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Malmberg, Filip
Publications (10 of 47) Show all publications
Sandberg Melin, C., Malmberg, F. & Söderberg, P. G. (2018). A strategy for OCT estimation of the optic nerve head pigment epithelium central limit-inner limit of the retina minimal distance, PIMD-2π. Acta Ophthalmologica Scandinavica, 96
Open this publication in new window or tab >>A strategy for OCT estimation of the optic nerve head pigment epithelium central limit-inner limit of the retina minimal distance, PIMD-2π
2018 (English)In: Acta Ophthalmologica Scandinavica, ISSN 1395-3907, E-ISSN 1600-0420, Vol. 96Article in journal (Refereed) Epub ahead of print
National Category
Ophthalmology Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-362723 (URN)10.1111/aos.13908 (DOI)
Available from: 2018-09-10 Created: 2018-10-09 Last updated: 2018-10-10Bibliographically approved
Strand, R., Malmberg, F., Johansson, L., Lind, L., Sundbom, M., Ahlström, H. & Kullberg, J. (2017). A concept for holistic whole body MRI data analysis, Imiomics. PLoS ONE, 12(2), Article ID e0169966.
Open this publication in new window or tab >>A concept for holistic whole body MRI data analysis, Imiomics
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2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 2, article id e0169966Article in journal (Refereed) Published
Abstract [en]

Purpose: To present and evaluate a whole-body image analysis concept, Imiomics (imaging omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data.

Methods: The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis.

Results: The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept.

Conclusions: The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis.

National Category
Radiology, Nuclear Medicine and Medical Imaging
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-316830 (URN)10.1371/journal.pone.0169966 (DOI)000395934400002 ()28241015 (PubMedID)
Available from: 2017-02-27 Created: 2017-03-07 Last updated: 2017-11-29Bibliographically approved
Nyström, I., Nysjö, J., Thor, A. & Malmberg, F. (2017). BoneSplit – A 3D painting tool for interactive bone segmentation in CT images. In: Pattern Recognition and Information Processing: PRIP 2016. Paper presented at PRIP 2016, October 3–5, Minsk, Belarus (pp. 3-13). Springer
Open this publication in new window or tab >>BoneSplit – A 3D painting tool for interactive bone segmentation in CT images
2017 (English)In: Pattern Recognition and Information Processing: PRIP 2016, Springer, 2017, p. 3-13Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer, 2017
Series
Communications in Computer and Information Science ; 673
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-317762 (URN)10.1007/978-3-319-54220-1_1 (DOI)978-3-319-54219-5 (ISBN)
Conference
PRIP 2016, October 3–5, Minsk, Belarus
Available from: 2017-02-17 Created: 2017-03-17 Last updated: 2017-03-17Bibliographically approved
Malmberg, F., Luengo Hendriks, C. L. & Strand, R. (2017). Exact Evaluation of Targeted Stochastic Watershed Cuts. Discrete Applied Mathematics, 216(2), 449-460
Open this publication in new window or tab >>Exact Evaluation of Targeted Stochastic Watershed Cuts
2017 (English)In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 216, no 2, p. 449-460Article in journal (Refereed) Published
Abstract [en]

