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Lindner T, Bolar DS, Achten E, Barkhof F, Bastos-Leite AJ, Detre JA, Golay X, Günther M, Wang DJJ, Haller S, Ingala S, Jäger HR, Jahng GH, Juttukonda MR, Keil VC, Kimura H, Ho ML, Lequin M, Lou X, Petr J, Pinter N, Pizzini FB, Smits M, Sokolska M, Zaharchuk G, Mutsaerts HJMM. Current state and guidance on arterial spin labeling perfusion MRI in clinical neuroimaging. Magn Reson Med 2023; 89:2024-2047. [PMID: 36695294 PMCID: PMC10914350 DOI: 10.1002/mrm.29572] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/16/2022] [Accepted: 12/19/2022] [Indexed: 01/26/2023]
Abstract
This article focuses on clinical applications of arterial spin labeling (ASL) and is part of a wider effort from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group to update and expand on the recommendations provided in the 2015 ASL consensus paper. Although the 2015 consensus paper provided general guidelines for clinical applications of ASL MRI, there was a lack of guidance on disease-specific parameters. Since that time, the clinical availability and clinical demand for ASL MRI has increased. This position paper provides guidance on using ASL in specific clinical scenarios, including acute ischemic stroke and steno-occlusive disease, arteriovenous malformations and fistulas, brain tumors, neurodegenerative disease, seizures/epilepsy, and pediatric neuroradiology applications, focusing on disease-specific considerations for sequence optimization and interpretation. We present several neuroradiological applications in which ASL provides unique information essential for making the diagnosis. This guidance is intended for anyone interested in using ASL in a routine clinical setting (i.e., on a single-subject basis rather than in cohort studies) building on the previous ASL consensus review.
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Affiliation(s)
- Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Divya S. Bolar
- Center for Functional Magnetic Resonance Imaging, Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Eric Achten
- Department of Radiology and Nuclear Medicine, Ghent University, Ghent, Belgium
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands; Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, UK
| | | | - John A. Detre
- Department of Neurology, University of Pennsylvania, Philadelphia PA USA
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Matthias Günther
- (1) University Bremen, Germany; (2) Fraunhofer MEVIS, Bremen, Germany; (3) mediri GmbH, Heidelberg, Germany
| | - Danny JJ Wang
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles CA USA
| | - Sven Haller
- (1) CIMC - Centre d’Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Genève 1201 Genève (2) Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden (3) Faculty of Medicine of the University of Geneva, Switzerland. Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, P. R. China
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Hans R Jäger
- UCL Queen Square Institute of Neuroradiology, University College London, London, UK
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Meher R. Juttukonda
- (1) Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown MA USA (2) Department of Radiology, Harvard Medical School, Boston MA USA
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Cancer Center Amsterdam, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Hirohiko Kimura
- Department of Radiology, Faculty of Medical sciences, University of Fukui, Fukui, JAPAN
| | - Mai-Lan Ho
- Nationwide Children’s Hospital and The Ohio State University, Columbus, OH, USA
| | - Maarten Lequin
- Division Imaging & Oncology, Department of Radiology & Nuclear Medicine | University Medical Center Utrecht & Princess Máxima Center for Pediatric Oncology, Utrecht, The Netherlands
| | - Xin Lou
- Department of Radiology, Chinese PLA General Hospital, Beijing, China
| | - Jan Petr
- (1) Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany (2) Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Nandor Pinter
- Dent Neurologic Institute, Buffalo, NY, USA. University at Buffalo Neurosurgery, Buffalo, NY, USA
| | - Francesca B. Pizzini
- Radiology Institute, Dept. of Diagnostic and Public Health, University of Verona, Verona, Italy
| | - Marion Smits
- (1) Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands (2) The Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Magdalena Sokolska
- Department of Medical Physics and Biomedical Engineering University College London Hospitals NHS Foundation Trust, UK
| | | | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
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Gorman C, Punzo D, Octaviano I, Pieper S, Longabaugh WJR, Clunie DA, Kikinis R, Fedorov AY, Herrmann MD. Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology. Nat Commun 2023; 14:1572. [PMID: 36949078 PMCID: PMC10033920 DOI: 10.1038/s41467-023-37224-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/08/2023] [Indexed: 03/24/2023] Open
Abstract
The exchange of large and complex slide microscopy imaging data in biomedical research and pathology practice is impeded by a lack of data standardization and interoperability, which is detrimental to the reproducibility of scientific findings and clinical integration of technological innovations. We introduce Slim, an open-source, web-based slide microscopy viewer that implements the internationally accepted Digital Imaging and Communications in Medicine (DICOM) standard to achieve interoperability with a multitude of existing medical imaging systems. We showcase the capabilities of Slim as the slide microscopy viewer of the NCI Imaging Data Commons and demonstrate how the viewer enables interactive visualization of traditional brightfield microscopy and highly-multiplexed immunofluorescence microscopy images from The Cancer Genome Atlas and Human Tissue Atlas Network, respectively, using standard DICOMweb services. We further show how Slim enables the collection of standardized image annotations for the development or validation of machine learning models and the visual interpretation of model inference results in the form of segmentation masks, spatial heat maps, or image-derived measurements.
