Journal articles

1. Microarray Detection by Geometric Restoration
   Authors: Jimmy Azar, Christer Busch (1), Ingrid Carlbom
   (1) Dept. Immunology, Genetics and Pathology, UU
   Journal: Analytical Cellular Pathology, volume 35, number 5-6, pp 381-393
   Abstract: Whole-slide imaging of tissue microarrays (TMAs) holds the promise of automated image analysis of a large number of histopathological samples from a single slide. This demands high-throughput image processing to enable analysis of these tissue samples for diagnosis of cancer and other conditions. In this paper, we present a completely automated method for the accurate detection and localization of tissue cores that is based on geometric restoration of the core shapes without placing any assumptions on grid geometry. The method relies on hierarchical clustering in conjunction with the Davies-Bouldin index for cluster validation in order to estimate the number of cores in the image where from we estimate the core radius and refine this estimate using morphological granulometry. The final stage of the algorithm reconstructs circular discs from core sections such that these discs cover the entire region of each core regardless of the precise shape of the core. The results show that the proposed method is able to reconstruct core locations without any evidence of localization. Furthermore, the algorithm is more efficient than existing methods based on the Hough transform for circle detection. The algorithm's simplicity, accuracy, and computational efficiency allow for automated high-throughput analysis of microarray images.

2. Osseointegration Using Image Analysis (Osseointegration med hjälp av Datoriserad Bildanalys, in Swedish)
   Authors:  Gunilla Borgefors, Hamid Sarve, Carina B. Johansson (1), Bertil Friberg (2)
   (1) Dept. Prosthodontics/Dental Materials Science, University of Gothenburg, Gothenburg
   (2) Brånemarkkliniken, Gothenburg
   Journal: Tandläkartidningen, volume 104, number 12, pp 66-71
   Abstract: Using computerized image processing we can quantify the bone tissue around implants. In addition to quantification methods in both 2D and 3D, we have developed two new 3D visualization methods for the contact between bone and implant.

3. Fully Automated Cellular-Resolution Vertebrate Screening Platform with Parallel Animal Processing
   Authors: Tsung-Yao Chang (1), Carlos Pardo-Martin (1), Amin Allalou (2), Carolina Wählby (2), Mehmet Fatih Yanik (1)
   (1) Research Laboratory of Electronics, Massachusetts Institute of Technology, MA, USA
   (2) SciLifeLab, UU
   Journal: Lab on a Chip, volume 12, Issue 4, pp 711-716
   Abstract: The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widely used to study genetics, developmental biology, and to model various human diseases. In this article, we present a set of novel technologies that significantly increase the throughput and capabilities of our previously described vertebrate automated screening technology (VAST). We developed a robust multi-thread system that can simultaneously process multiple animals. System throughput is limited only by the image acquisition speed rather than by the fluidic or mechanical processes. We developed image recognition algorithms that fully automate manipulation of animals, including orienting and positioning regions of interest within the microscope's field of view. We also identified the optimal capillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.

4. Salience Adaptive Structuring Elements
   Authors: Vladimir Curic, Cris L. Luengo Hendriks, Gunilla Borgefors
   Journal: IEEE Journal on Selected Topics in Signal Processing, volume 6, number 7, pp 809-819
   Abstract: Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.

5. Pharmacological Characterization of 18F-labeled Vorozole Analogs
   Authors: Håkan Hall (1), Kayo Takahashi(2), Maria Erlandsson (3,4), Sergio Estrada (1), Pasha Razifar (5), Elisabeth Bergström (6), Bengt Långström(4)
   (1) Dept. of Medicinal Chemistry, Preclinical PET Platform, UU
   (2) RIKEN Center for Molecular Imaging Science, Kobe, Japan
   (3) Dept. of Clinical Physiology, Nuclear Medicine & PET and Cluster for Molecular Imaging Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
   (4) Dept. of Biochemistry and Organic Chemistry, UU
   (5) RM-Medic-Tech AB, Uppsala
   (6) Uppsala Imanet, Uppsala
   Journal: Journal of labelled compounds & radiopharmaceuticals, volume 55, number 14, pp 484-490
   Abstract: Two 18F-labeled analogs of vorozole ([18F]FVOZ and [18F]FVOO) have been developed as potential tools for the in vivo characterization of aromatase. The pharmacological properties of these radioligands were evaluated using in vitro binding and in vivo distribution studies in the rat and primate. Saturation binding studies using rat ovary gave KD and Bmax values of and , respectively, for [18F]FVOZ, and and , respectively, for [18F]FVOO. Organ distribution studies in rats showed the highest accumulation in the adrenal glands, with standardized uptake values (SUVs) of 15 to 20, followed by ovaries and liver with SUVs of approximately 5. Ex vivo and in vitro autoradiography of the rat brain showed specific binding of both [18F]FVOZ and [18F]FVOO mainly in the amygdala. Positron emission tomography (PET) studies were performed in the Rhesus monkey, and these showed displaceable binding in the amygdala and the hypothalamus preoptic area. The PET images were also analyzed using masked volume-wise principal component analysis. These studies suggest that [18F]FVOZ might be a suitable tracer for the study of aromatase in vitro and in vivo, and could be an alternative to [11C]vorozole in human PET studies.

