Fluorescence-based microscopy as one of the standard tools in biomedical research benefits more and more from super-resolution methods, which offer enhanced spatial resolution allowing insights into new biological processes. A typical drawback of using these methods is the need for new, complex optical set-ups. This becomes even more significant when using two-photon fluorescence excitation, which offers deep tissue imaging and excellent z-sectioning. We show that the generation of striped-illumination patterns in two-photon laser scanning microscopy can readily be exploited for achieving optical super-resolution and contrast enhancement using open-source image reconstruction software. The special appeal of this approach is that even in the case of a commercial two-photon laser scanning microscope no optomechanical modifications are required to achieve this modality. Modifying the scanning software with a custom-written macro to address the scanning mirrors in combination with rapid intensity switching by an electro-optic modulator is sufficient to accomplish the acquisition of two-photon striped-illumination patterns on an sCMOS camera. We demonstrate and analyse the resulting resolution improvement by applying different recently published image resolution evaluation procedures to the reconstructed filtered widefield and super-resolved images. This article is part of the Theo Murphy meeting issue 'Super-resolution structured illumination microscopy (part 1)'.

• Keywords
• SIM, laser scanning fluorescence microscopy, multi-photon fluorescence excitation, structured illumination microscopy, super-resolution optical microscopy,
• MeSH
• Algorithms MeSH
• Convallaria ultrastructure   MeSH
• Kidney ultrastructure   MeSH
• Microscopy, Fluorescence, Multiphoton instrumentation   methods   statistics & numerical data   MeSH
• Mice MeSH
• Optical Phenomena MeSH
• Optical Devices MeSH
• Image Processing, Computer-Assisted methods   statistics & numerical data   MeSH
• Software MeSH
• Animals MeSH
• Check Tag
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH

Chromosome pairing in meiosis usually starts in the vicinity of the telomere attachment to the nuclear membrane and congregation of telomeres in the leptotene bouquet is believed responsible for bringing homologue pairs together. In a heterozygote for an inversion of a rye (Secale cereale L.) chromosome arm in wheat, a distal segment of the normal homologue is capable of chiasmate pairing with its counterpart in the inverted arm, located near the centromere. Using 3D imaging confocal microscopy, we observed that some telomeres failed to be incorporated into the bouquet and occupied various positions throughout the entire volume of the nucleus, including the centromere pole. Rye telomeres appeared ca. 21 times more likely to fail to be included in the telomere bouquet than wheat telomeres. The frequency of the out-of-bouquet rye telomere position in leptotene was virtually identical to the frequency of telomeres deviating from Rabl's orientation in the nuclei of somatic cells, and was similar to the frequency of synapsis of the normal and inverted chromosome arms, but lower than the MI pairing frequency of segments of these two arms normally positioned across the volume of the nucleus. Out-of-position placement of the rye telomeres may be responsible for reduced MI pairing of rye chromosomes in hybrids with wheat and their disproportionate contribution to aneuploidy, but appears responsible for initiating chiasmate pairing of distantly positioned segments of homology in an inversion heterozygote.

• Keywords
• 3D FISH, Centromere, Leptotene bouquet, Pairing initiation, Telomere,
• MeSH
• Cell Nucleus genetics   ultrastructure   MeSH
• Centromere chemistry   ultrastructure   MeSH
• Chimera genetics   MeSH
• Chromosome Inversion * MeSH
• Chromosomes, Plant chemistry   ultrastructure   MeSH
• Species Specificity MeSH
• Heterozygote MeSH
• In Situ Hybridization, Fluorescence MeSH
• Microscopy, Confocal MeSH
• Chromosome Pairing MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Meiotic Prophase I * MeSH
• Triticum genetics   ultrastructure   MeSH
• Plant Cells metabolism   ultrastructure   MeSH
• Telomere chemistry   ultrastructure   MeSH
• Secale genetics   ultrastructure   MeSH
• Imaging, Three-Dimensional methods   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH

