Filters








367 Hits in 5.6 sec

Portable Ultrasound Research System for Use in Automated Bladder Monitoring with Machine-Learning-Based Segmentation

Marc Fournelle, Tobias Grün, Daniel Speicher, Steffen Weber, Mehmet Yilmaz, Dominik Schoeb, Arkadiusz Miernik, Gerd Reis, Steffen Tretbar, Holger Hewener
2021 Sensors  
We developed a new mobile ultrasound device for long-term and automated bladder monitoring without user interaction consisting of 32 transmit and receive electronics as well as a 32-element phased array  ...  Furthermore, ML-based segmentation algorithms were developed and assessed with respect to their ability to reliably segment human bladders with different filling levels.  ...  In particular, machine-learning based approaches have been shown to have tremendous potential for automated segmentation of ultrasound data [10] , and have been reported in particular for breast imaging  ... 
doi:10.3390/s21196481 pmid:34640807 fatcat:m4r4eokhibgsljfuznebaqusne

Performance of an automated ultrasound device in identifying and tracing the heart in porcine cardiac arrest

Paul Olszynski, Rory A. Marshall, T. Dylan Olver, Trevor Oleniuk, Cameron Auser, Tracy Wilson, Paul Atkinson, Rob Woods
2022 The Ultrasound Journal  
Conclusion An automated ultrasound device (bladder scanner) reliably traced porcine hearts during cardiac arrest.  ...  In this proof-of-concept porcine study, we sought to describe the performance of an automated ultrasound device in correctly identifying and tracing the borders of the heart in three distinct states: pre-arrest  ...  All animal procedures were conducted in accordance with the National Institutes of Health policy on the use of animals in research and approved by the Research Ethics Board Animal Use and Care Committee  ... 
doi:10.1186/s13089-021-00251-5 pmid:34978635 pmcid:PMC8724362 fatcat:rr2nyrpvpvgtda2z5w4cxpibbm

Medical Deep Learning – A systematic Meta-Review [article]

Jan Egger, Christina Gsaxner, Antonio Pepe, Jianning Li
2020 arXiv   pre-print
With the collection of large quantities of patient records and data, and a trend towards personalized treatments, there is a great need for automated and reliable processing and analysis of health information  ...  This trend resulted in new, massive research efforts during the last years.  ...  Ultrasound -Ultrasound (US) is the imaging modality most commonly used in the clinical routine due to it is nonionizing, low-cost, and portable characteristics, whileproviding real-time images.  ... 
arXiv:2010.14881v4 fatcat:56nrzawncnaopcpuzlzac5ceoy

Chromosome Analysis by Image Processing in a Computerized Environment. Clinical Applications

P. MALET, M. BENKHALIFA, B. PERISSEL, A. GENEIX, B. LE CORVAISIER
1992 Journal of Radiation Research  
A specific program allows quantification of chromosome labelling with radioactive probes. Exchanges of digitized karyotypes are feasible with labs using automated karyo typing machines.  ...  Attempts for an accurate automated chromosome classification using a neural network have led to partial results.  ...  The possible user of a karyotyping system should keep in mind the following questions: are performances data based on routine clinical use?  ... 
doi:10.1269/jrr.33.supplement_171 pmid:1507168 fatcat:w5223nw4iree3juiqdtxr324aq

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson's Disease Affected by COVID-19: A Narrative Review

Jasjit S. Suri, Mahesh A. Maindarkar, Sudip Paul, Puneet Ahluwalia, Mrinalini Bhagawati, Luca Saba, Gavino Faa, Sanjay Saxena, Inder M. Singh, Paramjit S. Chadha, Monika Turk, Amer Johri (+31 others)
2022 Diagnostics  
Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID-19 framework.  ...  Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients.  ...  The AI-based solution for CVD/stroke risk assessment of PD patients in COVID-19 framework is the first to introduce the use of a machine learning system for CVD/stroke risk assessment and is easily amendable  ... 
doi:10.3390/diagnostics12071543 pmid:35885449 pmcid:PMC9324237 fatcat:rrhkppghkfayfbnlsyx7hq7koa

