Search Results - "Magnetic resonance imaging"

DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution by Wang, Shanshan, Cheng, Huitao, Ying, Leslie, Xiao, Taohui, Ke, Ziwen, Zheng, Hairong, Liang, Dong

“…This paper proposes a multi-channel image reconstruction method, named DeepcomplexMRI, to accelerate parallel MR imaging with residual complex convolutional…”
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DeepHarmony: A deep learning approach to contrast harmonization across scanner changes by Dewey, Blake E., Zhao, Can, Reinhold, Jacob C., Carass, Aaron, Fitzgerald, Kathryn C., Sotirchos, Elias S., Saidha, Shiv, Oh, Jiwon, Pham, Dzung L., Calabresi, Peter A., van Zijl, Peter C.M., Prince, Jerry L.

“…Magnetic resonance imaging (MRI) is a flexible medical imaging modality that often lacks reproducibility between protocols and scanners. It has been shown that…”
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Machine learning in resting-state fMRI analysis by Khosla, Meenakshi, Jamison, Keith, Ngo, Gia H., Kuceyeski, Amy, Sabuncu, Mert R.

“…Machine learning techniques have gained prominence for the analysis of resting-state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an…”
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3D Slicer as an image computing platform for the Quantitative Imaging Network by Fedorov, Andriy, Beichel, Reinhard, Kalpathy-Cramer, Jayashree, Finet, Julien, Fillion-Robin, Jean-Christophe, Pujol, Sonia, Bauer, Christian, Jennings, Dominique, Fennessy, Fiona, Sonka, Milan, Buatti, John, Aylward, Stephen, Miller, James V, Pieper, Steve, Kikinis, Ron

“…Abstract Quantitative analysis has tremendous but mostly unrealized potential in healthcare to support objective and accurate interpretation of the clinical…”
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A review on brain tumor segmentation of MRI images by Wadhwa, Anjali, Bhardwaj, Anuj, Singh Verma, Vivek

“…The process of segmenting tumor from MRI image of a brain is one of the highly focused areas in the community of medical science as MRI is noninvasive imaging…”
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A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification by Zhang, Jie, Zheng, Bowen, Gao, Ang, Feng, Xin, Liang, Dong, Long, Xiaojing

“…Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In recent years, machine learning methods have been widely used on…”
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Radiomics: the process and the challenges by Kumar, Virendra, Gu, Yuhua, Basu, Satrajit, Berglund, Anders, Eschrich, Steven A, Schabath, Matthew B, Forster, Kenneth, Aerts, Hugo J.W.L, Dekker, Andre, Fenstermacher, David, Goldgof, Dmitry B, Hall, Lawrence O, Lambin, Philippe, Balagurunathan, Yoganand, Gatenby, Robert A, Gillies, Robert J

“…Abstract “Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative imaging features with high throughput from medical images…”
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A review on brain tumor diagnosis from MRI images: Practical implications, key achievements, and lessons learned by Abd-Ellah, Mahmoud Khaled, Awad, Ali Ismail, Khalaf, Ashraf A.M., Hamed, Hesham F.A.

“…The successful early diagnosis of brain tumors plays a major role in improving the treatment outcomes and thus improving patient survival. Manually evaluating…”
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Artificial intelligence in medical imaging by Gore, John C.

“…The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how…”
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Synthesized b0 for diffusion distortion correction (Synb0-DisCo) by Schilling, Kurt G., Blaber, Justin, Huo, Yuankai, Newton, Allen, Hansen, Colin, Nath, Vishwesh, Shafer, Andrea T., Williams, Owen, Resnick, Susan M., Rogers, Baxter, Anderson, Adam W., Landman, Bennett A.

“…Diffusion magnetic resonance images typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may affect the…”
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Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI by Mazurowski, Maciej A., Buda, Mateusz, Saha, Ashirbani, Bashir, Mustafa R.

“…Deep learning is a branch of artificial intelligence where networks of simple interconnected units are used to extract patterns from data in order to solve…”
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Quantitative susceptibility mapping: current status and future directions by Haacke, E. Mark, Liu, Saifeng, Buch, Sagar, Zheng, Weili, Wu, Dongmei, Ye, Yongquan

“…Abstract Quantitative susceptibility mapping (QSM) is a new technique for quantifying magnetic susceptibility. It has already found various applications in…”
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What are normal relaxation times of tissues at 3 T? by Bojorquez, Jorge Zavala, Bricq, Stéphanie, Acquitter, Clement, Brunotte, François, Walker, Paul M., Lalande, Alain

“…The T1 and T2 relaxation times are the basic parameters behind magnetic resonance imaging. The accurate knowledge of the T1 and T2 values of tissues allows to…”
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Automatic brain tissue segmentation in fetal MRI using convolutional neural networks by Khalili, N., Lessmann, N., Turk, E., Claessens, N., Heus, R. de, Kolk, T., Viergever, M.A., Benders, M.J.N.L., Išgum, I.

“…MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in…”
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Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials by Shukla‐Dave, Amita, Obuchowski, Nancy A., Chenevert, Thomas L., Jambawalikar, Sachin, Schwartz, Lawrence H., Malyarenko, Dariya, Huang, Wei, Noworolski, Susan M., Young, Robert J., Shiroishi, Mark S., Kim, Harrison, Coolens, Catherine, Laue, Hendrik, Chung, Caroline, Rosen, Mark, Boss, Michael, Jackson, Edward F.

“…Physiological properties of tumors can be measured both in vivo and noninvasively by diffusion‐weighted imaging and dynamic contrast‐enhanced magnetic…”
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State of the art survey on MRI brain tumor segmentation by Gordillo, Nelly, Montseny, Eduard, Sobrevilla, Pilar

“…Abstract Brain tumor segmentation consists of separating the different tumor tissues (solid or active tumor, edema, and necrosis) from normal brain tissues:…”
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Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation by Li, Chunming, Gore, John C, Davatzikos, Christos

“…Abstract This paper proposes a new energy minimization method called multiplicative intrinsic component optimization (MICO) for joint bias field estimation and…”
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Low‐field MRI: An MR physics perspective by Marques, José P., Simonis, Frank F.J., Webb, Andrew G.

“…Historically, clinical MRI started with main magnetic field strengths in the ∼0.05–0.35T range. In the past 40 years there have been considerable developments…”
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Contrast‐enhanced MRI for breast cancer screening by Mann, Ritse M., Kuhl, Christiane K., Moy, Linda

“…Multiple studies in the first decade of the 21st century have established contrast‐enhanced breast MRI as a screening modality for women with a hereditary or…”
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APT‐weighted MRI: Techniques, current neuro applications, and challenging issues by Zhou, Jinyuan, Heo, Hye‐Young, Knutsson, Linda, van Zijl, Peter C.M., Jiang, Shanshan

“…Amide proton transfer‐weighted (APTw) imaging is a molecular MRI technique that generates image contrast based predominantly on the amide protons in mobile…”
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