Spheroids-three-dimensional aggregates of cells grown from a cancer cell line-represent a model of living tissue for chemotherapy investigation. Distribution of chemotherapeutics in spheroid sections was determined using the matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Proliferating or apoptotic cells were immunohistochemically labeled and visualized by laser scanning confocal fluorescence microscopy (LSCM). Drug efficacy was evaluated by comparing coregistered MALDI MSI and LSCM data of drug-treated spheroids with LSCM only data of untreated control spheroids. We developed a fiducial-based workflow for coregistration of low-resolution MALDI MS with high-resolution LSCM images. To allow comparison of drug and cell distribution between the drug-treated and untreated spheroids of different shapes or diameters, we introduced a common diffusion-related coordinate, the distance from the spheroid boundary. In a procedure referred to as "peeling", we correlated average drug distribution at a certain distance with the average reduction in the affected cells between the untreated and the treated spheroids. This novel approach makes it possible to differentiate between peripheral cells that died due to therapy and the innermost cells which died naturally. Two novel algorithms-for MALDI MS image denoising and for weighting of MALDI MSI and LSCM data by the presence of cell nuclei-are also presented.

• MeSH
• buněčné sféroidy účinky léků   MeSH
• konfokální mikroskopie metody   MeSH
• lidé MeSH
• nádory farmakoterapie   MeSH
• protinádorové látky farmakokinetika   farmakologie   MeSH
• spektrometrie hmotnostní - ionizace laserem za účasti matrice metody   MeSH
• teoretické modely MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

OBJECTIVE: T2 maps are more vendor independent than other MRI protocols. Multi-echo spin-echo signal decays to a non-zero offset due to imperfect refocusing pulses and Rician noise, causing T2 overestimation by the vendor's 2-parameter algorithm. The accuracy of the T2 estimate is improved, if the non-zero offset is estimated as a third parameter. Three-parameter Levenberg-Marquardt (LM) T2 estimation takes several minutes to calculate, and it is sensitive to initial values. We aimed for a 3-parameter fitting algorithm that was comparably accurate, yet substantially faster. METHODS: Our approach gains speed by converting the 3-parameter minimisation problem into an empirically unimodal univariate problem, which is quickly minimised using the golden section line search (GS). RESULTS: To enable comparison, we propose a novel noise-masking algorithm. For clinical data, the agreement between the GS and the LM fit is excellent, yet the GS algorithm is two orders of magnitude faster. For synthetic data, the accuracy of the GS algorithm is on par with that of the LM fit, and the GS algorithm is significantly faster. The GS algorithm requires no parametrisation or initialisation by the user. DISCUSSION: The new GS T2 mapping algorithm offers a fast and much more accurate off-the-shelf replacement for the inaccurate 2-parameter fit in the vendor's software.

• MeSH
• algoritmy MeSH
• časové faktory MeSH
• fantomy radiodiagnostické MeSH
• interpretace obrazu počítačem metody   MeSH
• lidé MeSH
• magnetická rezonanční tomografie * MeSH
• metoda nejmenších čtverců MeSH
• nádory prostaty diagnostické zobrazování   MeSH
• počítačové zpracování obrazu metody   MeSH
• poměr signál - šum MeSH
• pravděpodobnost MeSH
• regresní analýza MeSH
• reprodukovatelnost výsledků MeSH
• software MeSH
• Check Tag
• lidé MeSH
• mužské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Image registration tasks are often formulated in terms of minimization of a functional consisting of a data fidelity term penalizing the mismatch between the reference and the target image, and a term enforcing smoothness of shift between neighboring pairs of pixels (a min-sum problem). Most methods for deformable image registration use some form of interpolation between matching control points. The interpolation makes it impossible to account for isolated discontinuities in the deformation field that may appear, e.g., when a physical slice of a microscopy specimen is ruptured by the cutting tool. For registration of neighboring physical slices of microscopy specimens with discontinuities, Janácek proposed an L¹-distance data fidelity term and a total variation (TV) smoothness term, and used a graph-cut (GC) based iterative steepest descent algorithm for minimization. The L¹-TV functional is nonconvex; hence a steepest descent algorithm is not guaranteed to converge to the global minimum. Schlesinger presented transformation of max-sum problems to minimization of a dual quantity called problem power, which is--contrary to the original max-sum functional--convex. Based on Schlesinger's solution to max-sum problems we developed an algorithm for L¹-TV minimization by iterative multi-label steepest descent minimization of the convex dual problem. For Schlesinger's subgradient algorithm we proposed a novel step control heuristics that considerably enhances both speed and accuracy compared with standard step size strategies for subgradient methods. It is shown experimentally that our subgradient scheme achieves consistently better image registration than GC in terms of lower values both of the composite L¹-TV functional, and of its components, i.e., the L¹ distance of the images and the transformation smoothness TV, and yields visually acceptable results even in cases where the GC based algorithm fails. The new algorithm allows easy parallelization and can thus be sped up by running on multi-core graphic processing units.

