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GPU-Accelerated Compartmental Modeling Analysis of DCE-MRI Data from Glioblastoma Patients Treated with Bevacizumab

Yu-Han H. Hsu, Ziyin Huang, Gregory Z. Ferl, Chee M. Ng, Mara Cercignani
2015 PLoS ONE  
The method developed in this study could be of significant utility in reducing the computational times required to assess tumor physiology from dynamic contrast-enhanced magnetic resonance imaging data  ...  Using this approach, we performed the analysis of dynamic contrast-enhanced magnetic resonance imaging data from bevacizumab-treated glioblastoma patients in less than one minute per slice without losing  ...  Introduction Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a noninvasive quantitative tool that allows analysis of tumor vascular characteristics that might change in response to drug  ... 
doi:10.1371/journal.pone.0118421 pmid:25786263 pmcid:PMC4364976 fatcat:aq3elcm2tbhmfmhlcs4qz6w52i

FPGA-based acceleration of MRI registration: an enabling technique for improving MRI-guided cardiac therapy

Ka-Wai Kwok, Gary CT Chow, Thomas CP Chau, Yue Chen, Shelley H Zhang, Wayne Luk, Ehud J Schmidt, Zion T Tse
2014 Journal of Cardiovascular Magnetic Resonance  
processing unit (GPU)-based Demons reported in [3] and [4] .  ...  Journal of Cardiovascular Magnetic Resonance 2014, 16(Suppl 1):W11 © 2014Kwok et al.; licensee BioMed Central Ltd.  ...  Authors' details 1 College of Engineering, University of Georgia, Athens, Georgia, USA. 2 Computing, Imperial College London, London, UK. 3 Radiology, Brigham and Women's Hospital, Harvard, Boston  ... 
doi:10.1186/1532-429x-16-s1-w11 pmcid:PMC4044607 fatcat:hznqto5xdrhptjcxoom6xxlbsq

IEEE Access Special Section Editorial: Advanced Signal Processing Methods In Medical Imaging

Yu-Dong Zhang, Yin Zhang, Zhengchao Dong, Ti-Fei Yuan, Liangxiu Han, Ming Yang, Carlo Cattani, Huimin Lu
2018 IEEE Access  
), and magnetic resonance imaging (MRI)/functional MRI (fMRI).  ...  Many medical imaging techniques are widely used to produce images, such as computer tomography (CT), ultrasound (US), positron emission tomography (PET), single photon emission computed tomography (SPECT  ...  Factors that may influence the model performance, such as model width, depth, and dropout, were also examined. (11) In the article ''GPU-accelerated features extraction from magnetic resonance images,'  ... 
doi:10.1109/access.2018.2875308 fatcat:v4uxwxsvmnhfpgezgt2wzmxd2u

Vessel segmentation in MRI using a variational image subtraction approach

Ayşe Nurdan SARAN, Fatih NAR, Murat SARAN
2014 Turkish Journal of Electrical Engineering and Computer Sciences  
imaging (MRI) as prior information within the vessel segmentation of magnetic resonance angiography (MRA) or magnetic resonance venography (MRV) images.  ...  Although various approaches have been proposed to segment vessel structures from 3-dimensional medical images, to the best of our knowledge, there has been no known technique that uses magnetic resonance  ...  Acknowledgment The authors would like to thank Prof Dr Kıvılcım Gücüyener for her valuable time in evaluating our results; Asst Prof Dr Didem Gökçay for providing the clinical MRI, MRA, and MRV images;  ... 
doi:10.3906/elk-1206-18 fatcat:rhpldm2t3bfwfl2isic3gwdnka

Memory Efficient Model Based Deep Learning Reconstructions for High Spatial Resolution 3D Non-Cartesian Acquisitions [article]

Zachary Miller, Ali Pirasteh, Kevin M. Johnson
2022 arXiv   pre-print
Objective: Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Cartesian MRI acquisitions due to extreme GPU memory demand (>250 GB using traditional backpropagation  ...  This algorithm was used to train a MBDL architecture to reconstruct highly undersampled, 1.25mm isotropic, pulmonary magnetic resonance angiography volumes with matrix sizes varying from 300-450 x 200-  ...  Theory 2.1 Model Based DL Consider the problem of reconstructing an image from under-sampled data 𝑦.  ... 
arXiv:2204.13862v2 fatcat:widvl3uknjcvdfuc76iwaa2ai4