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Affiliation(s)
- Chris Gorman
- Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | | | | | | | - Ron Kikinis
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrey Y Fedorov
- Department of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
| | - Markus D Herrmann
- Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
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3
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O'Brien AT, Gil KE, Varghese J, Simonetti OP, Zareba KM. T2 mapping in myocardial disease: a comprehensive review. J Cardiovasc Magn Reson 2022; 24:33. [PMID: 35659266 PMCID: PMC9167641 DOI: 10.1186/s12968-022-00866-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 04/27/2022] [Indexed: 12/20/2022] Open
Abstract
Cardiovascular magnetic resonance (CMR) is considered the gold standard imaging modality for myocardial tissue characterization. Elevated transverse relaxation time (T2) is specific for increased myocardial water content, increased free water, and is used as an index of myocardial edema. The strengths of quantitative T2 mapping lie in the accurate characterization of myocardial edema, and the early detection of reversible myocardial disease without the use of contrast agents or ionizing radiation. Quantitative T2 mapping overcomes the limitations of T2-weighted imaging for reliable assessment of diffuse myocardial edema and can be used to diagnose, stage, and monitor myocardial injury. Strong evidence supports the clinical use of T2 mapping in acute myocardial infarction, myocarditis, heart transplant rejection, and dilated cardiomyopathy. Accumulating data support the utility of T2 mapping for the assessment of other cardiomyopathies, rheumatologic conditions with cardiac involvement, and monitoring for cancer therapy-related cardiac injury. Importantly, elevated T2 relaxation time may be the first sign of myocardial injury in many diseases and oftentimes precedes symptoms, changes in ejection fraction, and irreversible myocardial remodeling. This comprehensive review discusses the technical considerations and clinical roles of myocardial T2 mapping with an emphasis on expanding the impact of this unique, noninvasive tissue parameter.
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Affiliation(s)
- Aaron T O'Brien
- Ohio University Heritage College of Osteopathic Medicine, Athens, Ohio, USA
| | - Katarzyna E Gil
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
| | - Juliet Varghese
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA
| | - Orlando P Simonetti
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA
- Department of Radiology, The Ohio State University, Columbus, Ohio, USA
| | - Karolina M Zareba
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio, USA.
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, Ohio, USA.
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Cooper PS, Baillet S, Maroun REK, Chong TTJ. Over the rainbow: Guidelines for meaningful use of colour maps in neurophysiology. Neuroimage 2021; 245:118628. [PMID: 34637902 DOI: 10.1016/j.neuroimage.2021.118628] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/16/2021] [Accepted: 09/28/2021] [Indexed: 10/20/2022] Open
Abstract
Visualization of complex data is commonplace in neurophysiology research. Here, we highlight specific perceptual issues related to the ongoing misuse of variations of the rainbow colour scheme, with a particular emphasis on time-frequency decompositions in electrophysiology as an illustrative example. We review the risks of biased interpretation of neurophysiological data in this context, and provide guidelines to improve the use of colour maps to visualise complex, multidimensional data in neurophysiology research.