• MeSH
• algoritmy * MeSH
• hlava anatomie a histologie   MeSH
• mikroskopie metody   MeSH
• počítačové zpracování obrazu metody   MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• přehledy MeSH

• MeSH
• lidé MeSH
• sexuální obtěžování * prevence a kontrola   MeSH
• studenti lékařství MeSH
• studium lékařství MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• novinové články MeSH

When biological specimens are cut into physical sections for three-dimensional (3D) imaging by confocal laser scanning microscopy, the slices may get distorted or ruptured. For subsequent 3D reconstruction, images from different physical sections need to be spatially aligned by optimization of a function composed of a data fidelity term evaluating similarity between the reference and target images, and a regularization term enforcing transformation smoothness. A regularization term evaluating the total variation (TV), which enables the registration algorithm to account for discontinuities in slice deformation (ruptures), while enforcing smoothness on continuously deformed regions, was proposed previously. The function with TV regularization was optimized using a graph-cut (GC) based iterative solution. However, GC may generate visible registration artifacts, which impair the 3D reconstruction. We present an alternative, multilabel TV optimization algorithm, which in the examined samples prevents the artifacts produced by GC. The algorithm is slower than GC but can be sped up several times when implemented in a multiprocessor computing environment. For image pairs with uneven brightness distribution, we introduce a reformulation of the TV-based registration, in which intensity-based data terms are replaced by comparison of salient features in the reference and target images quantified by local image entropies.

• MeSH
• algoritmy MeSH
• artefakty MeSH
• barvení a značení MeSH
• embryo nesavčí MeSH
• embryo savčí MeSH
• entropie MeSH
• konfokální mikroskopie metody   MeSH
• krysa rodu rattus MeSH
• kur domácí MeSH
• mezonefros chemie   ultrastruktura   MeSH
• mikrotomie metody   MeSH
• reprodukovatelnost výsledků MeSH
• senzitivita a specificita MeSH
• vylepšení obrazu přístrojové vybavení   metody   MeSH
• zalévání tkání do parafínu MeSH
• želvy MeSH
• zvířata MeSH
• Check Tag
• krysa rodu rattus MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

In images acquired by confocal laser scanning microscopy (CLSM), regions corresponding to the same concentration of fluorophores in the specimen should be mapped to the same grayscale levels. However, in practice, due to multiple distortion effects, CLSM images of even homogeneous specimen regions suffer from irregular brightness variations, e.g., darkening of image edges and lightening of the center. The effects are yet more pronounced in images of real biological specimens. A spatially varying grayscale map complicates image postprocessing, e.g., in alignment of overlapping regions of two images and in 3D reconstructions, since measures of similarity usually assume a spatially independent grayscale map. We present a fast correction method based on estimating a spatially variable illumination gain, and multiplying acquired CLSM images by the inverse of the estimated gain. The method does not require any special calibration of reference images since the gain estimate is extracted from the CLSM image being corrected itself. The proposed approach exploits two types of morphological filters: the median filter and the upper Lipschitz cover. The presented correction method, tested on images of both artificial (homogeneous fluorescent layer) and real biological specimens, namely sections of a rat embryo and a rat brain, proved to be very fast and yielded a significant visual improvement.

• MeSH
• algoritmy MeSH
• konfokální mikroskopie metody   MeSH
• krysa rodu rattus embryologie   MeSH
• mozek cytologie   MeSH
• počítačové zpracování obrazu metody   MeSH
• zvířata MeSH
• Check Tag
• krysa rodu rattus embryologie   MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• hodnotící studie MeSH
• práce podpořená grantem MeSH