Automated computer-assisted detection system for cerebral aneurysms in time-of-flight magnetic resonance angiography using fully convolutional network

Geng Chen, Xia Wei, Huang Lei, Yang Liqin, Li Yuxin, Dai Yakang, Geng Daoying
2020 BioMedical Engineering OnLine  
The presented study developed a computer-assisted detection system for cerebral aneurysms in the contrast-unenhanced time-of-flight magnetic resonance angiography image.  ...  As fully convolutional network could classify the image pixel-wise, its three-dimensional implementation is highly suitable for the classification of the vascular structure.  ...  TOF-MRA: Time-of-flight magnetic resonance angiography; DSA: Digital subtraction angiography; CNN: Convolutional neural networks; FCN: Fully convolutional network; CAD: Computer-assisted detection; CPU  ... 
doi:10.1186/s12938-020-00770-7 pmid:32471439 fatcat:rg6awts3czdbbk7dbouzu3icyy

GPU Accelerated Non-rigid Registration for the Evaluation of Cardiac Function [chapter]

Bo Li, Alistair A. Young, Brett R. Cowan
2008 Lecture Notes in Computer Science  
We present a method for the fast and efficient tracking of motion in cardiac magnetic resonance (CMR) cines.  ...  In conclusion, GPU accelerated Levenberg-Marquardt non-linear optimization enables fast and accurate tracking of cardiac motion in CMR images.  ...  Introduction Cardiac magnetic resonance (CMR) imaging provides an abundant source of detailed, quantitative data for the accurate evaluation of the structure and function of the heart [1] .  ... 
doi:10.1007/978-3-540-85990-1_106 fatcat:23mn6eu4jbhwhok3rzxsy25ogy

Visual computing for medical diagnosis and treatment

Jan Klein, Ola Friman, Markus Hadwiger, Bernhard Preim, Felix Ritter, Anna Vilanova, Gabriel Zachmann, Dirk Bartz
2009 Computers & graphics  
This state-of-the-art report summarizes visual computing algorithms for medical diagnosis and treatment.  ...  vessel structures.  ...  Magnetic resonance imaging: Magnetic resonance imaging (MRI) scanners, which use static and time-varying magnetic fields for generating 3D volumes, also evolve at a fast pace toward stronger magnetic fields  ... 
doi:10.1016/j.cag.2009.04.006 fatcat:bckkhjox7fcq7kf7bi7ylyvbyq

An improved parallel fuzzy connected image segmentation method based on CUDA

Liansheng Wang, Dong Li, Shaohui Huang
2016 BioMedical Engineering OnLine  
In recent years, many methods of vascular segmentation have been proposed. For example, Gooya et al. [1] proposed a level-set based geometric regularization method for vascular segmentation.  ...  Vascular structure is a reliable mark to localize a tumor, especially in liver surgery.  ...  CUDA executing model The basic strategy of CUDA is for all computing threads to run concurrently in logic.  ... 
doi:10.1186/s12938-016-0165-2 pmid:27175785 pmcid:PMC4866034 fatcat:npwd2uwv5nbuvptx5tslqyww2m

Methodological Challenges of Deep Learning in Optical Coherence Tomography for Retinal Diseases: A Review

Ryan T. Yanagihara, Cecilia S. Lee, Daniel Shu Wei Ting, Aaron Y. Lee
2020 Translational Vision Science & Technology  
Artificial intelligence (AI)-based automated classification and segmentation of optical coherence tomography (OCT) features have become increasingly popular.  ...  Several recent studies have reported high diagnostic performances of AI models; however, significant methodological challenges still exist in applying these models in real-world clinical practice.  ...  However, 3-dimensional (3D) OCT volumes more closely resemble magnetic resonance images and CT scans.  ... 
doi:10.1167/tvst.9.2.11 pmid:32704417 pmcid:PMC7347025 fatcat:ty4lldia2vbtdlhx22gl3radxy

