Filippo Piccinini

Multi‐image based method to correct vignetting effect in light microscopy images

Vignetting is the radial attenuation effect of the images brightness intensity from the center of the optical axis to the edges. To perform quantitative image analyses it is mandatory to take into account this effect, intrinsic of the acquisition system. Many image processing steps, such as segmentation and object tracking, are strongly affected by vignetting and the effect becomes particularly evident in mosaicing. The most common approach to compensate the attenuation of the images brightness intensity is to estimate the vignetting function from a homogeneous reference object, typically an empty field, and to use it to normalize the images acquired under the same microscope set‐up conditions. However, several reasons lead to the use of image‐based methods to estimate the vignetting function from the images themselves. In this work, we propose an effective multi‐image based method suitable for real‐time applications. It is designed to correct vignetting in wide field light microscopy images. The vignetting function is computed stemming from a background built incrementally from the proposed background segmentation algorithm, validated on several manually segmented images. The extensive experiments carried out using cell cultures, histological samples and synthetic images prove that our method almost always yields the best results and in worst cases are comparable to those achieved by using homogeneous reference objects.

Automated image mosaics by non-automated light microscopes: the MicroMos software tool

Light widefield microscopes and digital imaging are the basis for most of the analyses performed in every biological laboratory. In particular, the microscopes user is typically interested in acquiring high‐detailed images for analysing observed cells and tissues, meanwhile being representative of a wide area to have reliable statistics. The microscopist has to choose between higher magnification factor and extension of the observed area, due to the finite size of the cameras field of view. To overcome the need of arrangement, mosaicing techniques have been developed in the past decades for increasing the cameras field of view by stitching together more images. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Or alternatively, the methods are conceived just to provide visually pleasant mosaics not suitable for quantitative analyses. This work presents a tool for building mosaics of images acquired with nonautomated light microscopes. The method proposed is based on visual information only and the mosaics are built by incrementally stitching couples of images, making the approach available also for online applications. Seams in the stitching regions as well as tonal inhomogeneities are corrected by compensating the vignetting effect. In the experiments performed, we tested different registration approaches, confirming that the translation model is not always the best, despite the fact that the motion of the sample holder of the microscope is apparently translational and typically considered as such. The methods implementation is freely distributed as an open source tool called MicroMos. Its usability makes building mosaics of microscope images at subpixel accuracy easier. Furthermore, optional parameters for building mosaics according to different strategies make MicroMos an easy and reliable tool to compare different registration approaches, warping models and tonal corrections.

Extended depth of focus in optical microscopy: Assessment of existing methods and a new proposal

Due to depth of focus constraints, the acquisition of a single 2‐D completely in‐focus image of 3‐D objects characterized by a relevant depth dimension is not possible with a standard light microscope. Since the Seventies numerous methods have been proposed to overcome this problem, mainly through different fusion processing techniques to extend the microscopes depth of focus. However, given a specific application, it is very difficult to know which method yields the best results because there are no validated approaches or tested metrics that are suitable for real world cases typically lacking in a reference ground truth. Although the Universal Quality Index (UQI) is widely used to evaluate output quality in image processing, it requires a reference ground truth. Some UQI extensions have been proposed to evaluate the output of fusion methods without a ground truth, but sufficient analyses have not been carried out to confirm their equivalence to the standard UQI in terms of (evaluation) performance. We propose a new method to extend the microscopes depth of focus and, using synthetic stacks of images with ground truth attached, show that it is superior to state‐of‐the‐art methods. We also demonstrate that the output of metrics proposed as UQI extensions is different from that of the UQI. Finally, we validate a new approach to evaluate extended depth of focus methods using real world stacks of slices, as per the UQI, but without the need for a reference ground truth. Microsc. Res. Tech.

Mosaicing of optical microscope imagery based on visual information

Tools for high-throughput high-content image analysis can simplify and expedite different stages of biological experiments, by processing and combining different information taken at different time and in different areas of the culture. Among the most important in this field, image mosaicing methods provide the researcher with a global view of the biological sample in a unique image. Current approaches rely on known motorized x-y stage offsets and work in batch mode, thus jeopardizing the interaction between the microscopic system and the researcher during the investigation of the cell culture. In this work we present an approach for mosaicing of optical microscope imagery, based on local image registration and exploiting visual information only. To our knowledge, this is the first approach suitable to work on-line with non-motorized microscopes. To assess our method, the quality of resulting mosaics is quantitatively evaluated through on-purpose image metrics. Experimental results show the importance of model selection issues and confirm the soundness of our approach.

