients and an image-based end-to-end Graph Attention Network to process this graph and predict the COVID-19 patient outcomes: admission to ICU, need for ventilation and mortality.
1 code implementation • 26 Jul 2021 • Daniil Pakhomov, Sanchit Hira, Narayani Wagle, Kemar E. Green, Nassir Navab
Derived regions are consistent across different images and coincide with human-defined semantic classes on some datasets.
no code implementations • 9 Jun 2021 • Jakob Weiss, Nassir Navab
In this work, we introduce Deep Direct Volume Rendering (DeepDVR), a generalization of DVR that allows for the integration of deep neural networks into the DVR algorithm.
no code implementations • 9 Jun 2021 • Ege Özsoy, Evin Pınar Örnek, Ulrich Eck, Federico Tombari, Nassir Navab
We then use MSSG to introduce a dynamically generated graphical user interface tool for surgical procedure analysis which could be used for many applications including process optimization, OR design and automatic report generation.
no code implementations • 5 May 2021 • Maria Tirindelli, Christine Eilers, Walter Simson, Magdalini Paschali, Mohammad Farid Azampour, Nassir Navab
Medical Ultrasound (US), despite its wide use, is characterized by artifacts and operator dependency.
1 code implementation • 8 Apr 2021 • Mahsa Ghorbani, Mojtaba Bahrami, Anees Kazi, Mahdieh SoleymaniBaghshah, Hamid R. Rabiee, Nassir Navab
The soft pseudo-labels are then used to train a deep student network for disease prediction of unseen test data for which the graph modality is unavailable.
1 code implementation • 4 Apr 2021 • Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab
We present our findings using publicly available chest pathologies (CheXpert, NIH ChestX-ray8) and COVID-19 datasets (BrixIA, and COVID-19 chest X-ray segmentation dataset).
1 code implementation • 1 Apr 2021 • Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab
Neural networks have demonstrated remarkable performance in classification and regression tasks on chest X-rays.
2 code implementations • CVPR 2021 • Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab
Is critical input information encoded in specific sparse pathways within the neural network?
no code implementations • 29 Mar 2021 • Anees Kazi, Soroush Farghadani, Nassir Navab
The main novelty lies in the interpretable attention module (IAM), which directly operates on multi-modal features.
2 code implementations • CVPR 2021 • Shun-Cheng Wu, Johanna Wald, Keisuke Tateno, Nassir Navab, Federico Tombari
Scene graphs are a compact and explicit representation successfully used in a variety of 2D scene understanding tasks.
Ranked #1 on
3D Object Classification
on 3R-Scan
no code implementations • 19 Mar 2021 • Aadhithya Sankar, Matthias Keicher, Rami Eisawy, Abhijeet Parida, Franz Pfister, Seong Tae Kim, Nassir Navab
Disentangled representations can be useful in many downstream tasks, help to make deep learning models more interpretable, and allow for control over features of synthetically generated images that can be useful in training other models that require a large number of labelled or unlabelled data.
1 code implementation • 17 Mar 2021 • Ario Sadafi, Lucía María Moya Sans, Asya Makhro, Leonid Livshits, Nassir Navab, Anna Bogdanova, Shadi Albarqouni, Carsten Marr
Hereditary hemolytic anemias are genetic disorders that affect the shape and density of red blood cells.
1 code implementation • 16 Mar 2021 • Megha Kalia, Tajwar Abrar Aleef, Nassir Navab, Septimiu E. Salcudean
The method leverages the availability of labelled data in a different domain.
1 code implementation • 12 Mar 2021 • Seong Tae Kim, Leili Goli, Magdalini Paschali, Ashkan Khakzar, Matthias Keicher, Tobias Czempiel, Egon Burian, Rickmer Braren, Nassir Navab, Thomas Wendler
Chest computed tomography (CT) has played an essential diagnostic role in assessing patients with COVID-19 by showing disease-specific image features such as ground-glass opacity and consolidation.
1 code implementation • 12 Mar 2021 • Christina Bukas, Bailiang Jian, Luis F. Rodriguez Venegas, Francesca De Benetti, Sebastian Ruehling, Anjany Sekuboyina, Jens Gempt, Jan S. Kirschke, Marie Piraud, Johannes Oberreuter, Nassir Navab, Thomas Wendler
The framework uses the patient CT scan and the fractured vertebra label to build a virtual healthy spine using a high-level approach.
no code implementations • 10 Mar 2021 • Florian Kofler, Ivan Ezhov, Fabian Isensee, Fabian Balsiger, Christoph Berger, Maximilian Koerner, Beatrice Demiray, Julia Rackerseder, Johannes Paetzold, Hongwei Li, Suprosanna Shit, Richard McKinley, Marie Piraud, Spyridon Bakas, Claus Zimmer, Nassir Navab, Jan Kirschke, Benedikt Wiestler, Bjoern Menze
It is often unclear how to optimize abstract metrics, such as human expert perception, in convolutional neural network (CNN) training.
no code implementations • 5 Mar 2021 • Tobias Czempiel, Magdalini Paschali, Daniel Ostler, Seong Tae Kim, Benjamin Busam, Nassir Navab
In this paper we introduce OperA, a transformer-based model that accurately predicts surgical phases from long video sequences.