Seeded segmentation with minimum spanning forests, also known as segmentation by watershed cuts, is a powerful method for supervised image segmentation. Given that correct segmentation labels are provided for a small set of image elements, called seeds, the watershed cut method completes the labeling for all image elements so that the boundaries between different labels are optimally aligned with salient edges in the image. Here, a randomized version of watershed segmentation, the targeted stochastic watershed, is proposed for performing multi-label targeted image segmentation with stochastic seed input. The input to the algorithm is a set of probability density functions (PDFs), one for each segmentation label, defined over the pixels of the image. For each pixel, we calculate the probability that the pixel is assigned a given segmentation label in seeded watershed segmentation with seeds drawn from the input PDFs. We propose an efficient algorithm (quasi-linear with respect to the number of image elements) for calculating the desired probabilities exactly.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Image segmentation, Stochastic watershed, Watershed cut, Minimum spanning forest
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-333808 (URN)10.1016/j.dam.2016.01.006 (DOI)000390504100011 ()
Available from: 2017-11-17 Created: 2017-11-17 Last updated: 2018-09-04Bibliographically approved
Söderberg, P. G., Malmberg, F. & Sandberg Melin, C. (2017). Further analysis of clinical feasibility of OCT-based glaucoma diagnosis with Pigment epithelium central limit–Inner limit of the retina Minimal Distance (PIMD). In: Ophthalmic Technologies XXVII: . Bellingham, WA: SPIE - International Society for Optical Engineering, Article ID 100450R.
Open this publication in new window or tab >>Further analysis of clinical feasibility of OCT-based glaucoma diagnosis with Pigment epithelium central limit–Inner limit of the retina Minimal Distance (PIMD)
2017 (English)In: Ophthalmic Technologies XXVII, Bellingham, WA: SPIE - International Society for Optical Engineering, 2017, article id 100450RConference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Bellingham, WA: SPIE - International Society for Optical Engineering, 2017
Series
Proc. SPIE ; 10045
National Category
Ophthalmology Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-341869 (URN)10.1117/12.2260139 (DOI)000405820700021 ()978-1-5106-0531-2 (ISBN)
Available from: 2017-02-10 Created: 2018-02-16 Last updated: 2018-03-03Bibliographically approved
Ahlström, H., Ekström, S., Sjöholm, T., Strand, R., Kullberg, J., Johansson, E., . . . Malmberg, F. (2017). Registration-based automated lesion detection and therapy evaluation of tumors in whole body PET-MR images. Paper presented at 42nd European-Society-for-Medical-Oncology Congress (ESMO), SEP 08-12, 2017, Madrid, SPAIN. Annals of Oncology, 28(S5), Article ID 78P.
Open this publication in new window or tab >>Registration-based automated lesion detection and therapy evaluation of tumors in whole body PET-MR images
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2017 (English)In: Annals of Oncology, ISSN 0923-7534, E-ISSN 1569-8041, Vol. 28, no S5, article id 78PArticle in journal, Meeting abstract (Other academic) Published
National Category
Radiology, Nuclear Medicine and Medical Imaging Cancer and Oncology
Identifiers
urn:nbn:se:uu:diva-346976 (URN)000411324000073 ()
Conference
42nd European-Society-for-Medical-Oncology Congress (ESMO), SEP 08-12, 2017, Madrid, SPAIN
Available from: 2018-03-26 Created: 2018-03-26 Last updated: 2018-03-26Bibliographically approved
Malmberg, F., Nordenskjöld, R., Strand, R. & Kullberg, J. (2017). SmartPaint: a tool for interactive segmentation of medical volume images. Computer Methods In Biomechanics And Biomedical Engeineering-Imaging And Visualization, 5(1), 36-44
Open this publication in new window or tab >>SmartPaint: a tool for interactive segmentation of medical volume images
2017 (English)In: Computer Methods In Biomechanics And Biomedical Engeineering-Imaging And Visualization, ISSN 2168-1163, Vol. 5, no 1, p. 36-44Article in journal (Refereed) Published
Abstract [en]

We present SmartPaint, a general-purpose method and software for interactive segmentation of medical volume images. SmartPaint uses a novel paint-brush interaction paradigm, where the user segments objects in the image by 'sweeping' over them with the mouse cursor. The key feature of SmartPaint is that the painting tools adapt to the image content, selectively sticking to objects of interest while avoiding other structures. This behaviour is achieved by modulating the effect of the tools by both the Euclidean distance and the range distance (difference in image intensity values) from the mouse cursor. We evaluate SmartPaint on three publicly available medical image datasets, covering different image modalities and segmentation targets. The results show that, with a limited user effort, SmartPaint can produce segmentations whose accuracy is comparable to both the state-of-the-art automatic segmentation methods and manual delineations produced by expert users. The SmartPaint software is freely available, and can be downloaded from the authors' web page (http://www.cb.uu.se/similar to filip/SmartPaint/).