6. Learning Histopathological Patterns
   Authors: Andreas Kårsnäs, Anders L. Dahl(1), Rasmus Larsen(1)
   (1) Technical University of Denmark, Department of Informatics and Mathematical Modelling, Technical University of Denmark, Copenhagen, Denmark
   Journal: Journal of Pathology Informatics, number 2:12
   Abstract: Aims: The aim was to demonstrate a method for automated image analysis of immunohistochemically stained tissue samples for extracting features that correlate with patient disease. We address the problem of quantifying tumor tissue and segmenting and counting cell nuclei. Materials and Methods: Our method utilizes a flexible segmentation method based on sparse coding trained from representative image samples. Nuclei counting is based on a nucleus model that takes size, shape, and nucleus probability into account. Nuclei clustering and overlays are resolved using a gray-weighted distance transform. We obtain a probability measure for pixels belonging to a nucleus from our segmentation procedure. Experiments are carried out on two sets of immunohistochemically stained images - one set based on the estrogen receptor (ER) and the other on antigen KI-67. For the nuclei separation we have selected 207 ER image samples from 58 tissue micro array-cores corresponding to 58 patients and 136 KI-67 image samples also from 58 cores. The images are hand-annotated by marking the center position of each nucleus. For the ER data we have a total of 1006 nuclei and for the KI-67 we have 796 nuclei. Segmentation performance was evaluated in terms of missing nuclei, falsely detected nuclei, and multiple detections. The proposed method is compared to state-of-the-art Bayesian classification. Statistical analysis used: The performance of the proposed method and a state-of-the-art algorithm including variations thereof is compared using the Wilcoxon rank sum test. Results: For both the ER experiment and the KI-67 experiment the proposed method exhibits lower error rates than the state-of-the-art method. Total error rates were 4.8 % and 7.7 % in the two experiments, corresponding to an average of 0.23 and 0.45 errors per image, respectively. The Wilcoxon rank sum tests show statistically significant improvements over the state-of-the-art method. Conclusions: We have demonstrated a method and obtained good performance compared to state-of-the-art nuclei separation. The segmentation procedure is simple, highly flexible, and we demonstrate how it, in addition to the nuclei separation, can perform precise segmentation of cancerous tissue. The complexity of the segmentation procedure is linear in the image size and the nuclei separation is linear in the number of nuclei. Additionally the method can be parallelized to obtain high-speed computations.

7. Segmentation of Virus Particle Candidates in Transmission Electron Microscopy Images
   Authors: Gustaf Kylberg, Mats Uppström (1), and Ida-Maria Sintorn
   (1) Vironova AB, Stockholm
   Journal: Journal of Microscopy, volume 245, Issue 2, pages 140-147
   Abstract: In this paper, we present an automatic segmentation method that detects virus particles of various shapes in transmission electron microscopy images. The method is based on a statistical analysis of local neighbourhoods of all the pixels in the image followed by an object width discrimination and finally, for elongated objects, a border refinement step. It requires only one input parameter, the approximate width of the virus particles searched for. The proposed method is evaluated on a large number of viruses. It successfully segments viruses regardless of shape, from polyhedral to highly pleomorphic.

