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Lebre, M.-A., Vacavant, A., Grand-Brochier, M., Rositi, H., Strand, R., Rosier, H., . . . Magnin, B. (2019). A robust multi-variability model based liver segmentation algorithm for CT-scan and MRI modalities. Computerized Medical Imaging and Graphics, 76, Article ID UNSP 101635.
Open this publication in new window or tab >>A robust multi-variability model based liver segmentation algorithm for CT-scan and MRI modalities
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2019 (English)In: Computerized Medical Imaging and Graphics, ISSN 0895-6111, E-ISSN 1879-0771, Vol. 76, article id UNSP 101635Article in journal (Refereed) Published
Abstract [en]

Developing methods to segment the liver in medical images, study and analyze it remains a significant challenge. The shape of the liver can vary considerably from one patient to another, and adjacent organs are visualized in medical images with similar intensities, making the boundaries of the liver ambiguous. Consequently, automatic or semi-automatic segmentation of liver is a difficult task. Moreover, scanning systems and magnetic resonance imaging have different settings and parameters. Thus the images obtained differ from one machine to another. In this article, we propose an automatic model-based segmentation that allows building a faithful 3-D representation of the liver, with a mean Dice value equal to 90.3% on CT and MRI datasets. We compare our algorithm with a semi-automatic method and with other approaches according to the state of the art. Our method works with different data sources, we use a large quantity of CT and MRI images from machines in various hospitals and multiple DICOM images available from public challenges. Finally, for evaluation of liver segmentation approaches in state of the art, robustness is not adequacy addressed with a precise definition. Another originality of this article is the introduction of a novel measure of robustness, which takes into account the liver variability at different scales. (C) 2019 Published by Elsevier Ltd.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2019
Keywords
Automatic segmentation, 3-D, Liver, CT, MRI, Shape model, Variability, Robustness
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
Identifiers
urn:nbn:se:uu:diva-396624 (URN)10.1016/j.compmedimag.2019.05.003 (DOI)000490629700004 ()31301489 (PubMedID)
Available from: 2019-11-13 Created: 2019-11-13 Last updated: 2019-11-13Bibliographically approved
Sjöholm, T., Ekström, S., Strand, R., Ahlström, H., Lind, L., Malmberg, F. & Kullberg, J. (2019). A whole-body FDG PET/MR atlas for multiparametric voxel-based analysis. Scientific Reports, 9, Article ID 6158.
Open this publication in new window or tab >>A whole-body FDG PET/MR atlas for multiparametric voxel-based analysis
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 6158Article in journal (Refereed) Published
Abstract [en]

Quantitative multiparametric imaging is a potential key application for Positron Emission Tomography/Magnetic Resonance (PET/MR) hybrid imaging. To enable objective and automatic voxel-based multiparametric analysis in whole-body applications, the purpose of this study was to develop a multimodality whole-body atlas of functional 18F-fluorodeoxyglucose (FDG) PET and anatomical fat-water MR data of adults. Image registration was used to transform PET/MR images of healthy control subjects into male and female reference spaces, producing a fat-water MR, local tissue volume and FDG PET whole-body normal atlas consisting of 12 male (66.6 +/- 6.3 years) and 15 female (69.5 +/- 3.6 years) subjects. Manual segmentations of tissues and organs in the male and female reference spaces confirmed that the atlas contained adequate physiological and anatomical values. The atlas was applied in two anomaly detection tasks as proof of concept. The first task automatically detected anomalies in two subjects with suspected malignant disease using FDG data. The second task successfully detected abnormal liver fat infiltration in one subject using fat fraction data.

National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-382934 (URN)10.1038/s41598-019-42613-z (DOI)000464652400029 ()30992502 (PubMedID)
Available from: 2019-04-16 Created: 2019-05-07 Last updated: 2020-02-05Bibliographically approved
Pilia, M., Kullberg, J., Ahlström, H., Malmberg, F., Ekström, S. & Strand, R. (2019). Average volume reference space for large scale registration of whole-body magnetic resonance images. PLoS ONE, 14(10), Article ID e0222700.
Open this publication in new window or tab >>Average volume reference space for large scale registration of whole-body magnetic resonance images
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2019 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 14, no 10, article id e0222700Article in journal (Refereed) Published
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-397325 (URN)10.1371/journal.pone.0222700 (DOI)
Funder
Swedish Research Council, 2016–01040Swedish Heart Lung Foundation, HLF 20170492
Available from: 2019-10-01 Created: 2019-11-19 Last updated: 2019-11-20Bibliographically approved
Lundström, E., Ljungberg, J., Andersson, J., Manell, H., Strand, R., Forslund, A., . . . Kullberg, J. (2019). Brown adipose tissue estimated with the magnetic resonance imaging fat fraction is associated with glucose metabolism in adolescents. Pediatric Obesity, 14(9), Article ID e12531.
Open this publication in new window or tab >>Brown adipose tissue estimated with the magnetic resonance imaging fat fraction is associated with glucose metabolism in adolescents
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2019 (English)In: Pediatric Obesity, ISSN 2047-6302, E-ISSN 2047-6310, Vol. 14, no 9, article id e12531Article in journal (Refereed) Published
Abstract [en]

Background

Despite therapeutic potential against obesity and diabetes, the associations of brown adipose tissue (BAT) with glucose metabolism in young humans are relatively unexplored.