Place, publisher, year, edition, pages
TAYLOR & FRANCIS LTD, 2017
Keywords
image segmentation, medical imaging, interactive segmentation
National Category
Biomaterials Science
Identifiers
urn:nbn:se:uu:diva-319143 (URN)10.1080/21681163.2014.960535 (DOI)000396688800005 ()
Available from: 2017-03-31 Created: 2017-03-31 Last updated: 2018-05-14Bibliographically approved
Strand, R., Ciesielski, K. C., Malmberg, F. & Saha, P. K. (2017). The Minimum Barrier Distance: A Summary of Recent Advances. In: Lecture Notes in Computer Science book series (LNCS, volume 10502): . Paper presented at International Conference on Discrete Geometry for Computer Imagery (pp. 57-68). Switzerland, 10502
Open this publication in new window or tab >>The Minimum Barrier Distance: A Summary of Recent Advances
2017 (English)In: Lecture Notes in Computer Science book series (LNCS, volume 10502), Switzerland, 2017, Vol. 10502, p. 57-68Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we present an overview and summary of recent results of the minimum barrier distance (MBD), a distance operator that is a promising tool in several image processing applications. The theory constitutes of the continuous MBD in Rn, its discrete formulation in Zn (in two different natural formulations), and of the discussion of convergence of discrete MBDs to their continuous counterpart. We describe two algorithms that compute MBD, one very fast but returning only approximate MBD, the other a bit slower, but returning the exact MBD. Finally, some image processing applications of MBD are presented and the directions of potential future research in this area are indicated.

Place, publisher, year, edition, pages
Switzerland: , 2017
National Category
Computer Sciences Discrete Mathematics
Identifiers
urn:nbn:se:uu:diva-333683 (URN)10.1007/978-3-319-66272-5_6 (DOI)978-3-319-66272-5 (ISBN)978-3-319-66271-8 (ISBN)
Conference
International Conference on Discrete Geometry for Computer Imagery
Available from: 2017-11-16 Created: 2017-11-16 Last updated: 2018-01-13Bibliographically approved
Nysjö, F., Olsson, P., Malmberg, F., Carlbom, I. B. & Nyström, I. (2017). Using anti-aliased signed distance fields for generating surgical guides and plates from CT images. Journal of WSCG, 25(1), 11-20
Open this publication in new window or tab >>Using anti-aliased signed distance fields for generating surgical guides and plates from CT images
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2017 (English)In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 25, no 1, p. 11-20Article in journal (Refereed) Published
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-335346 (URN)
Available from: 2017-12-04 Created: 2017-12-04 Last updated: 2017-12-15Bibliographically approved
Sandberg Melin, C., Malmberg, F. & Söderberg, P. G. (2016). An OCT variable for glaucoma follow-up: Pigment epithelium central limit - Inner limit of the retina, Minimal Distance, PIMD. Paper presented at Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), MAY 01-05, 2016, Seattle, WA. Investigative Ophthalmology and Visual Science, 57(12)
Open this publication in new window or tab >>An OCT variable for glaucoma follow-up: Pigment epithelium central limit - Inner limit of the retina, Minimal Distance, PIMD
2016 (English)In: Investigative Ophthalmology and Visual Science, ISSN 0146-0404, E-ISSN 1552-5783, Vol. 57, no 12Article in journal, Meeting abstract (Other academic) Published
Place, publisher, year, edition, pages
ASSOC RESEARCH VISION OPHTHALMOLOGY INC, 2016
National Category
Ophthalmology
Identifiers
urn:nbn:se:uu:diva-321044 (URN)000394174002292 ()
Conference
Annual Meeting of the Association-for-Research-in-Vision-and-Ophthalmology (ARVO), MAY 01-05, 2016, Seattle, WA
Available from: 2017-04-28 Created: 2017-04-28 Last updated: 2017-04-28Bibliographically approved
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