In this paper we present a three-dimensional (3D) morphometrical assessment of human tibia sexual dimorphism based on whole bone digital representation. To detect shape-size and shape differences between sexes, we used geometric morphometric tools and colour-coded surface deviation maps. The surface-based methodology enabled analysis of sexually dimorphic features throughout the shaft and articular ends of the tibia. The overall study dataset consisted of 183 3D models of adult tibiae from three Czech population subsets, dating to the early medieval (9-10th century) (N = 65), early 20th century (N = 61) and 21st-century (N = 57). The time gap between the chronologically most distant and contemporary datasets was more than 1200 years. The results showed that, in all three datasets, sexual dimorphism was pronounced. There were some sex-dimorphic characteristics common to all three samples, such as tuberosity protrusion, anteriorly bowed shaft and relatively larger articular ends in males. Diachronic comparisons also revealed substantial shape variation related to the most dimorphic area. Male/female distinctions showed a consistent temporal trend regarding the location of dimorphic areas (shifting distally with time), while the maximal deviation between male and female digitized surfaces fluctuated and reached the lowest level in the 21st-century sample. Sex determination on a whole-surface basis yielded the lowest return of correct sex assignment in the 20th-century group, which represented the lowest socioeconomic status. The temporal variation could be attributed to changes in living conditions, the decreasing lower limb loading/labour division in the last 12 centuries having the greatest effect. Overall, the results showed that a surface-based approach is successful for analysing complex long bone geometry.

• MeSH
• Principal Component Analysis methods   MeSH
• Anthropometry instrumentation   methods   MeSH
• History, 20th Century MeSH
• History, 21st Century MeSH
• History, Medieval MeSH
• Adult MeSH
• Humans MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Sex Characteristics * MeSH
• Tibia anatomy & histology   physiology   MeSH
• Sex Determination by Skeleton instrumentation   methods   MeSH
• Imaging, Three-Dimensional instrumentation   methods   MeSH
• Check Tag
• History, 20th Century MeSH
• History, 21st Century MeSH
• History, Medieval MeSH
• Adult MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Historical Article MeSH

Similar to the medical imaging community, the bioimaging community has recently realized the need to benchmark various image analysis methods to compare their performance and assess their suitability for specific applications. Challenges sponsored by prestigious conferences have proven to be an effective means of encouraging benchmarking and new algorithm development for a particular type of image data. Bioimage analysis challenges have recently complemented medical image analysis challenges, especially in the case of the International Symposium on Biomedical Imaging (ISBI). This review summarizes recent progress in this respect and describes the general process of designing a bioimage analysis benchmark or challenge, including the proper selection of datasets and evaluation metrics. It also presents examples of specific target applications and biological research tasks that have benefited from these challenges with respect to the performance of automatic image analysis methods that are crucial for the given task. Finally, available benchmarks and challenges in terms of common features, possible classification and implications drawn from the results are analysed.

• MeSH
• Algorithms MeSH
• Benchmarking * MeSH
• Databases, Factual MeSH
• Microscopy, Fluorescence instrumentation   methods   standards   MeSH
• Humans MeSH
• Molecular Imaging instrumentation   methods   standards   MeSH
• Image Processing, Computer-Assisted methods   statistics & numerical data   MeSH
• Pattern Recognition, Automated statistics & numerical data   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH

INTRODUCTION: The aim of this study was to determine the reproducibility and accuracy of linear measurements on 2 types of dental models derived from cone-beam computed tomography (CBCT) scans: CBCT images, and Anatomodels (InVivoDental, San Jose, Calif); these were compared with digital models generated from dental impressions (Digimodels; Orthoproof, Nieuwegein, The Netherlands). The Digimodels were used as the reference standard. METHODS: The 3 types of digital models were made from 10 subjects. Four examiners repeated 37 linear tooth and arch measurements 10 times. Paired t tests and the intraclass correlation coefficient were performed to determine the reproducibility and accuracy of the measurements. RESULTS: The CBCT images showed significantly smaller intraclass correlation coefficient values and larger duplicate measurement errors compared with the corresponding values for Digimodels and Anatomodels. The average difference between measurements on CBCT images and Digimodels ranged from -0.4 to 1.65 mm, with limits of agreement values up to 1.3 mm for crown-width measurements. The average difference between Anatomodels and Digimodels ranged from -0.42 to 0.84 mm with limits of agreement values up to 1.65 mm. CONCLUSIONS: Statistically significant differences between measurements on Digimodels and Anatomodels, and between Digimodels and CBCT images, were found. Although the mean differences might be clinically acceptable, the random errors were relatively large compared with corresponding measurements reported in the literature for both Anatomodels and CBCT images, and might be clinically important. Therefore, with the CBCT settings used in this study, measurements made directly on CBCT images and Anatomodels are not as accurate as measurements on Digimodels.