Objectives

To investigate possible associations between magnetic resonance imaging (MRI) estimates of BAT and glucose metabolism, whilst considering sex, age, and adiposity, in adolescents with normal and overweight/obese phenotypes.

Methods

In 143 subjects (10‐20 years), MRI estimates of BAT were assessed as cervical‐supraclavicular adipose tissue (sBAT) fat fraction (FF) and T*2 from water‐fat MRI. FF and T*2 of neighbouring subcutaneous adipose tissue (SAT) were also assessed. Adiposity was estimated with a standardized body mass index, the waist‐to‐height ratio, and abdominal visceral and subcutaneous adipose tissue volumes. Glucose metabolism was represented by the 2h plasma glucose concentration, the Matsuda index, the homeostatic model assessment of insulin resistance, and the oral disposition index; obtained from oral glucose tolerance tests.

Results

sBAT FF and T*2 correlated positively with adiposity before and after adjustment for sex and age. sBAT FF, but not T*2, correlated with 2h glucose and Matsuda index, also after adjustment for sex, age, and adiposity. The association with 2h glucose persisted after additional adjustment for SAT FF.

Conclusions

The association between sBAT FF and 2h glucose, observed independently of sex, age, adiposity, and SAT FF, indicates a role for BAT in glucose metabolism, which potentially could influence the risk of developing diabetes. The lacking association with sBAT T*2 might be due to FF being a superior biomarker for BAT and/or to methodological limitations in the T*2 quantification.

Keywords
adolescent, brown adipose tissue, glucose metabolism, magnetic resonance imaging
National Category
Pediatrics Medical Image Processing
Identifiers
urn:nbn:se:uu:diva-380052 (URN)10.1111/ijpo.12531 (DOI)000482155600007 ()31290284 (PubMedID)
Funder
Swedish Heart Lung Foundation, 2170492Swedish Research Council, 2016-01040EU, FP7, Seventh Framework Programme, 279153
Available from: 2019-07-09 Created: 2019-03-22 Last updated: 2019-10-23Bibliographically approved
Adler, J., Sintorn, I.-M., Strand, R. & Parmryd, I. (2019). Conventional analysis of movement on non-flat surfaces like the plasma membrane makes Brownian motion appear anomalous. Communications Biology, 2, Article ID 12.
Open this publication in new window or tab >>Conventional analysis of movement on non-flat surfaces like the plasma membrane makes Brownian motion appear anomalous
2019 (English)In: Communications Biology, ISSN 2399-3642, Vol. 2, article id 12Article in journal (Refereed) Published
National Category
Biophysics
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-380506 (URN)10.1038/s42003-018-0240-2 (DOI)000461148000001 ()30652124 (PubMedID)
Available from: 2019-01-08 Created: 2019-04-15 Last updated: 2019-05-07Bibliographically approved
Asplund, T., Serna, A., Marcotegui, B., Strand, R. & Luengo Hendriks, C. L. (2019). Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes. In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing: . Paper presented at International Symposium on Mathematical Morphology (ISMM 2019).
Open this publication in new window or tab >>Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes
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2019 (English)In: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, 2019Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

National Category
Signal Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-388524 (URN)10.1007/978-3-030-20867-7_29 (DOI)978-3-030-20866-0 (ISBN)978-3-030-20867-7 (ISBN)
Conference
International Symposium on Mathematical Morphology (ISMM 2019)
Funder
Swedish Research Council, 2014-5983
Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2019-10-17
Malmberg, F., Ciesielski, K. C. & Strand, R. (2019). Optimization of max-norm objective functions in image processing and computer vision. In: Discrete Geometry for Computer Imagery: . Paper presented at DGCI 2019, March 26–28, Marne-la-Vallée, France (pp. 206-218). Springer
Open this publication in new window or tab >>Optimization of max-norm objective functions in image processing and computer vision
2019 (English)In: Discrete Geometry for Computer Imagery, Springer, 2019, p. 206-218Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer, 2019
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11414
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-393368 (URN)10.1007/978-3-030-14085-4_17 (DOI)978-3-030-14084-7 (ISBN)
Conference
DGCI 2019, March 26–28, Marne-la-Vallée, France
Available from: 2019-02-23 Created: 2019-09-20 Last updated: 2019-09-20Bibliographically approved
Lind, L., Kullberg, J., Ahlström, H., Michaëlsson, K. & Strand, R. (2019). Proof of principle study of a detailed whole-body image analysis technique, "Imiomics", regarding adipose and lean tissue distribution. Scientific Reports, 9, Article ID 7388.
Open this publication in new window or tab >>Proof of principle study of a detailed whole-body image analysis technique, "Imiomics", regarding adipose and lean tissue distribution
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2019 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 9, article id 7388Article in journal (Refereed) Published
Abstract [en]

