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Article ; Online: Artificial Intelligence for MR Image Reconstruction: An Overview for Clinicians.

Lin, Dana J / Johnson, Patricia M / Knoll, Florian / Lui, Yvonne W

Journal of magnetic resonance imaging : JMRI

2020 Volume 53, Issue 4, Page(s) 1015–1028

Abstract: ... can match and, in some cases, eclipse conventional reconstruction methods in terms of image quality and ... synthesis, and image reconstruction. With an eye towards clinical applications, we summarize the active ... field of deep-learning-based MR image reconstruction. We review the basic concepts of how deep-learning ...

Abstract	Artificial intelligence (AI) shows tremendous promise in the field of medical imaging, with recent breakthroughs applying deep-learning models for data acquisition, classification problems, segmentation, image synthesis, and image reconstruction. With an eye towards clinical applications, we summarize the active field of deep-learning-based MR image reconstruction. We review the basic concepts of how deep-learning algorithms aid in the transformation of raw k-space data to image data, and specifically examine accelerated imaging and artifact suppression. Recent efforts in these areas show that deep-learning-based algorithms can match and, in some cases, eclipse conventional reconstruction methods in terms of image quality and computational efficiency across a host of clinical imaging applications, including musculoskeletal, abdominal, cardiac, and brain imaging. This article is an introductory overview aimed at clinical radiologists with no experience in deep-learning-based MR image reconstruction and should enable them to understand the basic concepts and current clinical applications of this rapidly growing area of research across multiple organ systems.
MeSH term(s)	Algorithms ; Artifacts ; Artificial Intelligence ; Humans ; Image Processing, Computer-Assisted ; Radiography
Language	English
Publishing date	2020-02-12
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.27078
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Article ; Online: Image reconstruction: an overview for clinicians.

Hansen, Michael S / Kellman, Peter

Journal of magnetic resonance imaging : JMRI

2014 Volume 41, Issue 3, Page(s) 573–585

Abstract: ... The MRI raw data is not acquired in image space and the role of the image reconstruction process is ... them to understand what role basic image reconstruction steps play in the formation of clinical images and how ... Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI ...

Abstract	Image reconstruction plays a critical role in the clinical use of magnetic resonance imaging (MRI). The MRI raw data is not acquired in image space and the role of the image reconstruction process is to transform the acquired raw data into images that can be interpreted clinically. This process involves multiple signal processing steps that each have an impact on the image quality. This review explains the basic terminology used for describing and quantifying image quality in terms of signal-to-noise ratio and point spread function. In this context, several commonly used image reconstruction components are discussed. The image reconstruction components covered include noise prewhitening for phased array data acquisition, interpolation needed to reconstruct square pixels, raw data filtering for reducing Gibbs ringing artifacts, Fourier transforms connecting the raw data with image space, and phased array coil combination. The treatment of phased array coils includes a general explanation of parallel imaging as a coil combination technique. The review is aimed at readers with no signal processing experience and should enable them to understand what role basic image reconstruction steps play in the formation of clinical images and how the resulting image quality is described.
MeSH term(s)	Humans ; Image Processing, Computer-Assisted/methods ; Magnetic Resonance Imaging/methods ; Signal Processing, Computer-Assisted ; Signal-To-Noise Ratio
Language	English
Publishing date	2014-06-25
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Intramural ; Review
ZDB-ID	1146614-5
ISSN	1522-2586 ; 1053-1807
ISSN (online)	1522-2586
ISSN	1053-1807
DOI	10.1002/jmri.24687
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Article ; Online: Image fusion in preoperative planning.

Schendel, Stephen A / Duncan, Kelly S / Lane, Christopher

Facial plastic surgery clinics of North America

2011 Volume 19, Issue 4, Page(s) 577–90, vii

Abstract: ... 3D surface image within a biomechanical context. As taking 3D radiographs has been common practice ... This article presents a comprehensive overview of generating a digital Patient-Specific Anatomic ... Reconstruction (PSAR) model of the craniofacial complex as the foundation for a more objective surgical planning ...

