An Innovative Method for Obtaining Consistent Images and Quantification of Histochemically Stained Specimens

Obtaining digital images of color brightfield microscopy is an important aspect of biomedical research and the clinical practice of diagnostic pathology. Although the field of digital pathology has had tremendous advances in whole-slide imaging systems, little effort has been directed toward standardizing color brightfield digital imaging to maintain image-to-image consistency and tonal linearity. Using a single camera and microscope to obtain digital images of three stains, we show that microscope and camera systems inherently produce image-to-image variation. Moreover, we demonstrate that post-processing with a widely used raster graphics editor software program does not completely correct for session-to-session inconsistency. We introduce a reliable method for creating consistent images with a hardware/software solution (ChromaCal™; Datacolor Inc., NJ) along with its features for creating color standardization, preserving linear tonal levels, providing automated white balancing and setting automated brightness to consistent levels. The resulting image consistency using this method will also streamline mean density and morphometry measurements, as images are easily segmented and single thresholds can be used. We suggest that this is a superior method for color brightfield imaging, which can be used for quantification and can be readily incorporated into workflows.     

Kite aerial photography: a low‐cost method for monitoring seabird colonies

Obtaining aerial high‐resolution images of bird nesting colonies using remote‐sensing technology such as satellite‐based remote sensing, manned aircraft, or Unmanned Aerial Vehicles might not be possible for many researchers due to financial constraints. Kite Aerial Photography (KAP) provides a possible low‐cost alternative. We collected digital images of ground‐nesting seabirds (i.e., cormorants and penguins) in two different ecosystems using a kite‐based platform equipped with consumer‐grade digital cameras with time‐lapse capability to obtain estimates of breeding population size. KAP proved to be an efficient method for acquiring high‐resolution aerial images. We obtained images of colonies of seabirds ranging in size from hundreds to several hundreds of thousands breeding pairs during flights lasting from a few minutes up to three hours, from flat to very steep areas, and in contrasted wind conditions (from 0.5 to 6 Beaufort force). KAP is an efficient low‐cost method for acquiring high‐resolution aerial images and an alternative to ground‐based censuses, especially useful in rugged areas.     

DR全脊柱成像技术应用探讨

目的探讨DR全脊柱成像技术在脊柱侧弯畸形诊断及测量中的价值,研究不同检查方法对成像质量及测量精度的影响。方法利用PHIIAPS公司Digital Diagnost DR系统和具有全脊柱拼接功能的SUN后处理工作站,对分次所摄的脊柱正位、侧位、左、右侧屈位影像进行拼接处理后作必要的测量,并打印成像。结果经上述处理后的全脊柱正位、侧位及左、右侧屈位均能将颈、胸、腰、骶椎完整联接,显示在1张14＋17的X光片上,其测量的数据真实可靠。结论DR全脊柱成像技术克服了以往颈、胸、腰、骶椎单独成像后测量上的误差,为临床手术提供了更精确的数据。     

Directional features for automatic tumor classification of mammogram images

One way for breast cancer diagnosis is provided by taking radiographic (X-ray) images (termed mammograms) for suspect patients, images further used by physicians to identify potential abnormal areas thorough visual inspection. When digital mammograms are available, computer-aided based diagnostic may help the physician in having a more accurate decision. This implies automatic abnormal areas detection using segmentation, followed by tumor classification. This work aims at describing an approach to deal with the classification of digital mammograms. Patches around tumors are manually extracted to segment the abnormal areas from the remaining of the image, considered as background. The mammogram images are filtered using Gabor wavelets and directional features are extracted at different orientation and frequencies. Principal Component Analysis is employed to reduce the dimension of filtered and unfiltered high-dimensional data. Proximal Support Vector Machines are used to final classify the data. Superior mammogram image classification performance is attained when Gabor features are extracted instead of using original mammogram images. The robustness of Gabor features for digital mammogram images distorted by Poisson noise with different intensity levels is also addressed.     

Imaging technics in bronchology

Bronchoscopic imaging and diagnostics are tightly connected with radiological and pathological techniques. While computer tomography (virtual bronchoscopy) makes possible to mimic a realistic endobronchial situation, autofluorescent bronchoscopy holds significant potential to discover precancerous lesions not identifiable by standard bronchoscopy. Endoscopic ultrasound and fluoroscopy can be applied in order to obtain images and tissue samples from the extrabronchial areas. Electromagnetic navigation during flexible bronchoscopy, a novel technology that facilitates approaching peripheral lung lesions, involves creating an electromagnetic field around the thorax and localizing an endoscopic tool using a microsensor overlaid upon previously acquired CT images. In conclusion, parallel use of invasive and non-invasive imaging has the potential for considerable improvements in the diagnostic possibilities of routine bronchoscopic procedures.     