Review of optical coherence tomography in oncology

Jianfeng Wang, Yang Xu, Stephen A. Boppart
2017 Journal of Biomedical Optics  
for OCT technologies, with particular emphasis on their applications in oncology.  ...  OCT imaging has been used to image a broad spectrum of malignancies, including those arising in the breast, brain, bladder, the gastrointestinal, respiratory, and reproductive tracts, the skin, and oral  ...  Acknowledgments We wish to thank all of our colleagues, researchers, and students who have joined us in the pursuit to fundamentally understand the complex process of carcinogenesis, as well as to improve  ... 
doi:10.1117/1.jbo.22.12.121711 pmid:29274145 pmcid:PMC5741100 fatcat:khdymmcwdngc3fnqfdrheuvuwq

Artificial Intelligence: A Review of Progress and Prospects in Medicine and Healthcare

Saurav Mishra
2022 Journal of Electronics Electromedical Engineering and Medical Informatics  
The paper also discusses about the implementation opportunities various AI technologies like Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision provide  ...  Research and Innovations are happening in almost every field of healthcare and hospital workflows with the target of making healthcare processes more efficient & accessible, increase the overall state  ...  Various different researchers have applied CNN based learnings for classifying coding, and non-coding based variants.  ... 
doi:10.35882/jeeemi.v4i1.1 fatcat:j2zcn22rl5f77nmy7rmbpr76ma

Surgical Robotics and Computer-Integrated Interventional Medicine

Russell H. Taylor, Nabil Simaan, Arianna Menciassi, Guang-Zhong Yang
2022 Proceedings of the IEEE  
Robotic systems  ...  For example, a recent study [5] found that over 15% of all general surgery procedures in 2020 were performed robotically, compared to only 1.8% in 2012.  ...  Robotic joint replacement with the "Robodoc" system [9], [19], [20]. The system combined CT-based planning with autonomous robotic machining of bone for cementless hip and knee implants.  ... 
doi:10.1109/jproc.2022.3177693 fatcat:4bipw52t7bdy3hejycmrgnlqra

2020 Index IEEE Transactions on Instrumentation and Measurement Vol. 69

2020 IEEE Transactions on Instrumentation and Measurement  
Converter Using All-Digital Nested Delay-Locked Loops With 50-ps Resolution and High Throughput for LiDAR TIM Nov. 2020 9262-9271 Helsen, J., see Huchel, L., TIM July 2020 4145-4153 Hemavathi, N.,  ...  of Rounds; TIM June 2020 3739-3749 Hendeby, G., see Kasebzadeh, P., TIM Aug. 2020 5862-5874 Heng, Y., see Xue, M., TIM June 2020 3812-3817 Henry, M.P., The Prism: Recursive FIR Signal Processing for  ...  ., +, TIM Oct. 2020 7411-7421 Laser Cladding Quality Monitoring Using Coaxial Image Based on Machine Learning.  ... 
doi:10.1109/tim.2020.3042348 fatcat:a5f4fsqs45fbbetre6zwsg3dly

iApp: An Autonomous Inspection, Auscultation, Percussion, and Palpation Platform

Semin Ryu, Seung-Chan Kim, Dong-Ok Won, Chang Seok Bang, Jeong-Hwan Koh, In cheol Jeong
2022 Frontiers in Physiology  
A deep multi-modal learning model, yielding a single prediction from multi-modal inputs, was designed for learning distinctive features in eight abdominal divisions.  ...  The results demonstrate that the iApp system can successfully categorize abdominal divisions, with the test accuracy of 89.46%.  ...  SR, S-CK, IJ, and D-OW conceived and designed the deep multi-modal learning architecture.  ... 
doi:10.3389/fphys.2022.825612 pmid:35237180 pmcid:PMC8883036 fatcat:gxewbws5vzbmnansvrkklszaqa