Abstract	This article presents a comprehensive overview of generating a digital Patient-Specific Anatomic Reconstruction (PSAR) model of the craniofacial complex as the foundation for a more objective surgical planning platform. The technique explores fusing the patient's 3D radiograph with the corresponding high-precision 3D surface image within a biomechanical context. As taking 3D radiographs has been common practice for many years, this article describes various approaches to 3D surface imaging and the importance of achieving high-precision anatomical results to simulate surgical outcomes that can be measured and quantified. With the PSAR model readily available for facial assessment and virtual surgery, the advantages of this surgical planning technique are discussed.
MeSH term(s)	Algorithms ; Esthetics ; Face/diagnostic imaging ; Face/surgery ; Female ; Humans ; Image Processing, Computer-Assisted ; Imaging, Three-Dimensional ; Male ; Patient Care Planning ; Phantoms, Imaging ; Photogrammetry/methods ; Preoperative Care/methods ; Radiography ; Surgery, Plastic/instrumentation ; Surgery, Plastic/methods ; Treatment Outcome
Language	English
Publishing date	2011-11
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	1315178-2
ISSN	1558-1926 ; 1064-7406
ISSN (online)	1558-1926
ISSN	1064-7406
DOI	10.1016/j.fsc.2011.07.002
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Article: Advances in PET Image Reconstruction.

Reader, Andrew J / Zaidi, Habib

PET clinics

2007 Volume 2, Issue 2, Page(s) 173–190

Abstract: ... an overview of image reconstruction theory and algorithms for PET, with a particular emphasis on statistical ... Until recently, the most widely used methods for image reconstruction were direct ... iterative reconstruction techniques. Future directions for image reconstruction in PET are considered ...

Abstract	Until recently, the most widely used methods for image reconstruction were direct analytic techniques. Iterative techniques, although computationally much more intensive, produce improved images (principally arising from more accurate modeling of the acquired projection data), enabling these techniques to replace analytic techniques not only in research settings but also in the clinic. This article offers an overview of image reconstruction theory and algorithms for PET, with a particular emphasis on statistical iterative reconstruction techniques. Future directions for image reconstruction in PET are considered, which concern mainly improving the modeling of the data acquisition process and task-specific specification of the parameters to be estimated in image reconstruction.
Language	English
Publishing date	2007-04
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	2764575-7
ISSN	1879-9809 ; 1556-8598
ISSN (online)	1879-9809
ISSN	1556-8598
DOI	10.1016/j.cpet.2007.08.001
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Article ; Online: In Vivo Confocal Microscopy of the Cornea: New Developments in Image Acquisition, Reconstruction, and Analysis Using the HRT-Rostock Corneal Module.

Petroll, W Matthew / Robertson, Danielle M

The ocular surface

2015 Volume 13, Issue 3, Page(s) 187–203

Abstract: ... for quantitative imaging of the subbasal nerve plexus, which require a combination of advanced image acquisition ... Corneal Module (HRT-RCM). We provide an overview of the unique strengths and weaknesses of the HRT-RCM ... of these rapidly evolving strategies should benefit corneal clinicians and basic scientists alike. ...

Abstract	The optical sectioning ability of confocal microscopy allows high magnification images to be obtained from different depths within a thick tissue specimen and is thus ideally suited to the study of intact tissue in living subjects. In vivo confocal microscopy has been used in a variety of corneal research and clinical applications since its development over 25 years ago. In this article we review the latest developments in quantitative corneal imaging with the Heidelberg Retinal Tomograph with Rostock Corneal Module (HRT-RCM). We provide an overview of the unique strengths and weaknesses of the HRT-RCM. We discuss techniques for performing 3-D imaging with the HRT-RCM, including hardware and software modifications that allow full-thickness confocal microscopy through-focusing (CMTF) of the cornea, which can provide quantitative measurements of corneal sublayer thicknesses, stromal cell and extracellular matrix backscatter, and depth-dependent changes in corneal keratocyte density. We also review current approaches for quantitative imaging of the subbasal nerve plexus, which require a combination of advanced image acquisition and analysis procedures, including wide-field mapping and 3-D reconstruction of nerve structures. The development of new hardware, software, and acquisition techniques continues to expand the number of applications of the HRT-RCM for quantitative in vivo corneal imaging at the cellular level. Knowledge of these rapidly evolving strategies should benefit corneal clinicians and basic scientists alike.
MeSH term(s)	Cornea/innervation ; Humans ; Imaging, Three-Dimensional ; Microscopy, Confocal/methods ; Reproducibility of Results
Language	English
Publishing date	2015-05-18
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2208578-6
ISSN	1937-5913 ; 1542-0124
ISSN (online)	1937-5913
ISSN	1542-0124
DOI	10.1016/j.jtos.2015.05.002
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Article ; Online: Advanced visibility enhancement for stents and other devices: image processing aspects.

Schoonenberg, Gert / Florent, Raoul

Cardiology clinics

2009 Volume 27, Issue 3, Page(s) 477–490

Abstract: ... compensating and integrating images of exposure sequences. Three-dimensional stent reconstruction has been ... In non-contrast-enhanced x-ray sequences, the image quality of stents can be enhanced by motion ... an overview of the different methods used for enhanced stent visualization, describes studies that have ...