This "proof-of-principle" study evaluates if the recently presented "Imiomics" technique could visualize how fat and lean tissue mass are associated with local tissue volume and fat content at high/unprecedented resolution. A whole-body quantitative water-fat MRI scan was performed in 159 men and 167 women aged 50 in the population-based POEM study. Total fat and lean mass were measured by DXA. Fat content was measured by the water-fat MRI. Fat mass and distribution measures were associated to the detailed differences in tissue volume and fat concentration throughout the body using Imiomics. Fat mass was positively correlated (r > 0.50, p < 0.05) with tissue volume in all subcutaneous areas of the body, as well as volumes of the liver, intraperitoneal fat, retroperitoneal fat and perirenal fat, but negatively to lung volume. Fat mass correlated positively with volumes of paravertebral muscles, and muscles in the ventral part of the thigh and lower limb. Fat mass was distinctly correlated with the fat content in subcutaneous adipose tissue at the trunk. Lean mass was positively related to the large skeletal muscles and the skeleton. The present study indicates the Imiomics technique to be suitable for studies of fat and lean tissue distribution, and feasible for large scale studies.

National Category
Radiology, Nuclear Medicine and Medical Imaging
Identifiers
urn:nbn:se:uu:diva-383519 (URN)10.1038/s41598-019-43690-w (DOI)000467839800059 ()31089168 (PubMedID)
Available from: 2019-05-16 Created: 2019-05-16 Last updated: 2019-06-19Bibliographically approved
Roodakker, K. R., Alhuseinalkhudhur, A., Al-Jaff, M., Georganaki, M., Zetterling, M., Berntsson, S. G., . . . Smits, A. (2019). Region-by-region analysis of PET, MRI, and histology in en bloc-resected oligodendrogliomas reveals intra-tumoral heterogeneity. European Journal of Nuclear Medicine and Molecular Imaging, 46(3), 569-579
Open this publication in new window or tab >>Region-by-region analysis of PET, MRI, and histology in en bloc-resected oligodendrogliomas reveals intra-tumoral heterogeneity
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2019 (English)In: European Journal of Nuclear Medicine and Molecular Imaging, ISSN 1619-7070, E-ISSN 1619-7089, Vol. 46, no 3, p. 569-579Article in journal (Refereed) Published
National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-356591 (URN)10.1007/s00259-018-4107-z (DOI)000457151600005 ()30109401 (PubMedID)
Funder
Erik, Karin och Gösta Selanders Foundation
Available from: 2018-08-14 Created: 2018-08-08 Last updated: 2019-04-06Bibliographically approved
Lind, L., Strand, R., Michaëlsson, K., Kullberg, J. & Ahlström, H. (2019). Relationship between endothelium-dependent vasodilation and fat distribution using the new "imiomics" image analysis technique. NMCD. Nutrition Metabolism and Cardiovascular Diseases, 29(10), 1077-1086
Open this publication in new window or tab >>Relationship between endothelium-dependent vasodilation and fat distribution using the new "imiomics" image analysis technique
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2019 (English)In: NMCD. Nutrition Metabolism and Cardiovascular Diseases, ISSN 0939-4753, E-ISSN 1590-3729, Vol. 29, no 10, p. 1077-1086Article in journal (Refereed) Published
Abstract [en]

Background and aims: We investigated how vasoreactivity in the brachial artery and the forearm resistance vessels were related to fat distribution and tissue volume, using both traditional imaging analysis and a new technique, called “Imiomics”, whereby vasoreactivity was related to each of the >2M 3D image elements included in the whole-body magnetic resonance imaging (MRI).

Methods and results: In 326 subjects in the Prospective investigation of Obesity, Energy and Metabolism (POEM) study (all aged 50 years), endothelium-dependent vasodilation was measured by acetylcholine infusion in the brachial artery (EDV) and flow-mediated vasodilation (FMD). Fat distribution was evaluated by dual-energy X-ray absorptiometry (DXA) and magnetic resonance imaging (MRI). EDV, but not FMD, was significantly related to total fat mass, liver fat, subcutaneous (SAT) and visceral (VAT) adipose tissue in a negative fashion in women, but not in men. Using Imiomics, an inverse relationship was seen between EDV and a local tissue volume of SAT in both the upper part of the body, as well as the gluteo-femoral part and the medial parts of the legs in women. Also the size of the liver, heart and VAT was inversely related to EDV. In men, less pronounced relationships were seen. FMD was also significantly related to local tissue volume of upper-body SAT and liver fat in women, but less so in men.

Conclusion: EDV, and to a lesser degree also FMD, were related to liver fat, SAT and VAT in women, but less so in men. Imiomics both confirmed findings from traditional methods and resulted in new, more detailed results.

Keywords
Magnetic resonance imaging, Whole body imaging, Image analysis, Atherosclerosis, Endothelial dysfunction, Obesity
National Category
Medical Image Processing Radiology, Nuclear Medicine and Medical Imaging
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-392832 (URN)10.1016/j.numecd.2019.06.017 (DOI)000484832100011 ()31377180 (PubMedID)
Funder
Swedish Research Council, 2016-01040Swedish Heart Lung Foundation, 20170492
Available from: 2019-06-24 Created: 2019-09-10 Last updated: 2019-10-11Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-7764-1787

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