Multiple Kernel-Learning Approach for Medical Image Analysis [chapter]

Nisar Wani, Khalid Raza
2018 Soft Computing Based Medical Image Analysis  
about nature of medical images, image features and basics in machine learning and kernel methods, we present the application of multiple kernel learning algorithms for medical image analysis. keywords  ...  learning tools, particularly kernel based algorithms seem to be an obvious choice to process and analyze this high dimensional and heterogeneous data.In this chapter, after presenting a breif description  ...  As computer hardware became cheaper and sophisticated classification algorithms emerged in the domains of machine learning and artificial intelligence, the research focus on automated image analysis of  ... 
doi:10.1016/b978-0-12-813087-2.00002-6 fatcat:isyoold725bt3n4bvly4qznvvq

Three-dimensional and Four-dimensional Ultrasound: Techniques and Abdominal Applications

Se Hyung Kim, Byung Ihn Choi
2007 Journal of Medical Ultrasound  
Three-dimensional (3D) or four-dimensional (4D) ultrasound (US) has been developed and researched in two major ways.  ...  Therefore, radiologists or sonographers should be ready to accept the paradigm shift of viewing 3D images on a computer monitor rather than viewing 2D US images on the ultrasound machine, and they must  ...  Therefore, radiologists or sonographers should be ready to accept the paradigm shift of viewing 3D images on a computer monitor rather than viewing 2D US images on the ultrasound machine and must be familiar  ... 
doi:10.1016/s0929-6441(08)60040-5 fatcat:2h5faowaprhh7idm4pimlkcega

Multiple Kernel Learning Approach For Medical Image Analysis [article]

Nisar Wani, Khalid Raza
2017 bioRxiv   pre-print
In this chapter, after presenting a brief description about nature of medical images, image features and basics in machine learning and kernel methods, we present the application of multiple kernel learning  ...  Machine learning tools, particularly kernel based algorithms seem to be an obvious choice to process and analyze this high dimensional and heterogeneous data.  ...  As computer hardware became cheaper and sophisticated classification algorithms emerged in the domains of machine learning and artificial intelligence, the research focus on automated image analysis of  ... 
doi:10.1101/121509 fatcat:dfgacanmvrghdhrcmhrcew7aqe

Table of Contents

2020 2020 IEEE International Ultrasonics Symposium (IUS)  
07:30 AM 2358: Highly Doped AlScN XBAW Resonators with 15.7% k2 eff for 5G RF Filter Applications  ...  Research, Netherlands 04:55 AM 2423: In Vivo Monitoring of Corneal Viscoelasticity in Rabbits with Collagen Cross-Linking Treatment Using Ultrasound Elastography Linfeng Zhao, Yuxi Zhang, Xin Chen  ...  PM -Machine Learning Applications II Session Chair(s): James Wiskin (QT Ultrasound Inc.)  ... 
doi:10.1109/ius46767.2020.9251713 fatcat:nzjz2g5cgrbs7ikrkqajtvb24a

A multiparametric magnetic resonance imaging-based virtual reality surgical navigation tool for robotic-assisted radical prostatectomy

Sherif Mehralivand, Department of Urology and Pediatric Urology, University Medical Center, Mainz, Germany, Abhishek Kolagunda, Kai Hammerich, Vikram Sabarwal, Stephanie Harmon, Thomas Sanford, Samuel Gold, Graham Hale, Vladimir Valera Romero, Jonathan Bloom, Maria J. Merino (+22 others)
2019 Turkish journal of urology  
MRI using an in-house segmentation software.  ...  All participants found the system useful, especially for tumors with locally aggressive growth patterns.  ...  Acknowledgements: This project was funded in whole or in part with federal funds from the National Cancer Institute, National Institutes of Health, under Contract No. HHSN261200800001E.  ... 
doi:10.5152/tud.2019.19133 pmid:31509508 pmcid:PMC6739087 fatcat:stkuikpe5jdmfokr2ggyba4uwy
« Previous Showing results 1 — 15 out of 367 results