8. Automatic Measurement of Compression Wood Cell Attributes in Fluorescence Microscopy Images
   Authors: Bettina Selig, Cris L. Luengo Hendriks, Stig Bardage (1), Geoffrey Daniel (2), Gunilla Borgefors
   (1) SP Technical Research Institute of Sweden, SP Trätek, Stockholm
   (2) Dept. of Wood Science, SLU, Uppsala
   Journal: Journal of Microscopy, volume 246, number 3, pp 298-308
   Abstract: This paper presents a new automated method for analyzing compression wood fibers in fluorescence microscopy. Abnormal wood known as compression wood is present in almost every softwood tree harvested. Compression wood fibers show a different cell wall morphology and chemistry compared to normal wood fibers, and their mechanical and physical characteristics are considered detrimental for both construction wood and pulp and paper purposes. Currently there is the need for improved methodologies for characterization of lignin distribution in wood cell walls, such as from compression wood fibers, that will allow for a better understanding of fiber mechanical properties. Traditionally, analysis of fluorescence microscopy images of fiber cross-sections has been done manually, which is time consuming and subjective. Here, we present an automatic method, using digital image analysis, that detects and delineates softwood fibers in fluorescence microscopy images, dividing them into cell lumen, normal and highly lignified areas. It also quantifies the different areas, as well as measures cell wall thickness. The method is evaluated by comparing the automatic with a manual delineation. While the boundaries between the various fiber wall regions are detected using the automatic method with precision similar to inter and intra expert variability, the position of the boundary between lumen and the cell wall has a systematic shift that can be corrected. Our method allows for transverse structural characterization of compression wood fibers, which may allow for improved understanding of the micro-mechanical modeling of wood and pulp fibers.

9. Coverage Segmentation Based on Linear Unmixing and Minimization of Perimeter and Boundary Thickness
   Authors: Joakim Lindblad (1), Nataša Sladoje (1)
   (1) Faculty of Technical Sciences, University of Novi Sad, Serbia
   Journal: Pattern Recognition Letters, volume 33, number 6, pp 728-738
   Abstract: We present a method for coverage segmentation, where the, possibly partial, coverage of each image element by each of the image components is estimated. The method combines intensity information with spatial smoothness criteria. A model for linear unmixing of image intensities is enhanced by introducing two additional conditions: (i) minimization of object perimeter, leading to smooth object boundaries, and (ii) minimization of the thickness of the fuzzy object boundary, and to some extent overall image fuzziness, to respond to a natural assumption that imaged objects are crisp, and that fuzziness is mainly due to the imaging and digitization process. The segmentation is formulated as an optimization problem and solved by the Spectral Projected Gradient method. This fast, deterministic optimization method enables practical applicability of the proposed segmentation method. Evaluation on both synthetic and real images confirms very good performance of the algorithm.
10. Distance Transform Computation for Digital Distance Functions
    Authors: Robin Strand, Nicolas Normand (1)
    (1) LUNAM Université, Université de Nantes, Nantes, France
    Journal: Theoretical Computer Science,volume 448, pp 80-93
    Abstract: In image processing, the distance transform (DT), in which each object grid point is assigned the distance to the closest background grid point, is a powerful and often used tool. In this paper, distance functions defined as minimal cost-paths are used and a number of algorithms that can be used to compute the DT are presented. We give proofs of the correctness of the algorithms.

11. A Non-destructive X-ray Microtomography Approach for Measuring Fibre Length in Short-fibre Composites
    Authors: Arttu Miettinen (1), Cris L. Luengo Hendriks, Gary Chinga-Carrasco (2), E. Kristofer Gamstedt (3), Markku Kataja (1)
    (1) Dept. of Physics, University of Jyväskylä, Finland
    (2) Paper and Fibre Research Institute, Trondheim, Norway
    (3) Dept. of Engineer Sciences, UU
    Journal: Composites Science And Technology, volume 72, number 15, pp 1901-1908
    Abstract: An improved method based on X-ray microtomography is developed for estimating fibre length distribution of short-fibre composite materials. In particular, a new method is proposed for correcting the biasing effects caused by the finite sample size as defined by the limited field of view of the tomographic devices. The method is first tested for computer generated fibre data and then applied in analyzing the fibre length distribution in three different types of wood fibre reinforced composite materials. The results were compared with those obtained by an independent method based on manual registration of fibres in images from a light microscope. The method can be applied in quality control and in verifying the effects of processing parameters on the fibre length and on the relevant mechanical properties of short fibre composite materials, e.g. stiffness, strength and fracture toughness.

