Automatic panorama with auto-focusing based on image fusion for microscopic imaging system

Doğan, Hülya; Ekinci, Murat

doi:10.1007/s11760-014-0717-5

Cited by 14 publications

(3 citation statements)

References 18 publications

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“…Blending techniques are colour-mapping algorithms minimizing colour differences between views [ 57 ]. Many different colour-mapping approaches, also known as colour-registration, colour-correction, colour-balancing (if restricted to the overlapped area only), and colour-transfer [ 37 ], have been proposed in literature [ 58 ]. Their aim is to transfer the colour palette of the source image to the target one, while extending the transferred colour from the overlapped area to the full target image [ 59 ].…”

Section: Discussionmentioning

confidence: 99%

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses

Piccinini

Bevilacqua

2018

BioMed Research International

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Image mosaicing permits achieving one high-resolution image, extending the visible area of the sample while keeping the same resolution. However, intensity inhomogeneity of the stitched images can alter measurements and the right perception of the original sample. The problem can be solved by flat-field correcting the images through the vignetting function. Vignetting correction has been widely addressed for grey-level images, but not for colour ones. In this work, a practical solution for the colour vignetting correction in microscopy, also facing the problem of saturated pixels, is described. In order to assess the quality of the proposed approach, five different tonal correction approaches were quantitatively compared using state-of-the-art metrics and seven pairs of partially overlapping images of seven different samples. The results obtained proved that the proposed approach allows obtaining high quality colour flat-field corrected images and seamless mosaics without employing any blending adjustment. In order to give the opportunity to easily obtain seamless mosaics ready for quantitative analysis, the described vignetting correction method has been implemented in an upgraded release of MicroMos (version 3.0), an open-source software specifically designed to automatically obtain mosaics of partially overlapped images.

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Section: Discussionmentioning

confidence: 99%

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses

Piccinini

Bevilacqua

2018

BioMed Research International

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“…Therefore, the literature approaches recommended for the creation of panoramic images with a wide-view sample in the microscopic system are explained by two different titles as 2D microscopic image stitching and 3D microscopic image stitching in this study. (1) 2D microscopic ımage stitching approaches: Literature studies related to 2D microscopic image stitching can be classified as follows: (i) Improving the efficiency of 2D panoramic image with a wide-view of the sample in the microscopic system, where a new pre-processing stage or algorithm was proposed to crate the 2D panoramic image with less noisy and seamless overlapping areas [1][2][3][4][5][6][7][8][9][10][11]. (ii) Accelerate the 2D microscopic image stitching system, where researchers developed a tool or algorithm to provide more accurate and rapid 2D panoramic imaging with a wide-view of the sample [12][13][14][15][16].…”

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confidence: 99%

A hybrid technique using modified ICP algorithm for faster and automatic 2D & 3D microscopic image stitching in cytopathologic examination

Doğan¹,

Kablan²,

Ekinci³

et al. 2021

Turk J Elec Eng & Comp Sci

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Due to the limitations of the light microscopic system such as limited depth of field and narrow field of view, entire sample areas are invisible and pathologists move the light microscope stage along the X -Y -Z axes with eye-hand coordination. In order to reduce the dependence on the pathologist and to allow whole sample areas to be examined in a short time without any control (without eye-hand coordination), this study creates 2D & 3D panoramic images with wide-view of sample in the light microscopic systems. According to our literature research, there is no study that creates 2D & 3D panoramic images in the microscopic system together. For this reason, it is thought that our study, which is the first one in which 2D & 3D panoramic images are created together in the light microscopic system, will be one of the pioneering studies in this field. Literature studies generally utilize specific microscope types such as laser, stereo and confocal, where 3D shape of the sample is extracted automatically and only 2D & 3D microscopic image stitching techniques are performed. Unlike these studies, due to the use of the light microscope which is requires a procedure to extract the 3D structure of the sample, this study contains an extra phase which creates 2D & 3D adjacent images using series of multi-focus 2D adjacent images before 2D & 3D microscopic image stitching technique. Moreover, a hybrid 2D & 3D microscopic image stitching technique which uses modified ıterative closest point algorithm and combines the stages of 2D and 3D image-based 2D & 3D image stitching techniques is developed in this study. Both qualitative and quantitative evaluations of the proposed study are performed on real microscope image data sets from samples prepared for cytopathologic examination in the light microscopic system. Our hybrid technique creates 2D panoramic images whose values of peak signal to noise ratio (PSNR), correlation coefficient (CC), entropy and average gradient are computed respectively as 30.4267, 0.9997, 7.4670 and 122.2510 and 3D panoramic images whose values of PSNR, universal quality index, root mean square error, CC, kurtosis metric and standard deviation are computed respectively as 17.7458, 0.9702, 8.9230, 0.8702, 5.4981 and 31.006, which are the best values when compared with well-established studies. Moreover, the proposed hybrid technique with 9.8403 and 23.5902 (s) execution times accelerates the process of automatic 2D & 3D panoramic imaging.