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Affiliation(s)
- Patrick S Cooper
- Turner Institute for Brain and Mental Health, Monash University, Victoria 3800, Australia; Melbourne School of Psychological Sciences, University of Melbourne, Victoria 3010, Australia.
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Québec H3A 2B4, Canada
| | | | - Trevor T-J Chong
- Turner Institute for Brain and Mental Health, Monash University, Victoria 3800, Australia; Department of Neurology, Alfred Health, Melbourne, Victoria 3004, Australia; Department of Clinical Neurosciences, St Vincent's Hospital, Victoria 3065, Australia
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Whitehead MT, Guillot LM, Reilly BK. Cochlear signal alterations using pseudo-color perceptual enhancement for patients with sensorineural hearing loss. Pediatr Radiol 2021; 51:1448-1456. [PMID: 33687494 DOI: 10.1007/s00247-021-04987-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/12/2020] [Accepted: 01/26/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Neuroimaging detection of sensorineural hearing loss (SNHL)-related temporal bone abnormalities is limited (20-50%). We hypothesize that cochlear signal differences in gray-scale data may exceed the threshold of human eye detection. Gray-scale images can be post-processed to enhance perception of tonal difference using "pseudo-color" schemes. OBJECTIVE To compare patients with unilateral SNHL to age-matched normal magnetic resonance imaging (MRI) exams for "labyrinthine color differences" employing pseudo-color post-processing. MATERIALS AND METHODS The MRI database at an academic children's hospital was queried for "hearing loss." Only unilateral SNHL cases were analyzed. Sixty-nine imaging exams were reviewed. Thirteen age-matched normal MR exams in children without hearing loss were chosen for comparison. Pseudo-color was applied with post-processing assignment of specific hues to each gray-scale intensity value. Gray-scale and pseudo-color images were qualitatively evaluated for signal asymmetries by a board-certified neuroradiologist blinded to the side of SNHL. RESULTS Twenty-six SNHL (mean: 7.6±3 years) and 13 normal control exams (mean: 7.3±4 years) were included. All patients had normal gray-scale cochlear signal and all controls had symmetrical pseudo-color signal. However, pseudo-color images revealed occult asymmetries localizing to the SNHL ear with lower values in 38%. Ninety-one percent of these cases showed concordance between the side of pseudo-color positivity and the side of hearing loss. CONCLUSION Pseudo-color perceptual image enhancement reveals intra-labyrinthine fluid alterations on MR exams in children with unilateral SNHL. Pseudo-color image enhancement techniques improve detection of cochlear pathology and could have therapeutic implications.
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Affiliation(s)
- Matthew T Whitehead
- Department of Radiology, Children's National Hospital, 111 Michigan Ave. NW, Washington, DC, 20010, USA. .,The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.
| | - Lori M Guillot
- The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Department of Otolaryngology, Children's National Hospital, Washington, DC, USA.,Pediatric Ear, Nose and Throat of Atlanta, Atlanta, GA, USA
| | - Brian K Reilly
- The George Washington University School of Medicine and Health Sciences, Washington, DC, USA.,Department of Otolaryngology, Children's National Hospital, Washington, DC, USA
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Abstract
In two experiments, we trained pigeons (Columba livia) to sort visual images (obtained by clinical myocardial perfusion imaging techniques) depicting different degrees of human cardiac disfunction (myocardial hypoperfusion of the left ventricle) into normal and abnormal categories by providing food reward only after correct choice responses. Pigeons proved to be highly proficient at categorizing pseudo-colorized images as well as highly sensitive to the degree of the perfusion deficit depicted in the abnormal images. In later testing, the pigeons completely transferred discriminative responding to novel stimuli, demonstrating that they had fully learned the normal and abnormal categories. Yet, these pigeons failed to transfer discriminative responding to grayscale images containing no color information. We therefore trained a second cohort of pigeons to categorize grayscale image sets from the outset. These birds required substantially more training to achieve similar levels of performance. Yet, they too completely transferred discriminative responding to novel stimuli by relying on both global and local disparities in brightness between the normal and abnormal images. These results confirm that pseudo-colorization can enhance pigeons' categorization of human cardiac images, a result also found with human observers. Overall, our findings further document the potential of the pigeon as a useful aide in studies of medical image perception.
