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Suveer, Amit
Publications (6 of 6) Show all publications
Suveer, A., Sladoje, N., Lindblad, J., Dragomir, A. & Sintorn, I.-M. (2017). Cilia ultrastructural visibility enhancement by multiple instance registration and super-resolution reconstruction. In: Swedish Symposium on Image Analysis: . Swedish Society for Automated Image Analysis
Open this publication in new window or tab >>Cilia ultrastructural visibility enhancement by multiple instance registration and super-resolution reconstruction
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2017 (English)In: Swedish Symposium on Image Analysis, Swedish Society for Automated Image Analysis , 2017Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Swedish Society for Automated Image Analysis, 2017
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-335371 (URN)
Available from: 2017-12-04 Created: 2017-12-04 Last updated: 2018-08-24
Gupta, A., Suveer, A., Lindblad, J., Dragomir, A., Sintorn, I.-M. & Sladoje, N. (2017). Convolutional neural networks for false positive reduction of automatically detected cilia in low magnification TEM images. In: Image Analysis: Part I. Paper presented at SCIA 2017, June 12–14, Tromsø, Norway (pp. 407-418). Springer
Open this publication in new window or tab >>Convolutional neural networks for false positive reduction of automatically detected cilia in low magnification TEM images
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2017 (English)In: Image Analysis: Part I, Springer, 2017, p. 407-418Conference paper, Published paper (Refereed)
Abstract
Place, publisher, year, edition, pages
Springer, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10269
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-334218 (URN)10.1007/978-3-319-59126-1_34 (DOI)978-3-319-59125-4 (ISBN)
Conference
SCIA 2017, June 12–14, Tromsø, Norway
Funder
VINNOVA, 2016-02329
Available from: 2017-05-19 Created: 2017-11-21 Last updated: 2018-08-24Bibliographically approved
Suveer, A., Sladoje, N., Lindblad, J., Dragomir, A. & Sintorn, I.-M. (2017). Enhancement of cilia sub-structures by multiple instance registration and super-resolution reconstruction. In: Image Analysis: Part II. Paper presented at SCIA 2017, June 12–14, Tromsø, Norway (pp. 362-374). Springer
Open this publication in new window or tab >>Enhancement of cilia sub-structures by multiple instance registration and super-resolution reconstruction
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2017 (English)In: Image Analysis: Part II, Springer, 2017, p. 362-374Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Springer, 2017
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10270
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-334225 (URN)10.1007/978-3-319-59129-2_31 (DOI)978-3-319-59128-5 (ISBN)
Conference
SCIA 2017, June 12–14, Tromsø, Norway
Available from: 2017-05-19 Created: 2017-11-21 Last updated: 2018-08-24Bibliographically approved
Gupta, A., Suveer, A., Lindblad, J., Dragomir, A., Sintorn, I.-M. & Sladoje, N. (2017). False positive reduction of cilia detected in low resolution TEM images using a convolutional neural network. In: Swedish Symposium on Image Analysis: . Paper presented at SWEDISH SYMPOSIUM ON IMAGE ANALYSIS 2017 (SSBA), 13-15 March 2017, Linköping, Sweden. Swedish Society for Automated Image Analysis
Open this publication in new window or tab >>False positive reduction of cilia detected in low resolution TEM images using a convolutional neural network
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2017 (English)In: Swedish Symposium on Image Analysis, Swedish Society for Automated Image Analysis , 2017Conference paper, Published paper (Other academic)
Place, publisher, year, edition, pages
Swedish Society for Automated Image Analysis, 2017
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-335454 (URN)
Conference
SWEDISH SYMPOSIUM ON IMAGE ANALYSIS 2017 (SSBA), 13-15 March 2017, Linköping, Sweden
Available from: 2017-12-05 Created: 2017-12-05 Last updated: 2018-08-24Bibliographically approved
Suveer, A., Sladoje, N., Lindblad, J., Dragomir, A. & Sintorn, I.-M. (2016). Automated detection of cilia in low magnification transmission electron microscopy images using template matching. In: Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on: . Paper presented at IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2016 (pp. 386-390). IEEE
Open this publication in new window or tab >>Automated detection of cilia in low magnification transmission electron microscopy images using template matching
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2016 (English)In: Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on, IEEE, 2016, p. 386-390Conference paper, Published paper (Other academic)
Abstract [en]

Ultrastructural analysis using Transmission Electron Microscopy (TEM) is a common approach for diagnosing primary ciliary dyskinesia. The manually performed diagnostic procedure is time consuming and subjective, and automation of the process is highly desirable. We aim at automating the search for plausible cilia instances in images at low magnification, followed by acquisition of high magnification images of regions with detected cilia for further analysis. This paper presents a template matching based method for automated detection of cilia objects in low magnification TEM images, where object radii do not exceed 10 pixels. We evaluate the performance of a series of synthetic templates generated for this purpose by comparing automated detection with results manually created by an expert pathologist. The best template achieves a detection at equal error rate of 47% which suffices to identify densely populated cilia regions suitable for high magnification imaging.

Place, publisher, year, edition, pages
IEEE, 2016
Series
IEEE International Symposium on Biomedical Imaging, ISSN 1945-7928
Keywords
Image resolution, Transmission Electron Microscopy, Object detection, Shape, Image analysis, Template matching
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing; Computerized Image Analysis
Identifiers
urn:nbn:se:uu:diva-308090 (URN)10.1109/ISBI.2016.7493289 (DOI)000386377400093 ()9781479923496 (ISBN)9781479923502 (ISBN)
Conference
IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2016
Available from: 2016-11-23 Created: 2016-11-23 Last updated: 2018-08-24Bibliographically approved
Lindblad, J., Sladoje, N., Suveer, A., Dragomir, A. & Sintorn, I.-M. (2015). High-resolution reconstruction by feature distance minimization from multiple views of an object. In: Proc. 5th International Conference on Image Processing Theory, Tools and Applications: . Paper presented at IPTA 2015, November 10–13, Orléans, France (pp. 29-34). Piscataway, NJ: IEEE
Open this publication in new window or tab >>High-resolution reconstruction by feature distance minimization from multiple views of an object
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2015 (English)In: Proc. 5th International Conference on Image Processing Theory, Tools and Applications, Piscataway, NJ: IEEE , 2015, p. 29-34Conference paper, Published paper (Refereed)
Abstract [en]

We present a method which utilizes advantages of fuzzy object representations and image processing techniques adjusted to them, to further increase efficient utilization of image information. Starting from a number of low-resolution images of affine transformations of an object, we create its suitably defuzzified high-resolution reconstruction. We evaluate the proposed method on synthetic data, observing its performance w.r.t. noise sensitivity, influence of the number of used low-resolution images, sensitivity to object variation and to inaccurate registration. Our aim is to explore applicability of the method to real image data acquired by Transmission Electron Microscopy, in a biomedical application we are currently working on.

Place, publisher, year, edition, pages
Piscataway, NJ: IEEE, 2015
Keywords
High-resolution reconstruction; Energy minimization; Image registration; Defuzzification
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-267295 (URN)10.1109/IPTA.2015.7367090 (DOI)000380472700003 ()9781479986361 (ISBN)
Conference
IPTA 2015, November 10–13, Orléans, France
Funder
VINNOVA
Available from: 2016-01-12 Created: 2015-11-19 Last updated: 2016-08-24Bibliographically approved
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