Issues in using whole slide imaging for diagnostic pathology: “routine” stains,immunohistochemistry and predictive markers

The traditional microscope, together with the “routine” hematoxylin and eosin (H & E) stain, remains the “gold standard” for diagnosis of cancer and other diseases; remarkably, it and the majority of associated biological stains are more than 150 years old. Immunohistochemistry has added to the repertoire of “stains” available. Because of the need for specific identification and even measurement of “biomarkers,” immunohistochemistry has increased the demand for consistency of performance and interpretation of staining results. Rapid advances in the capabilities of digital imaging hardware and software now offer a realistic route to improved reproducibility, accuracy and quantification by utilizing whole slide digital images for diagnosis, education and research. There also are potential efficiencies in work flow and the promise of powerful new analytical methods; however, there also are challenges with respect to validation of the quality and fidelity of digital images, including the standard H & E stain, so that diagnostic performance by pathologists is not compromised when they rely on whole slide images instead of traditional stained tissues on glass slides.     

Electronic light microscopy: present capabilities and future prospects

Electronic light microscopy involves the combination of microscopic techniques with electronic imaging and digital image processing, resulting in dramatic improvements in image quality and ease of quantitative analysis. In this review, after a brief definition of digital images and a discussion of the sampling requirements for the accurate digital recording of optical images, I discuss the three most important imaging modalities in electronic light microscopy-video-enhanced contrast microscopy, digital fluorescence microscopy and confocal scanning microscopy-considering their capabilities, their applications, and recent developments that will increase their potential. Video-enhanced contrast microscopy permits the clear visualisation and real-time dynamic recording of minute objects such as microtubules, vesicles and colloidal gold particles, an order of magnitude smaller than the resolution limit of the light microscope. It has revolutionised the study of cellular motility, and permits the quantitative tracking of organelles and gold-labelled membrane bound proteins. In combination with the technique of optical trapping (optical tweezers), it permits exquisitely sensitive force and distance measurements to be made on motor proteins. Digital fluorescence microscopy enables low-light-level imaging of fluorescently labelled specimens. Recent progress has involved improvements in cameras, fluorescent probes and fluorescent filter sets, particularly multiple bandpass dichroic mirrors, and developments in multiparameter imaging, which is becoming particularly important for in situ hybridisation studies and automated image cytometry, fluorescence ratio imaging, and time-resolved fluorescence. As software improves and small computers become more powerful, computational techniques for out-of-focus blur deconvolution and image restoration are becoming increasingly important. Confocal microscopy permits convenient, high-resolution, non-invasive, blur-free optical sectioning and 3D image acquisition, but suffers from a number of limitations. I discuss advances in confocal techniques that address the problems of temporal resolution, spherical and chromatic aberration, wavelength flexibility and cross-talk between fluorescent channels, and describe new optics to enhance axial resolution and the use of two-photon excitation to reduce photobleaching. Finally, I consider the desirability of establishing a digital image database, the BioImage database, which would permit the archival storage of, and public Internet access to, multidimensional image data from all forms of biological microscopy. Submission of images to the BioImage database would be made in coordination with the scientific publication of research results based upon these data. In the context of electronic light microscopy, this would be particularly useful for three-dimensional images of cellular structure and video sequences of dynamic cellular processes, which are otherwise hard to communicate. However, it has the wider significance of allowing correlative studies on data obtained from many different microscopies and from sequence and crystallographic investigations. It also opens the door to interactive hypermedia access to the multidimensional image data, and multimedia publishing ventures based upon this.Presented at the XXXVII Symposium of the Society for Histochemistry, 23 September 1995, Rigi Kaltbad, Switzerland     

Toward the virtual cell: Automated approaches to building models of subcellular organization "learned" from microscopy images

We review state-of-the-art computational methods for constructing, from image data, generative statistical models of cellular and nuclear shapes and the arrangement of subcellular structures and proteins within them. These automated approaches allow consistent analysis of images of cells for the purposes of learning the range of possible phenotypes, discriminating between them, and informing further investigation. Such models can also provide realistic geometry and initial protein locations to simulations in order to better understand cellular and subcellular processes. To determine the structures of cellular components and how proteins and other molecules are distributed among them, the generative modeling approach described here can be coupled with high throughput imaging technology to infer and represent subcellular organization from data with few a priori assumptions. We also discuss potential improvements to these methods and future directions for research.     