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Affiliation(s)
- Victor M Navarro
- Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA, 52242, USA
| | - Edward A Wasserman
- Department of Psychological and Brain Sciences, The University of Iowa, Iowa City, IA, 52242, USA.
| | - Piotr Slomka
- Cedars-Sinai Medical Center, University of California, Los Angeles, CA, USA
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7
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Knippa EE, Berg E, Richard S, Lin Y, Roy Choudhury K, Samei E, Baker JA. Impact of Colorized Display of Mammograms on Lesion Detection. JOURNAL OF BREAST IMAGING 2020; 2:22-28. [PMID: 38424995 DOI: 10.1093/jbi/wbz075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 10/18/2019] [Indexed: 03/02/2024]
Abstract
OBJECTIVE To assess the effect of the colorized display of digital mammograms on observer detection of subtle breast lesions. METHODS Three separate observer studies compared detection performance using grayscale versus color display of 1) low-contrast mass-like objects in a standardized mammography phantom; 2) simulated microcalcifications in a background of normal breast parenchyma; and 3) standard-of-care clinical digital mammograms with subtle calcifications and masses. Colorization of the images was done by displaying each image pixel in blue, green, and red hues, or gray, maintaining DICOM-calibrated luminance scale and consistent luminance range. For the simulated calcifications and clinical mammogram studies, comparison of detection rates was computed using McNemar's test for paired differences. RESULTS For the phantom study, mass-like object detection was significantly better using a green colormap than grayscale (73.3% vs 70.8%, P = .009), with no significant improvement using blue or red colormaps (72.6% and 72.5%, respectively). For simulated microcalcifications, no significant difference was noted in detection using the green colormap, as compared with grayscale. For clinical digital screening mammograms, no significant difference was noted between gray and green colormaps for detection of microcalcifications. Green color display, however, resulted in decreased sensitivity for detection of subtle masses (63% vs 69%, P = .03). CONCLUSION Although modest improvement was demonstrated for a detection task using colorized display of a standard mammography phantom, no significant improvement was demonstrated using a color display for a simulated clinical detection task, and actual clinical performance was worse for colorized display of mammograms in comparison to standard grayscale display.
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Affiliation(s)
- Emily E Knippa
- University of Texas Southwestern Medical Center, Department of Radiology, Dallas, TX
| | - Erica Berg
- Wisconsin Radiology Specialists, Milwaukee, WI
| | | | - Yuan Lin
- OPPO US Research Center, AI Department, Palo Alto, CA
| | | | - Ehsan Samei
- Duke University, Departments of Radiology, Physics, and Biomedical Engineering, and Electrical and Computer Engineering, Durham, NC
| | - Jay A Baker
- Duke University Hospital, Department of Radiology, Durham, NC
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Wong TH, Shagera QA, Ryoo HG, Ha S, Lee DS. Basal and Acetazolamide Brain Perfusion SPECT in Internal Carotid Artery Stenosis. Nucl Med Mol Imaging 2020; 54:9-27. [PMID: 32206127 PMCID: PMC7062956 DOI: 10.1007/s13139-019-00633-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Revised: 12/19/2019] [Accepted: 12/26/2019] [Indexed: 10/25/2022] Open
Abstract
Internal carotid artery (ICA) stenosis including Moyamoya disease needs revascularization when hemodynamic insufficiency is validated. Vascular reserve impairment was the key to find the indication for endarterectomy/bypass surgery in the atherosclerotic ICA stenosis and to determine the indication, treatment effect, and prognosis in Moyamoya diseases. Vascular reserve was quantitatively assessed by 1-day split-dose I-123 IMP basal/acetazolamide SPECT in Japan or by Tc-99m HMPAO SPECT in other countries using qualitative or semi-quantitative method. We summarized the development of 1-day basal/ acetazolamide brain perfusion SPECT for ICA stenosis, both quantitative and qualitative methods, and their methodological issues regarding (1) acquisition protocol; (2) qualitative assessment, either visual or deep learning-based; (3) clinical use for atherosclerotic ICA steno-occlusive diseases and mostly Moyamoya diseases; and (4) their impact on the choice of treatment options. Trials to use CT perfusion or perfusion MRI using contrast materials or arterial spin labeling were briefly discussed in their endeavor to use basal studies alone to replace acetazolamide-challenge SPECT. Theoretical and practical issues imply that basal perfusion evaluation, no matter how much sophisticated, will not disclose vascular reserve. Acetazolamide rarely causes serious adverse reactions but included fatality, and now, we need to monitor patients closely in acetazolamide-challenge studies.