Forensic-Case Analysis: From 3D Imaging to Interactive Visualization

Martin Urschler, Alexander Bornik, Eva Scheurer, Kathrin Yen, Horst Bischof, Dieter Schmalstieg
2012 IEEE Computer Graphics and Applications  
such as computed tomography (CT) and magnetic resonance imaging (MRI). 2, 3 The obvious benefit of these modalities is the possibility of imaging a whole 3D anatomy from the inside of the subject.  ...  We address this high-performance requirement by leveraging recent improvements in parallel processing on the An interactive framework prepares raw computed tomography and magnetic resonance imaging scans  ...  A T1 weighting in a spin-echo sequence 8 acquired the first volume, which provided an overview of the left hip and upper thigh (see Figure 5a ). However, this image doesn't show much contrast  ... 
doi:10.1109/mcg.2012.75 pmid:24806635 fatcat:zwrgq4rk6jhzna5aepghonxdiq

A statistical 3D model of the human cortical vasculature to compute the hemodynamic fingerprint of the BOLD fMRI signal [article]

Mario Gilberto Baez-Yanez, Jeroen C.W. Siero, Natalia Petridou
2020 bioRxiv   pre-print
The proposed model considers also the biophysical interactions and the intrinsic magnetic properties of the nearby tissue in order to compute a dynamic BOLD fMRI signal response.  ...  Using this model, we simulated hemodynamic changes triggered by a neuronal activation and local magnetic field disturbances created by the vascular topology and the blood oxygenation changes.  ...  Functional brain mapping by blood oxygenation level-dependent 882 contrast magnetic resonance imaging. A comparison of signal characteristics 883 with a biophysical model.  ... 
doi:10.1101/2020.10.05.326512 fatcat:mhtsm7do35h4bibvnupd7j3bxa

Augmented Reality Approaches in Intelligent Health Technologies and Brain Lesion Detection [chapter]

Tomasz Hachaj, Marek R. Ogiela
2011 Lecture Notes in Computer Science  
discrete gradient computation schemas taking into account image quality and processing speed on two VR algorithms: volume ray casting and texture based visualization with view aligned slices.  ...  In this paper authors present their new proposition of system for cognitive analysis of dynamic computer tomography perfusion maps (dpCT).  ...  This work has been supported by the Ministry of Science and Higher Education, Republic of Poland, under project number N N516 511939.  ... 
doi:10.1007/978-3-642-23300-5_11 fatcat:nns64xl64ba2hgagt3oirh5zmi

Practical parallel imaging compressed sensing MRI: Summary of two years of experience in accelerating body MRI of pediatric patients

SS Vasanawala, MJ Murphy, MT Alley, P Lai, K Keutzer, JM Pauly, M Lustig
2011 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
For the last two years 1 , we have been experimenting with applying compressed sensing parallel imaging for body imaging of pediatric patients.  ...  Clinical results showing higher quality reconstruction and better diagnostic confidence than parallel imaging alone at accelerations on the order of number of coils.  ...  ACKNOWLEDGEMENTS The authors are grateful for the support of GE Healthcare, the John and Tashia Morgridge Foundation, and the NIH (R01-EB009690, RR09794-15).  ... 
doi:10.1109/isbi.2011.5872579 pmid:24443670 pmcid:PMC3892425 dblp:conf/isbi/VasanawalaMALKPL11 fatcat:avg6zmplrzfzfgjft7trzwlhza

Photoacoustic digital brain: numerical modelling and image reconstruction via deep learning [article]

Tengbo Lyu, Jiadong Zhang, Zijian Gao, Changchun Yang, Feng Gao, Fei Gao
2021 arXiv   pre-print
In this work, we use 10 magnetic resonance angiography (MRA) human brain volumes, and manually segment them to obtain the 2D human brain numerical phantoms for PAT.  ...  Photoacoustic tomography (PAT) is a newly developed medical imaging modality, which combines the advantages of pure optical imaging and ultrasound imaging, owning both high optical contrast and deep penetration  ...  They are magnetic resonance angiography (MRA) [1] , computed tomography angiography (CTA) [2] and digital subtraction angiography (DSA) [3] , which are illustrated in Though the above three methods  ... 
arXiv:2109.09127v1 fatcat:b6ei47cftjecfgx5o76fyrefxq
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