Anatomic Pathways of Peripancreatic Fluid Draining to Mediastinum in Recurrent Acute Pancreatitis: Visible Human Project and CT Study

Background

In past reports, researchers have seldom attached importance to achievements in transforming digital anatomy to radiological diagnosis. However, investigators have been able to illustrate communication relationships in the retroperitoneal space by drawing potential routes in computerized tomography (CT) images or a virtual anatomical atlas. We established a new imaging anatomy research method for comparisons of the communication relationships of the retroperitoneal space in combination with the Visible Human Project and CT images. Specifically, the anatomic pathways of peripancreatic fluid extension to the mediastinum that may potentially transform into fistulas were studied.

Methods

We explored potential pathways to the mediastinum based on American and Chinese Visible Human Project datasets. These drainage pathways to the mediastinum were confirmed or corrected in CT images of 51 patients with recurrent acute pancreatitis in 2011. We also investigated whether additional routes to the mediastinum were displayed in CT images that were not in Visible Human Project images.

Principal Findings

All hypothesized routes to the mediastinum displayed in Visible Human Project images, except for routes from the retromesenteric plane to the bilateral retrorenal plane across the bilateral fascial trifurcation and further to the retrocrural space via the aortic hiatus, were confirmed in CT images. In addition, route 13 via the narrow space between the left costal and crural diaphragm into the retrocrural space was demonstrated for the first time in CT images.

Conclusion

This type of exploration model related to imaging anatomy may be used to support research on the communication relationships of abdominal spaces, mediastinal spaces, cervical fascial spaces and other areas of the body.     

CHARGE CONTRAST IMAGING OF EXCEPTIONALLY-PRESERVED FOSSILS

Abstract:  Charge contrast images are a variant of secondary electron images acquired by operating a variable pressure scanning electron microscope in low vacuum mode; i.e. a gas is present in the specimen chamber. Spatial variation in the amount of charge that accumulates on the surface of the specimen is expressed as differences in greyscale tone; areas that are charging less are darker in tone. The precise mechanisms by which charge contrast images are generated are not known fully. Various different properties of a mineral may create a charge contrast; electrical conductivity is known to be one potentially important variable. As carbon is highly conductive but typical host lithologies (carbonates, silicates) less so or dielectric, the technique is potentially very suitable for imaging organically preserved fossils such as those from the Solite and Jehol biotas. It can also be applied to Burgess Shale fossils: complex films comprising 'aluminosilicates' with or without carbonaceous remains. Charge contrast images reveal anatomical detail not visible using either optical or other scanning electron microscope-based imaging methods.     

Illuminating the Regenerative Properties of Stem Cells In Vivo with Bioluminescence Imaging

Preclinical animal studies are essential to the development of safe and effective stem cell therapies. Bioluminescence imaging (BLI) is a powerful tool in animal studies that enables the real-time longitudinal monitoring of stem cells in vivo to elucidate their regenerative properties. This review describes the application of BLI in preclinical stem cell research to address critical challenges in producing successful stem cell therapeutics. These challenges include stem cell survival, proliferation, homing, stress response, and differentiation. The applications presented here utilize bioluminescence to investigate a variety of stem and progenitor cells in several different in vivo models of disease and implantation. An overview of luciferase reporters is provided, along with the advantages and disadvantages of BLI. Additionally, BLI is compared to other preclinical imaging modalities and potential future applications of this technology are discussed in emerging areas of stem cell research.     

Noise suppressed,multifocus image fusion for enhanced intraoperative navigation

Current intraoperative imaging systems are typically not able to provide ‘sharp’ images over entire large areas or entire organs. Distinct structures such as tissue margins or groups of malignant cells are therefore often difficult to detect, especially under low signal‐to‐noise‐ratio conditions. In this report, we introduce a noise suppressed multifocus image fusion algorithm, that provides detailed reconstructions even when images are acquired under sub‐optimal conditions, such is the case for real time fluorescence intraoperative surgery. The algorithm makes use of the Anscombe transform combined with a multi‐level stationary wavelet transform with individual threshold‐based shrinkage. While the imaging system is integrated with a respiratory monitor triggering system, it can be easily adapted to any commercial imaging system. The developed algorithm is made available as a plugin for Osirix. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Secure Similar Image Search and Copyright Protection over Encrypted Medical Image Databases