Vignetting correction by exploiting an optical microscopy image sequence

Vignetting is one of the most common problem that may affect digital imaging. The effect becomes particularly evident when images are stitched together to increase the cameras field of view (e.g., when building a mosaic), where it can lead to errors in automatic analyses. To correct the effect, the most common approach is to acquire an empty field image in advance that is used later to perform a flat field correction on every subsequently acquired image. However, in several cases, such as when dealing with off-line images or with real time acquisitions, this is not a viable option. The method we propose relies on a non parametric model to characterize in real time the vignetting function from the specimen itself, by using our foreground/background segmentation algorithm. The function is computed over a background built incrementally, detecting regions free of objects of interest. The experiments carried out using cell cultures and histological samples prove that our method yields results at least comparable to those achieved by using empty field.

Illumination field estimation through background detection in optical microscopy

Automated microscopic image analysis techniques are increasingly gaining attention in the field of biological imaging. The success of these applications mostly depends on the earlier image processing steps applied to the acquired images, aiming at enhancing image content while performing noise and artifacts removal. One such artifact is the vignetting effect that in general occurs in most imaging sensors due to an uneven illumination of the scene being imaged. As a consequence, images are usually lighter near the optical center and darker at image borders. This effect is particularly evident when stitching images into a mosaic in order to increase the field of view of the microscope. The existing approaches deal with either the parametric model of the known light distribution or the estimation of the illumination field based on just one image or a sequence of empty-field images. These approaches are only feasible when the acquisition apparatus is at ones disposal. We propose a non parametric and general purpose approach, without using prior information about the light distribution, where the illumination field is estimated from the background, that is built automatically stemming from a sequence of images containing even the objects of interest.

Vignetting and photo-bleaching correction in automated fluorescence microscopy from an array of overlapping images

We propose a novel acquisition scheme and non-parametric multi-image based method for correcting illumination in fluorescence images. Our approach measures changes in intensity of the subject by moving the microscope stage at regularly spaced intervals, and exploits this information to learn the correction function. The acquisition process and learning are performed prior to imaging, and take only a few minutes. Afterwards, images can be corrected for vignetting and photobleaching effects on the fly. Our approach can be implemented in any microscope with a motorized stage, and does not require a reference calibration slide. Experiments demonstrate that our method outperforms standard approaches to illumination correction.

Semi-quantitative monitoring of confluence of adherent mesenchymal stromal cells on calcium-phosphate granules by using widefield microscopy images.

The analysis of cell confluence and proliferation is essential to design biomaterials and scaffolds to use as bone substitutes in clinical applications. Accordingly, several approaches have been proposed in the literature to estimate the area of the scaffold covered by cells. Nevertheless, most of the approaches rely on sophisticated equipment not employed for routine analyses, while the rest of them usually do not provide significant statistics about the cell distribution. This research aims at studying confluence and proliferation of mesenchymal stromal cells (MSC) adherent on OSPROLIFE®, a commercial biomaterial in the form of granules. In particular, we propose a Computer Vision approach that can routinely be employed to monitor the surface of the single granules covered by cells because only a standard widefield fluorescent microscope is required. In order to acquire significant statistics data, we analyse wide-area images built by using MicroMos v2.0, an updated version of a previously published software specific for stitching brightfield and phase-contrast images manually acquired via a widefield microscope. In particular, MicroMos v2.0 permits to build accurate “mosaics” of fluorescent images, after correcting vignetting and photo-bleaching effects, providing a consistent representation of a sample region containing numerous granules. Then, our method allows to make automatically a statistically significant estimate of the percentage of the area of the single granules covered by cells. Finally, by analysing hundreds of granules at different time intervals we also obtained reliable data regarding cell proliferation, confirming that not only MSC adhere onto the OSPROLIFE® granules, but even proliferate over time.

An incremental method for mosaicing of optical microscope imagery

Digital imaging is nowadays widely employed in the field of optical microscopy. One of the most apparent benefits consists in the possibility for the researcher to see the whole biological sample in one image, achieved by collecting all the parts being inspected. Common approaches work in batch mode and rely on known motorized x–y stage offsets of the microscope holder. Or alternatively, the methods are conceived just to provide visually pleasant mosaics off-line, that are often built by altering the photometric values or the geometric properties of the original component images. This work presents an incremental mosaicing method for optical microscopy imagery, compliant with on-line requirements and suitable even for non-motorized microscopes. The resulting mosaics are very accurate and preserve the consistency of the original images so to be used for further global measurement steps. Nevertheless, the mosaics are visually pleasant so to be used for visual inspection as well. The experimental results obtained in different biological examinations confirm the efficacy of our approach.