• MeSH
• Cephalometry statistics & numerical data   MeSH
• Humans MeSH
• Cone-Beam Computed Tomography statistics & numerical data   MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Surface Properties MeSH
• Reproducibility of Results MeSH
• Software MeSH
• Imaging, Three-Dimensional statistics & numerical data   MeSH
• Tooth Crown anatomy & histology   MeSH
• Models, Dental * MeSH
• Dental Arch anatomy & histology   MeSH
• Dental Impression Technique statistics & numerical data   MeSH
• Tooth anatomy & histology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH

INTRODUCTION: The process of fabricating physical medical skull models requires many steps, each of which is a potential source of geometric error. The aim of this study was to demonstrate inaccuracies and differences caused by DICOM to STL conversion in additively manufactured medical skull models. MATERIAL AND METHODS: Three different institutes were requested to perform an automatic reconstruction from an identical DICOM data set of a patients undergoing tumour surgery into an STL file format using their software of preference. The acquired digitized STL data sets were assessed and compared and subsequently used to fabricate physical medical skull models. The three fabricated skull models were then scanned, and differences in the model geometries were assessed using established CAD inspection software methods. RESULTS: A large variation was noted in size and anatomical geometries of the three physical skull models fabricated from an identical (or "a single") DICOM data set. CONCLUSIONS: A medical skull model of the same individual can vary markedly depending on the DICOM to STL conversion software and the technical parameters used. Clinicians should be aware of this inaccuracy in certain applications.

• Keywords
• Additive-manufacturing, Bio-modelling, CBCT, DICOM, STL,
• MeSH
• Algorithms MeSH
• Models, Anatomic * MeSH
• Computer-Aided Design statistics & numerical data   MeSH
• Cephalometry statistics & numerical data   MeSH
• Skull anatomy & histology   MeSH
• Humans MeSH
• Mandible anatomy & histology   MeSH
• Nasal Cavity anatomy & histology   MeSH
• Orbit anatomy & histology   MeSH
• Cone-Beam Computed Tomography statistics & numerical data   MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Surface Properties MeSH
• Radiology Information Systems statistics & numerical data   MeSH
• Maxillary Sinus anatomy & histology   MeSH
• Software MeSH
• Imaging, Three-Dimensional statistics & numerical data   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

The purpose of this study is (1) to introduce a new approach for edge detection in orthopantograms (OPGs) and an improved automatic parameter selector for common edge detectors, (2) to present a comparison between our novel approach with common edge detectors and (3) to provide faster outputs without compromising quality. A new approach for edge detection based on statistical measures was introduced: (1) a set of N edge detection results is calculated from a given input image and a selected type of edge detector, (2) N correspondence maps are constructed from N edge detection results, (3) probabilities and average probabilities are computed, (4) an overall correspondence is evaluated for each correspondence map and (5) the correspondence map providing the best overall correspondence is taken as the result of edge detection procedure. A comparison with common edge detectors (the Roberts, Prewitt, Sobel, Laplacian of the Gaussian and Canny methods) with various parameter settings (304 combinations for each test image) was carried out. The methods were assessed objectively [edge mismatch error (EME), modified Hausdorff distance (MHD) and principal component analysis] and subjectively by experts in dentistry and based on time demands. The suitability of the new approach for edge detection in OPGs was confirmed by experts. The current conventional methods in edge detection in OPGs are inadequate (none of the tested methods reach an EME value or MHD value below 0.1). Our proposed approach for edge detection shows promising potential for its implementation in clinical dentistry. It enhances the accuracy of OPG interpretation and advances diagnosis and treatment planning.

• Keywords
• computer-assisted image processing, medical imaging, panoramic radiography,
• MeSH
• Algorithms MeSH
• Principal Component Analysis MeSH
• Anatomic Landmarks diagnostic imaging   MeSH
• Artifacts MeSH
• Time Factors MeSH
• Jaw Cysts diagnostic imaging   MeSH
• Tooth Extraction MeSH
• Humans MeSH
• Normal Distribution MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Probability MeSH
• Radiography, Panoramic statistics & numerical data   MeSH
• Radiographic Image Interpretation, Computer-Assisted methods   MeSH
• Dental Caries diagnostic imaging   MeSH
• Tooth, Supernumerary diagnostic imaging   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH

