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International Conference on New Interfaces for Musical Expression, NIME 2022

作者： Boettcher, Brady Malloch, Joseph Wang, Johnty Wanderley, Marcelo M. Input Devices and Musical Interaction Laboratory CIRMMT McGill University Canada Graphics and Experiential Media Laboratory Faculty of Computer Science Dalhousie University Canada

This paper presents Mapper4Live, a software plugin made for the popular digital audio workstation software Ableton Live. Mapper4Live exposes Ableton’s synthesis and effect parameters on the distributed libmapper signal mapping network, providing new opportunities for interaction between software and hardware synths, audio effects, and controllers. The plugin’s uses and relevance in research, music production and musical performance settings are explored, detailing the development journey and ideas for future work on the project. © 2022, International Conference on New Interfaces for Musical Expression. All rights reserved.

关键词： Mapping

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Preface

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Journal of computer Science & Technology 2019年第2期34卷 1-2页

作者： Shi-Min Hu Hongbo Fu Marcus Magnor Department of Computer Science and Technology Tsinghua University Beijing China School of Creative Media City University of Hong Kong Hong Kong Hong Kong Computer Graphics Laboratory Braunschweig University of Technology Braunschweig Germany

It is our great pleasure to announce the publication of this special section in Journal of computer Science and Technology (JCST),Advances in computer Science and Technology --Current Advances in the NSFC Joint Resear... 详细信息

关键词： publication computer Science and Technology Chinese Scholars

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Preface

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Journal of computer Science & Technology 2019年第3期34卷 507-508页

作者： Shi-Min Hu Hongbo Fu Marcus Magnor Department of Computer Science and Technology Tsinghua University.Beijing School of Creative Media City University of Hong KongHong Kong Computei Graphics Laboratory Braunschweig University of TechnologyBraunschweig

The Computational Visual media (CVM) conference series is intended to provide a major international forum for exchanging novel research ideas and significant computational methods that either underpin or apply visual media. The primary goal is to promote cross-disciplinary research to amalgamate aspects of computer graphics, computer vision, machine learning, image and video processing, visualization and geometric computing. The main topics of interest to CVM include classification, composition, retrieval, synthesis, cognition and understanding of visual media (e.g., images, videos, 3D geometry).

关键词： Preface Computational Visual media(CVM) primary goal

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Robot-assisted mechanical scanning and co-registration of Magnetic Resonance Imaging and light-induced fluorescence

Robot-assisted mechanical scanning and co-registration of Ma...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Ahmet E. Sonmez William M. Spees Alpay Özcan Zhigang Deng Andrew G. Webb Nikolaos V. Tsekos Medical Robotics Laboratory Department of Computer Science at University of Houston Houston TX USA Biomedical Magnetic Resonance Laboratory Washington University St. Louis MO USA Arlington Innovation Center Virginia Polytechnic Institute and State University Arlington VA USA Computer Graphics & Interactive Media Lab and Computer Science Department at University of Houston Houston TX USA Department of Radiology Leiden University Medical Center Leiden Netherlands

Robotic manipulators offer some unique opportunities to address research and clinical needs. Among those is the potential use of a robotic manipulator to mechanically scan the tissue of interest with biosensors that have limited tissue penetration. In such cases, the robot can serve a dual role. First, it can perform spatial scanning with the biosensor along a pre-selected path inside the tissue. Second, it can function as the mechanical link to spatially co-register the data collected with the biosensor and the images of a guidance modality. Herein, we describe a robotic system to mechanically scan with a light-induced fluorescence (LIF) sensor and co-register LIF data to the guiding modality of MRI. Specifically, a custom-built MR-compatible endoscope was integrated onto the end-effector of an MR-compatible manipulator to collect MRI-guided LIF 1D scans. A miniature radiofrequency (RF) coil attached onto the end-effector was used as a fiducial marker for co-registering LIF and MRI. This mechanically scanning system was investigated on two compartment phantoms, each with different optical agents. Those studies demonstrated “robot-assisted” multi-modality co-registration, i.e. the spatial distribution of the LIF signals matched with the MR guiding images. The system can incorporate additional sensors for collecting complementary biochemical information.

关键词： Optical fibers Manipulators Robot sensing systems Probes Coils

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An approach for robot-assisted biosensing: Demonstration with MRI-guided MR spectroscopy

An approach for robot-assisted biosensing: Demonstration wit...

引用

10th IEEE International Workshop on Biomedical Engineering, BioEng 2011

作者： Sonmez, Ahmet E. Hedayati, Yousef Webb, Andrew G. Deng, Zhigang Navkar, Nikhil Tsekos, Nikolaos V. Medical Robotics Laboratory Department of Computer Science University of Houston Houston TX 77204 United States Computer Graphics and Interactive Media Laboratory Department of Computer Science University of Houston Houston TX 77204 United States Department of Radiology Leiden University Medical Centre Leiden Netherlands

ISBN: (纸本)9781457705526

Emerging and established methods, such as optical imaging and MR spectroscopy (MRS), offer new opportunities for in situ biosensing. The limited tissue penetration of these modalities can be addressed by locally placing the sensor via minimally invasive trans-needle or trans-catheter access. This work introduces a generic system that mechanically scans an area of interest with a sensor, capable of generating 1D scans while registering them to a guiding modality. computer simulations illustrate the operation of this approach for a miniature RF coil as the mechanically scanned biosensor. Experimental studies demonstrated the approach on phantoms, using MRI as the guiding modality, and an MR-compatible manipulator, which carried a miniature RF coil, was used to scan and collect MRS and generated 1D MRS scans co-registered to the guiding MRI. © 2011 IEEE.