The recent advances in digital medical imaging and storage in cloud are bringing about more demands for efficient and secure image retrieval and management. Typically, medical images are very sensitive to changes where any modifications in its content may bring about an erroneous medical diagnosis. Therefore, securing medical images is a very essential process and the major task is, the medical image must maintain their sensitive contents at the time of reconstruction. The proposed methodology executes a secure image encryption and search of medical images proficiently over encrypted image database without leaking any sensitive data. It also ensures medical data integrity by introducing an efficient recovery mechanism on ROI of the image. The proposed scheme obtains recovery information about the image from the ROI of the medical data and embeds it in the RONI region using IWT transform which act as a reversible watermarking. If any alterations or tampers are caused to ROI at the third-party end, then it can be identified and recovered from the obtained recovery data. Besides, the model also executes a Copyright protection scheme to locate the authorized users, who illegally duplicate and distribute the retrieved image to unauthorized entities.     

FPGA技术在生物医学成像中的研究进展

数字图像处理技术和微电子集成电路的飞速发展,使实时动态生物医学成像成为可能.生物医学动态成像的关键是高的通讯带宽和快速的数据处理能力,FPGA (field programmable gate array)即现场可编程逻辑门阵列,为数字图像实时处理系统在算法、系统结构上提供了新的思路与方法.文中首先简单介绍FPGA的概念、特点及其发展历程,详细对比FPGA与通用处理器之间的性能指标,然后重点介绍常规生物医疗成像技术原理和FPGA在医疗领域高速成像技术方面的研究和应用情况,最后对FPGA在实时成像方面进行总结和展望.     

An ImageJ-based tool for three-dimensional registration between different types of microscopic images

Three-dimensional (3D) registration (i.e., alignment) between two microscopic images is very helpful to study tissues that do not adhere to substrates, such as mouse embryos and organoids, which are often 3D rotated during imaging. However, there is no 3D registration tool easily accessible for experimental biologists. Here we developed an ImageJ-based tool which allows for 3D registration accompanied with both quantitative evaluation of the accuracy and reconstruction of 3D rotated images. In this tool, several landmarks are manually provided in two images to be aligned, and 3D rotation is computed so that the distances between the paired landmarks from the two images are minimized. By simultaneously providing multiple points (e.g., all nuclei in the regions of interest) other than the landmarks in the two images, the correspondence of each point between the two images, i.e., to which nucleus in one image a certain nucleus in another image corresponds, is quantitatively explored. Furthermore, 3D rotation is applied to one of the two images, resulting in reconstruction of 3D rotated images. We demonstrated that this tool successfully achieved 3D registration and reconstruction of images in mouse pre- and post-implantation embryos, where one image was obtained during live imaging and another image was obtained from fixed embryos after live imaging. This approach provides a versatile tool applicable for various tissues and species.     

Digital photography provides a fast,reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues

Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer‐level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content‐chroma ratio, anthocyanin content‐chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r² and normalized root‐mean‐square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Analyzing Microbial Population Heterogeneity—Expanding the Toolbox of Microfluidic Single-Cell Cultivations

Recent research on population heterogeneity revealed fascinating insights into microbial behavior. In particular emerging single-cell technologies, image-based microfluidics lab-on-chip systems generate insights with spatio-temporal resolution, which are inaccessible with conventional tools. This review reports recent developments and applications of microfluidic single-cell cultivation technology, highlighting fields of broad interest such as growth, gene expression and antibiotic resistance and susceptibility. Combining advanced microfluidic single-cell cultivation technology for environmental control with automated time-lapse imaging as well as smart computational image analysis offers tremendous potential for novel investigation at the single-cell level. We propose on-chip control of parameters like temperature, gas supply, pressure or a change in cultivation mode providing a versatile technology platform to mimic more complex and natural habitats. Digital analysis of the acquired images is a requirement for the extraction of biological knowledge and statistically reliable results demand for robust and automated solutions. Focusing on microbial cultivations, we compare prominent software systems that emerged during the last decade, discussing their applicability, opportunities and limitations. Next-generation microfluidic devices with a high degree of environmental control combined with time-lapse imaging and automated image analysis will be highly inspiring and beneficial for fruitful interdisciplinary cooperation between microbiologists and microfluidic engineers and image analysts in the field of microbial single-cell analysis.