1 code implementation • 5 Mar 2021 • Tariq Bdair, Nassir Navab, Shadi Albarqouni
With few annotated data, FedPerl is on par with a state-of-the-art method in skin lesion classification in the standard setup while outperforming SSFLs and the baselines by 1. 8% and 15. 8%, respectively.
1 code implementation • 27 Feb 2021 • Mahsa Ghorbani, Anees Kazi, Mahdieh Soleymani Baghshah, Hamid R. Rabiee, Nassir Navab
This is accomplished by associating a graph-based neural network to each class, which is responsible for weighting the class samples and changing the importance of each sample for the classifier.
no code implementations • 1 Jan 2021 • Azade Farshad, Samin Hamidi, Nassir Navab
Data clustering is a well-known unsupervised learning approach.
no code implementations • 1 Jan 2021 • Ashkan Khakzar, Soroosh Baselizadeh, Saurabh Khanduja, Christian Rupprecht, Seong Tae Kim, Nassir Navab
Is critical input information encoded in specific sparse paths within the network?
1 code implementation • 20 Dec 2020 • Haowen Deng, Mai Bui, Nassir Navab, Leonidas Guibas, Slobodan Ilic, Tolga Birdal
For the former we contributed our own dataset composed of five indoor scenes where it is unavoidable to capture images corresponding to views that are hard to uniquely identify.
1 code implementation • 6 Dec 2020 • Roger D. Soberanis-Mukul, Nassir Navab, Shadi Albarqouni
In this context, we proposed a segmentation refinement method based on uncertainty analysis and graph convolutional networks.
no code implementations • 1 Dec 2020 • Ashkan Khakzar, Soroosh Baselizadeh, Nassir Navab
In this work, we empirically show that two approaches for handling the gradient information, namely positive aggregation, and positive propagation, break these methods.
no code implementations • 14 Nov 2020 • Matthias Grimm, Javier Esteban, Mathias Unberath, Nassir Navab
First, a neural network is trained once to detect a set of anatomical landmarks on simulated X-rays.
no code implementations • 10 Nov 2020 • Abinav Ravi Venkatakrishnan, Seong Tae Kim, Rami Eisawy, Franz Pfister, Nassir Navab
To address these issues, recently, unsupervised deep anomaly detection methods that train the model on large-sized normal scans and detect abnormal scans by calculating reconstruction error have been reported.
no code implementations • 30 Oct 2020 • Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya, Keno März, Toby Collins, Anand Malpani, Johannes Fallert, Hubertus Feussner, Stamatia Giannarou, Pietro Mascagni, Hirenkumar Nakawala, Adrian Park, Carla Pugh, Danail Stoyanov, Swaroop S. Vedula, Kevin Cleary, Gabor Fichtinger, Germain Forestier, Bernard Gibaud, Teodor Grantcharov, Makoto Hashizume, Doreen Heckmann-Nötzel, Hannes G. Kenngott, Ron Kikinis, Lars Mündermann, Nassir Navab, Sinan Onogur, Raphael Sznitman, Russell H. Taylor, Minu D. Tizabi, Martin Wagner, Gregory D. Hager, Thomas Neumuth, Nicolas Padoy, Justin Collins, Ines Gockel, Jan Goedeke, Daniel A. Hashimoto, Luc Joyeux, Kyle Lam, Daniel R. Leff, Amin Madani, Hani J. Marcus, Ozanan Meireles, Alexander Seitel, Dogu Teber, Frank Ückert, Beat P. Müller-Stich, Pierre Jannin, Stefanie Speidel
We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
no code implementations • 28 Oct 2020 • Stefano Gasperini, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Federico Tombari
Panoptic segmentation has recently unified semantic and instance segmentation, previously addressed separately, thus taking a step further towards creating more comprehensive and efficient perception systems.
2 code implementations • 26 Oct 2020 • Shun-Cheng Wu, Keisuke Tateno, Nassir Navab, Federico Tombari
We propose a framework that ameliorates this issue by performing scene reconstruction and semantic scene completion jointly in an incremental and real-time manner, based on an input sequence of depth maps.
1 code implementation • 18 Oct 2020 • Mahdi Saleh, Shervin Dehghani, Benjamin Busam, Nassir Navab, Federico Tombari
3D Point clouds are a rich source of information that enjoy growing popularity in the vision community.
1 code implementation • 15 Oct 2020 • Yanyan Li, Raza Yunus, Nikolas Brasch, Nassir Navab, Federico Tombari
This work proposes a RGB-D SLAM system specifically designed for structured environments and aimed at improved tracking and mapping accuracy by relying on geometric features that are extracted from the surrounding.
Robotics
no code implementations • 26 Sep 2020 • Benjamin Busam, Hyun Jun Jung, Nassir Navab
We change this p