Abstract	In non-contrast-enhanced x-ray sequences, the image quality of stents can be enhanced by motion compensating and integrating images of exposure sequences. Three-dimensional stent reconstruction has been developed to allow enhanced stent visualization and assessment in three dimensions. This article gives an overview of the different methods used for enhanced stent visualization, describes studies that have evaluated these methods, and summarizes results of these methods on other cardiac and non-cardiac devices.
MeSH term(s)	Angiography, Digital Subtraction ; Coronary Angiography/methods ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional ; Radiographic Image Enhancement ; Stents
Language	English
Publishing date	2009-08
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	1196385-2
ISSN	1558-2264 ; 0733-8651
ISSN (online)	1558-2264
ISSN	0733-8651
DOI	10.1016/j.ccl.2009.03.007
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Article: Gradient-enhanced volume rendering: an image processing strategy to facilitate whole small bowel imaging with MRI.

Wyss, Michael / Froehlich, Johannes M / Patak, Michael A / Juli, Christoph F / Scheidegger, Markus B / Zollikofer, Christoph L / Wentz, Klaus U

European radiology

2006 Volume 17, Issue 4, Page(s) 1081–1088

Abstract: ... on a single image. Twelve healthy volunteers, median age 32 years (range 18-49 years) participated ... format that clinicians are accustomed to and that maximizes the amount of information visualized ... were reproducible and provided an entire overview of the small bowel. In addition thin-slab volume ...

Abstract	MRI of the small bowel with positive contrast from orally administered contrast agent is a promising non-invasive imaging method. The aim of our study was to introduce small bowel MRI in a display format that clinicians are accustomed to and that maximizes the amount of information visualized on a single image. Twelve healthy volunteers, median age 32 years (range 18-49 years) participated in the study. A mixture of 20 ml Gd-DOTA (Dotarem), 0.8 g/kg body weight psyllium fibre (Metamucil) and 1.2 l water were sequentially administered over a period of 4 h. Imaging was performed on a 1.5 T unit (Philips Gyroscan, Intera). Fat-saturated, 3D, gradient echo imaging was performed while the patient was in apnea (30 s). Bowel motion was reduced with 40 mg intravenously administered scopolamine (Buscopan). A 3D, gradient-enhanced, volume rendering technique was applied to the 3D data sets. Standard projections [left anterior oblique (LAO), right anterior oblique (RAO), supine and prone] resembling conventional enteroclysis were successfully generated within fewer than 10 min processing time. Reconstructions were reproducible and provided an entire overview of the small bowel. In addition thin-slab volume rendering allowed an overlap-free display of individual structures. Positive contrast from orally administered contrast agent, combined with a gradient enhanced volume rendering method, allows the reconstruction of the small bowel in a pattern resembling conventional double-contrast enteroclysis. Segmental display without overlay is possible.
MeSH term(s)	Adolescent ; Adult ; Contrast Media/administration & dosage ; Echo-Planar Imaging ; Female ; Humans ; Intestinal Diseases/diagnosis ; Intestine, Small/diagnostic imaging ; Magnetic Resonance Imaging/instrumentation ; Magnetic Resonance Imaging/methods ; Male ; Meglumine/administration & dosage ; Middle Aged ; Organometallic Compounds/administration & dosage ; Radiography
Chemical Substances	Contrast Media ; Organometallic Compounds ; Meglumine (6HG8UB2MUY) ; gadoterate meglumine (L0ND3981AG)
Language	English
Publishing date	2006-10-05
Publishing country	Germany
Document type	Evaluation Study ; Journal Article
ZDB-ID	1085366-2
ISSN	1432-1084 ; 0938-7994 ; 1613-3749
ISSN (online)	1432-1084
ISSN	0938-7994 ; 1613-3749
DOI	10.1007/s00330-006-0472-2
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Article ; Online: Artificial intelligence in multiparametric magnetic resonance imaging: A review.

Li, Cheng / Li, Wen / Liu, Chenyang / Zheng, Hairong / Cai, Jing / Wang, Shanshan

Medical physics

2022 Volume 49, Issue 10, Page(s) e1024–e1054

Abstract: ... employed to perform mpMRI image classification, segmentation, registration, detection, reconstruction, and ... and interpretability. This survey aims to provide an overview for new researchers in the field as well ... Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the clinical ...