A new reconstruction method for parallel MRI called PROBER is proposed. The method PROBER works in an image domain similar to methods based on Sensitivity Encoding (SENSE). However, unlike SENSE, which first estimates the spatial sensitivity maps, PROBER approximates the reconstruction coefficients directly by B-splines. Also, B-spline coefficients are estimated at once in order to minimize the reconstruction error instead of estimating the reconstruction in each pixel independently (as in SENSE). This makes the method robust to noise in reference images. No presmoothing of reference images is necessary. The number of estimated parameters is reduced, which speeds up the estimation process. PROBER was tested on simulated, phantom, and in vivo data. The results are compared with commercial implementations of the algorithms SENSE and GRAPPA (Generalized Autocalibrating Partially Parallel Acquisitions) in terms of elapsed time and reconstruction quality. The experiments showed that PROBER is faster than GRAPPA and SENSE for images wider than 150x150 pixels for comparable reconstruction quality. With more basis functions, PROBER outperforms both SENSE and GRAPPA in reconstruction quality at the cost of slightly increased computational time.

• MeSH
• Algorithms MeSH
• Artifacts MeSH
• Time Factors MeSH
• Gadolinium DTPA MeSH
• Adult MeSH
• Phantoms, Imaging MeSH
• Head anatomy & histology   MeSH
• Thorax anatomy & histology   MeSH
• Calibration MeSH
• Contrast Media MeSH
• Humans MeSH
• Magnetic Resonance Imaging methods   MeSH
• Computer Simulation MeSH
• Image Processing, Computer-Assisted methods   statistics & numerical data   MeSH
• Image Enhancement methods   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Comparative Study MeSH
• Names of Substances
• Gadolinium DTPA MeSH
• Contrast Media MeSH

The aim of the study was a quantitative comparison of relative renal uptake and both the whole-kidney and the parenchymal transit time derived from factor analysis of image sequences and provided by standard clinical procedues. In order to extract the stable, well-interpretable factors, factor analysis was performed locally in the problem-specific time and spatial windows and the resulting factor images either evaluated directly as functional images or used as fuzzy regions of interest (ROIs) for the subsequent extraction of time-activity curves from the analysed data. The values of relative renal uptake of the left kidney measured in the functional factor images, which demonstrate the initial accumulation of activity in renal parenchyma (mean 51.0%), did not differ significantly from the values obtained by a standard method (mean 51.5%, r = 0.98, P<0.001). Whole-kidney transit time calculated using fuzzy ROI curves correlated well with the reference values (r = 0.84, P<0.001); however, both its mean value (336.5 s) and the standard deviation (151.5 s) were substantially greater than those of the values provided by a standard procedure (262.8+/-86.9 s). Parenchymal transit time calculated using ROI curves correlated better with the transit time through a wider corticomedullary region rather than through a narrow cortical region, which is decisive in a differential diagnosis of renal disorders. In general, values of transit times provided by factor analysis correlated well with those provided by reference methods but with a shift towards the higher numerical values. This may have been a consequence of a greater extent of the automatically extracted fuzzy ROIs, or of occasionally delayed accumulation in the upper calyces. Results of the study provide quantitative evidence that the factor analysis of dynamic data, even without the introduction of prior physiological information, may yield clinically relevant information. However, some basic requirements, such as sufficiently high sampling frequency and count rate, adaption of the method to a specific clinical task, and proper selection of time and spatial windows for locally performed analysis, have to be fullfilled if the method is to be successfully applied clinically.

• MeSH
• Algorithms MeSH
• Models, Biological MeSH
• Factor Analysis, Statistical MeSH
• Fuzzy Logic MeSH
• Kidney diagnostic imaging   metabolism   MeSH
• Humans MeSH
• Antibodies, Monoclonal MeSH
• Organotechnetium Compounds MeSH
• Image Processing, Computer-Assisted statistics & numerical data   MeSH
• Radiopharmaceuticals MeSH
• Radionuclide Imaging MeSH
• Kidney Function Tests MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Clinical Trial MeSH
• Research Support, Non-U.S. Gov't MeSH
• Randomized Controlled Trial MeSH
• Names of Substances
• Antibodies, Monoclonal MeSH
• Organotechnetium Compounds MeSH
• Radiopharmaceuticals MeSH
• technetium-99m-MAG3-dsFV MeSH Browser