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“…In "Automatic Panorama with Auto-focusing based on Image Fusion for Microscopic Imaging System" [2], Dogan et al discuss the problem of imaging large tissue slides in an automated fashion. Field-of-view extension through mosaicing is an important technique in microscopic image processing, because most of the time, the clinicians do not rely their diagnosis on limited small field-of-view images generated by the microscopes.…”

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confidence: 99%

Special issue on microscopic image processing

Kose

Cetin-Atalay

Çetin

2014

SIViP

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Microscopic images play an essential role in detection and diagnosis of numerous diseases. For example, analysis of histology images of the human tissue biopsies remains the most reliable way of diagnosis and grading cancer. On the other hand, there is significant inter-and intra-rater variability in the grading and diagnosis of cancer from histology slides by clinicians. Computational histopathology can assist the pathologists in making the grading and diagnosis reproducible, by providing useful quantitative measures from histology images of a patient suspected or diagnosed of having cancer [1]. Similarly, in cellular biology, live cell fluorescence imaging made possible by the rapid advances of fluorescent microscopy opens new avenues for microscopic image processing. It is possible to give many similar examples.In this special issue, we bring together six recent research articles on microscopic image processing and analysis. The subject topics of papers cover a diverse set of topics related to microscopic images processing such as creating efficient representations, segmentation of diagnostically significant structures, and automated classification. Even if the targeted applications are diverse, the main goal of all the algorithms was similar; they describe automated analysis methods for In "Automatic Panorama with Auto-focusing based on Image Fusion for Microscopic Imaging System" [2], Dogan et al. discuss the problem of imaging large tissue slides in an automated fashion. Field-of-view extension through mosaicing is an important technique in microscopic image processing, because most of the time, the clinicians do not rely their diagnosis on limited small field-of-view images generated by the microscopes. Typically, they either sift through the tissue sample by manually sliding it under the microscope objective or use expensive slide scanners to obtain large field-of-view digital images. In their study, Dogan et al. developed a color image fusion-based autofocus system followed by an automated microscopic image mosaicing method that can create high-resolution, large field-of-view images of the sample tissue using a low-cost system. The system enables quantitative imaging by minimizing the user input for focus purposes as well as it speeds up the imaging process. They showed the feasibility of their system on bright-field microscopy images of Mycobacterium tuberculosis in specimen of ZiehlNeelsen-stained sputum smears.Segmentation of microscopic images is another area that computational methods are making an impact on. In many cases, the clinical diagnosis in histology relies on making quantifiable measurements from the microscopic images, such as counting number of a specific cell type or measuring their shape and sizes. Considering that a single microscopic image contains several of these structures, making such measurements manually, in a quantitative manner, is laborintensive if not infeasible. However, computer-aided segmentation algorithms are ideally suited for such operations as they rely on objectiv...

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Automatic panorama with auto-focusing based on image fusion for microscopic imaging system

Cited by 14 publications

References 18 publications

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses

Colour Vignetting Correction for Microscopy Image Mosaics Used for Quantitative Analyses

A hybrid technique using modified ICP algorithm for faster and automatic 2D & 3D microscopic image stitching in cytopathologic examination

Special issue on microscopic image processing

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