关键词： Robotics

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Partial generalized correlation for hyperspectral data

Partial generalized correlation for hyperspectral data

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： Marc Strickert Björn Labitzke Volker Blanz Institute of Vision and Graphics University of Siegen Germany Computer Graphics Group University of Siegen Germany Media Systems Laboratory University of Siegen Germany

A variational approach is proposed for the unsupervised assessment of attribute variability of high-dimensional data given a differentiable similarity measure. The key question addressed is how much each data attribute contributes to an optimum transformation of vectors for reaching maximum similarity. This question is formalized and solved in a mathematically rigorous optimization framework for each data pair of interest. Trivially, for the Euclidean metric minimization to zero distance induces highest vector similarity, but in case of the linear Pearson correlation measure the highest similarity of one is desired. During optimization the not necessarily symmetric trajectories between two vectors are recorded and analyzed in terms of attribute changes and line integral. The proposed formalism allows to assess partial covariance and correlation characteristics of data attributes for vectors being compared by any differentiable similarity measure. Its potential for generating alternative and localized views such as for contrast enhancement is demonstrated for hyperspectral images from the remote sensing domain.

关键词： Correlation Euclidean distance Covariance matrix Vectors Equations Mathematical model Geologic measurements

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Extracting geometric features of aortic valve annulus motion from dynamic MRI for guiding interventions

Extracting geometric features of aortic valve annulus motion...

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IEEE International Symposium on Biomedical Imaging

作者： Nikhil V. Navkar Erol Yeniaras Dipan J. Shah Nikolaos V. Tsekos Zhigang Deng Medical Robotics Laboratory Department of Computer Science University of Houston Houston TX USA Methodist DeBakey Heart & Vascular Center Methodist Hospital Houston TX USA Computer Graphics and Interactive Media Laboratory Department of Computer Science University of Houston Houston TX USA

ISBN: (纸本)9781424441273

Transcatheter aortic valve implant (TAVI) has emerged as a prominent approach for treating aortic stenosis. Success of such implants depends upon the accurate assessment of the geometric features such as the diameter, center and orientation of the aortic valve annulus (AVA). In this paper, we present a method for extracting these geometric features from magnetic resonance images (MRI). The method is based on finding an optimal fit for a circular ring mimicking AVA in the aortic root. Moreover, the presented approach provides dynamic tracking of the AVA in CINE MR images. This approach can be used for preoperative planning of prosthetic valve implantation, as well as for the emerging MRI guided manual, or with robot-assisted, annuloplasty.

关键词： Valves Magnetic resonance imaging Robots Heart Tracking Prosthetics

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Magnetic Resonance Based Control of a Robotic Manipulator for Interventions in the Beating Heart

Magnetic Resonance Based Control of a Robotic Manipulator fo...

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2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

作者： Nikolaos V. Tsekos Johann Lamaury Erol Yeniaras Zhigang Deng Nikhil V. Navkar Dipan J. Shah Karen Chin Medical Robotics Laboratory Department of Computer Science at University of HoustonHoustonTX 77204 Computer Graphics and Interactive Media Lab. Department of Computer ScienceUniversity of HoustonHo Methodist DeBakey Heart & Vascular Center HoustonTX 77030 USA

As a part of an ongoing project, in this paper we introduce the first version of a system which has a novel methodology for Cine (as in cinema) MRI based control of a cardiac robot for beating heart surgeries. The system uses the preoperative planning approach that we developed earlier, and integrates it to the intraoperative algorithms for controlling a robot and tracking some specific landmarks of a highly dynamical surgical field. In particular, our late studies presented herein aim to demonstrate the feasibility of integrating appropriate computational tools to achieve the volumetric image guidance for minimally invasive surgeries in the beating heart. We conceive of the system as practicable for in vitro experiments upon the completion of the first physical prototype, which may pave the way for expansion of the approach for other complex surgeries as well.

关键词： Heart Magnetic resonance imaging Manipulators Surgery Robot kinematics Valves

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A Novel Visualization System for Expressive Facial Motion Data Exploration

A Novel Visualization System for Expressive Facial Motion Da...

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Pacific (formerly Asia-Pacific APVIS) Visualization Symposium

作者： Tanasai Sucontphunt Xiaoru Yuan Qing Li Zhigang Deng Computer Graphics and Interactive Media Laboratory Department of CS University of Houston USA Laboratory of Machine Intelligence Peking University China

Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensionality of facial motion data make its exploration and processing challenging. In this paper, we propose a novel visualization system for expressive facial motion data exploration. Based on Principal Component Analysis (PCA) dimensionality reduction on anatomical facial sub regions, high dimensional facial motion data is mapped to 3D spaces. We further rendered it as colored 3D trajectories and color represents different emotion. We design an intuitive interface to allow users effectively explore and analyze high dimensional facial motion spaces. The applications of our visualization system on novel facial motion synthesis and emotion recognition are demonstrated.

关键词： Data visualization computer graphics Principal component analysis Motion analysis Human computer interaction Application software Emotion recognition Space exploration Mouth Laboratories

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