Abstract	Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the clinical workflow for the diagnosis and treatment planning of various diseases. Machine learning-based artificial intelligence (AI) methods, especially those adopting the deep learning technique, have been extensively employed to perform mpMRI image classification, segmentation, registration, detection, reconstruction, and super-resolution. The current availabilities of increasing computational power and fast-improving AI algorithms have empowered numerous computer-based systems for applying mpMRI to disease diagnosis, imaging-guided radiotherapy, patient risk and overall survival time prediction, and the development of advanced quantitative imaging technology for magnetic resonance fingerprinting. However, the wide application of these developed systems in the clinic is still limited by a number of factors, including robustness, reliability, and interpretability. This survey aims to provide an overview for new researchers in the field as well as radiologists with the hope that they can understand the general concepts, main application scenarios, and remaining challenges of AI in mpMRI.
MeSH term(s)	Artificial Intelligence ; Humans ; Machine Learning ; Magnetic Resonance Imaging/methods ; Magnetic Resonance Spectroscopy ; Reproducibility of Results
Language	English
Publishing date	2022-08-31
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	188780-4
ISSN	2473-4209 ; 0094-2405
ISSN (online)	2473-4209
ISSN	0094-2405
DOI	10.1002/mp.15936
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Article ; Online: Computer Vision Techniques for Transcatheter Intervention

Feng Zhao / Xianghua Xie / Matthew Roach

IEEE Journal of Translational Engineering in Health and Medicine, Vol 3, Pp 1-

2015 Volume 31

Abstract: ... We aim to give a comprehensive overview for researchers in the area of computer vision on the subject ... Qualitative and quantitative analysis of these cross-sectional image data will be beneficial to the evaluation ... g., image segmentation and motion tracking) have been largely applied in the field to accomplish ...

Abstract	Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and the treatment of cardiovascular diseases. For example, transcatheter aortic valve implantation is an alternative to aortic valve replacement for the treatment of severe aortic stenosis, and transcatheter atrial fibrillation ablation is widely used for the treatment and the cure of atrial fibrillation. In addition, catheter-based intravascular ultrasound and optical coherence tomography imaging of coronary arteries provides important information about the coronary lumen, wall, and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial to the evaluation and the treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation and motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods. We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence, it is important to understand the application domain, clinical background, and imaging modality, so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on the background information of the transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area.
Keywords	Image processing ; IVUS ; medical imaging ; OCT ; reconstruction ; registration ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Medical technology ; R855-855.5
Subject code	004
Language	English
Publishing date	2015-01-01T00:00:00Z
Publisher	IEEE
Document type	Article ; Online
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Article ; Online: Potential Role of Artificial Intelligence in Cardiac Magnetic Resonance Imaging: Can It Help Clinicians in Making a Diagnosis?

Cau, Riccardo / Cherchi, Valeria / Micheletti, Giulio / Porcu, Michele / Mannelli, Lorenzo / Bassareo, Pierpaolo / Suri, Jasjit S / Saba, Luca

Journal of thoracic imaging

2021 Volume 36, Issue 3, Page(s) 142–148

Abstract: ... to improve image acquisition and reconstruction, thus simplifying their analysis, interpretation, and ... magnetic resonance to assist clinicians and engineers in reducing the costs of exams and, at the same time ... This article presents an overview of the existing AI literature in cardiac magnetic resonance ...

Abstract	In the era of modern medicine, artificial intelligence (AI) is a growing field of interest which is experiencing a steady development. Several applications of AI have been applied to various aspects of cardiac magnetic resonance to assist clinicians and engineers in reducing the costs of exams and, at the same time, to improve image acquisition and reconstruction, thus simplifying their analysis, interpretation, and decision-making process as well. In fact, the role of AI and machine learning in cardiovascular imaging relies on evaluating images more quickly, improving their quality, nulling intraobserver and interobserver variability in their interpretation, upgrading the understanding of the stage of the disease, and providing with a personalized approach to cardiovascular care. In addition, AI algorithm could be directed toward workflow management. This article presents an overview of the existing AI literature in cardiac magnetic resonance, with its strengths and limitations, recent applications, and promising developments. We conclude that AI is very likely be used in all the various process of diagnosis routine mode for cardiac care of patients.
MeSH term(s)	Algorithms ; Artificial Intelligence ; Heart/diagnostic imaging ; Humans ; Machine Learning ; Magnetic Resonance Spectroscopy
Language	English
Publishing date	2021-03-21
Publishing country	United States
Document type	Journal Article ; Review
ZDB-ID	632900-7
ISSN	1536-0237 ; 0883-5993
ISSN (online)	1536-0237
ISSN	0883-5993
DOI	10.1097/RTI.0000000000000584
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