12. Non-Random mtDNA Segregation Patterns Indicate a Metastable Heteroplasmic Segregation Unit in m.3243AG Cybrid Cells
    Authors: Anton K. Raap (1), Roshan S. Jahangir Tafrechi (1), Frans M. van de Rijke (1), Angela Pyle (2), Carolina Wählby (3), Karoly Szuhai (1), Raimond B. G. Ravelli (1), René F. M. de Coo (4), Harsha K. Rajasimha (5), Mats Nilsson (6), Patrick F. Chinnery (2), David C. Samuels (5), George M. C. Janssen (1)
    (1) Dept. of Molecular Cell Biology, Leiden University Medical Centre, Leiden, The Netherlands
    (2) Wellcome Trust Centre for Mitochondrial Research, Newcastle University, Newcastle upon Tyne, United Kingdom
    (3) Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
    (4) Dept of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
    (5) Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
    (6) Dept. of Immunology, Genetics and Pathology, UU
    Journal: PLoS ONE, volume 7, number 12, pp e52080
    Abstract: Many pathogenic mitochondrial DNA mutations are heteroplasmic, with a mixture of mutated and wild-type mtDNA present within individual cells. The severity and extent of the clinical phenotype is largely due to the distribution of mutated molecules between cells in different tissues, but mechanisms underpinning segregation are not fully understood. To facilitate mtDNA segregation studies we developed assays that measure m.3243AG point mutation loads directly in hundreds of individual cells to determine the mechanisms of segregation over time. In the first study of this size, we observed a number of discrete shifts in cellular heteroplasmy between periods of stable heteroplasmy. The observed patterns could not be parsimoniously explained by random mitotic drift of individual mtDNAs. Instead, a genetically metastable, heteroplasmic mtDNA segregation unit provides the likely explanation, where stable heteroplasmy is maintained through the faithful replication of segregating units with a fixed wild-type/m.3243A>G mutant ratio, and shifts occur through the temporary disruption and re-organization of the segregation units. While the nature of the physical equivalent of the segregation unit remains uncertain, the factors regulating its organization are of major importance for the pathogenesis of mtDNA diseases.

13. Visualising Individual Sequence-specific Protein-DNA Interactions in situ
    Authors: Irene Weibrecht (1,2), Milan Gavrilovic (2), Lena Lindbom (1,2), Ulf Landegren (1,2), Carolina Wählby (2), Ola Söderberg (1,2)
    (1) Dept. of Immunology, Genetics and Pathology, UU
    (2) SciLifeLab, UU
    Journal: New Biotechnology, volume 29, number 5, pp 589-598
    Abstract: Gene expression-a key feature for modulating cell fate-is regulated in part by histone modifications, which modulate accessibility of the chromatin to transcription factors. Until now, protein-DNA interactions (PDIs) have mostly been studied in bulk without retrieving spatial information from the sample or with poor sequence resolution. New tools are needed to reveal proteins interacting with specific DNA sequences in situ for further understanding of the orchestration of transcriptional control within the nucleus. We present herein an approach to visualise individual PDIs within cells, based on the in situ proximity ligation assay (PLA). This assay, previously used for the detection of protein-protein interactions in situ, was adapted for analysis of target PDIs, using padlock probes to identify unique DNA sequences in complex genomes. As a proof-of-principle we detected histone H3 interacting with a 26bp consensus sequence of the Alu-repeat abundantly expressed in the human genome, but absent in mice. However, the mouse genome contains a highly similar sequence, providing a model system to analyse the selectivity of the developed methods. Although efficiency of detection currently is limiting, we conclude that in situ PLA can be used to achieve a highly selective analysis of PDIs in single cells.

14. An Image Analysis Toolbox for High-throughput C. Elegans Assays
    Authors: Carolina Wählby (1,2), Lee Kamentsky (2), Zihan H. Liu (2), Tammy Riklin-Raviv (3), Annie L. Conery (4), Eyleen O'Rourke (4), Katherine Sokolnicki (2), Orane Visvikis (5), Vebjorn Ljosa (2), Javier E. Irazoqui (5), Polina Golland (3), Gary Ruvkun (4), Frederick M. Ausubel (4), Anne E. Carpenter (2)
    (1) SciLifeLab, UU
    (2) Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
    (3) Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
    (4) Dept. of Molecular Biology and Center for Computational and Integrative Biology, Mass. General Hospital, Boston, MA, USA
    (5) Developmental Immunology Program, Dept of Pediatrics, Mass. General Hospital, Boston, MA, USA
    Journal: Nature Methods, volume 9, number 7, pp 714-716
    Abstract: We present a toolbox for high-throughput screening of image-based Caenorhabditis elegans phenotypes. The image analysis algorithms measure morphological phenotypes in individual worms and are effective for a variety of assays and imaging systems from different laboratories. The toolbox is available via the open-source CellProfiler project and enables objective scoring of whole-animal high-throughput image-based assays using this unique model organism for the study of diverse biological pathways relevant to human disease.