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Affiliation(s)
- Teck Huat Wong
- Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Jongno-Gu, Seoul, 110-744 South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea
| | - Qaid Ahmed Shagera
- Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Jongno-Gu, Seoul, 110-744 South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea
| | - Hyun Gee Ryoo
- Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Jongno-Gu, Seoul, 110-744 South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea
| | - Seunggyun Ha
- Division of Nuclear Medicine Department of Radiology, Seoul St. Mary’s Hospital, The Catholic University of Korea, Seoul, South Korea
| | - Dong Soo Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Jongno-Gu, Seoul, 110-744 South Korea
- Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea
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Kimpe T, Rostang J, Van Hoey G, Xthona A. Color standard display function: A proposed extension of DICOM GSDF. Med Phys 2017; 43:5009. [PMID: 27587031 DOI: 10.1118/1.4959544] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
PURPOSE Color images are being used more in medical imaging for a broad range of modalities and applications. While in the past, color was mostly used for annotations, today color is also widely being used for diagnostic purposes. Surprisingly enough, there is no agreed upon standard yet that describes how color medical images need to be visualized and how calibration and quality assurance of color medical displays need to be performed. This paper proposes color standard display function (CSDF) which is an extension of the DICOM GSDF standard toward color. CSDF defines how color medical displays need to be calibrated and how QA can be performed to obtain perceptually linear behavior not only for grayscale but also for color. METHODS The proposed CSDF algorithm uses DICOM GSDF calibration as a starting point and subsequently uses a color visual difference metric to redistribute colors in order to obtain perceptual linearity not only for the grayscale behavior but also for the color behavior. A clear calibration and quality assurance algorithm is defined and is validated on a wide range of different display systems. RESULTS A detailed description of the proposed CSDF calibration and quality assurance algorithms is provided. These algorithms have been tested extensively on three types of display systems: consumer displays, professional displays, and medical grade displays. Test results are reported both for the calibration algorithm as well as for the quantitative and visual quality assurance methods. The tests confirm that the described algorithm generates consistent results and is able to increase perceptual linearity for color and grayscale visualization. Moreover the proposed algorithms are working well on a wide range of display systems. CONCLUSIONS CSDF has been proposed as an extension of the DICOM GSDF standard toward color. Calibration and QA algorithms for CSDF have been described in detail. The proposed algorithms have been tested on several types of display systems and the results confirm that CSDF largely increases the perceptual linearity of visualized colors, while at the same time remaining compliant with DICOM GSDF.
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Affiliation(s)
- Tom Kimpe
- Barco NV, Healthcare Division, Beneluxpark 21, 8500 Kortrijk, Belgium
| | - Johan Rostang
- Barco NV, Healthcare Division, Beneluxpark 21, 8500 Kortrijk, Belgium
| | - Gert Van Hoey
- Barco NV, Healthcare Division, Beneluxpark 21, 8500 Kortrijk, Belgium
| | - Albert Xthona
- Barco NV, Healthcare Division, Beneluxpark 21, 8500 Kortrijk, Belgium
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