Super-Resolution Imaging (The Springer International Series in Engineering and Computer Science)

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Engineering Letters , 22 4 , pp. Web of Science Hashmi, M. Real time copyright protection and implementation of image and video processing on Android and embedded platforms. Procedia Computer Science , 46, pp. Copy-move image forgery detection using an efficient and robust method combining un-decimated wavelet transform and scale invariant feature transform. Aasri Procedia , 9, pp. Accepted Hashmi, M. International Journal of Computer Applications , 3 , pp. Comparative analysis of fast wavelet transform for image compression for optimal image quality and higher compression ratio. International Journal of Engineering Science and Technology , 3 5 , pp.

Medicine Ophthalmology. Free Preview. Open Access This content is freely available online to anyone, anywhere at any time. Adopts an interdisciplinary approach Provides cutting edge technology in microscopy and ophthalmology Presents newest clinical results of retina and glaucoma diagnostics and therapy control see more benefits. Buy Hardcover. FAQ Policy. A meshing process then takes place, whereby the vertices points in the point cloud are algorithmically connected to form a manifold surface called a mesh [ Figure 2b ].

That mesh is then generally stored as a series of components which define each polygon that make up its surface. Next, images called textures are mapped onto the surface of the mesh in order to faithfully represent the original color of the object that was scanned [ Figure 2c ]. This is achieved by mapping each 3D vertex coordinate onto a corresponding coordinate within a 2D parametric UV unit plane. During the rendering process, this UV mapping is used to broadcast a 2D texture across the 3D surface of the model.

Three-dimensional model generation pipeline through point clouds, meshes, and texture Maps for three-dimensional scanners. For many 3D scanners, multiple scans are required to produce a high fidelity and complete 3D representation of the object being scanned. Generally, in between scans, the object is oriented along a different axis, to ensure that point clouds are obtained from as many different directions as possible; this ensures that information is obtained from all sides of the object.

After multiple scans are obtained, the individual scans are brought into a common reference system through a process that is usually referred to as alignment or registration.

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After the scans are registered, they are subsequently merged to create a more complete 3D model i. There are a wide range of potential approaches to 3D scanning, each with its own advantages and limitations. In this review, we mostly focus on nondestructive methods in which the object is left largely unaltered during digitization. Within this limited scope, 3D scanners fall into one of two broad categories: contact and noncontact data capture methods. Table 2 provides additional characteristics associated with commonly used noncontact, volumetric, and surface scanning methods.

Classification of three-dimensional digitizing method. Three-dimensional scanners fall into broad contact and noncontact based categories. Contact three-dimensional scanners are sub-classified according to whether or not the scanning method is a destructive i. Noncontact three-dimensional scanners are sub-classified by the type of electromagnetic radiation utilized. Within visible light-based noncontact scanning, methods can be further divided devices that emit or absorb radiation. Contact 3D scanners probe objects through physical touch, usually while the objects are mounted or laid upon a flat surface.

This method of data collection is generally more accurate for defining the geometric form of an object rather than organic freeform shapes. Mechanical contact-based digitizing is also more suitable for highly reflective, mirroring, or transparent objects and for objects with difficult-to-reach areas.

Limitations of contact scanning include the relatively slow scan speed and the necessity for physical contact, which may modify or permanently damage the object. As mentioned above, contact 3D digitization requires physically interacting with the object, such that contact 3D scanners are further split into one of two subtypes: destructive and nondestructive [ Figure 3 ]. Nondestructive scanners require physical touch but leave the object largely intact.

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Many popular, commercially available 3D scanners, especially those employed for industrial applications, are of the nondestructive type. An example of such would include a coordinate-measuring machine, which is commonly employed for reverse engineering, rapid prototyping, and large-scale part inspection. Destructive scanners, like automated serial block-face or serial section microscopy, produce volumetric data by consecutively removing minute layers of material, while digitizing each layer as it is processed. The process is repeated until the entire object has been fully digitized, and thus fully destroyed.

Examples of destructive contact scanning include knife-edge scanning microscopy KESM , micro-optical serial tomography, light-sheet microscopy, and focused-ion-beam scanning electron microscopy FIBSEM. These platforms combine robotics, computer vision, and advanced optics for high-throughput imaging and computational analysis. These methods are popular among researchers in the medical and health sciences like connectomics, wherein high-resolution images are used to create structural maps of neural connections.


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Noncontact methods offer a faster and more simple option for obtaining 3D scans. Since the s, the optical or light-based noncontact scanners have become the preferred method for certain kinds of objects. Some include large, freeform, flexible or fragile objects, objects with numerous features, and objects where probe contact is not feasible e. For both subtypes, the concept is more or less the same. Light is reflected off an object's surface through an array of lenses and then onto an image sensor. Passive scanners illuminate objects using an undirected light source, such as ambient light.

Passive scanning methods are simple to set up, have rapid measurement times, and some commercial versions provide automated surface matching.

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In contrast, active scanners employ a directed light source, such as lasers and light patterns. Computer's are able to calculate the 3D coordinates of points of an object's surface by comparing the image of an object light by directed light to what would have been captured under known conditions i. Active scanning is the more popular method. Many commonly used noncontact, active 3D scanning microscopes use fluorescence imaging to provide contrast.

Confocal, multi-photon, and light-sheet microscopy is often used in research laboratories to image small tissue samples at a limited depth. A fundamental challenge for currently available 3D fluorescence microscopy systems is the need to image large volumes of tissue at high resolution in a reasonable time frame.

Confocal and multi-photon microscopy systems provide excellent resolution and contrast but can be prohibitively slow for imaging clinical specimens. For example, a recent study required 30 h to image a single kidney biopsy specimen. These properties of light-sheet microscopy have led to high impact studies in neuroscience and developmental biology. Three-dimensional light-sheet microscopy image of a prostate biopsy measuring 2 cm in length by 1 mm in diameter. The biopsy specimen was chemically cleared with 2, 2' thiodiethanol to enable three-dimensional imaging, then stained with DRAQ5 nuclear and eosin cytoplasmic fluorescent dyes.

A custom-built light-sheet microscope imaged the biopsy in three-dimensions. The nuclear and cytoplasmic channels were false-colored and volume rendered using Imaris software. There are three primary methods of 3D modeling: organic modeling, hard surface modeling, and procedural modeling [ Table 3 ]. It is important to note that only a few file formats will support the full gamut of geometry, colors, and textures.

For example, the stereolithography format. In addition, many commonly used 3D microscopy visualization software packages including Vaa3D[ 41 ] and ImageJ[ 42 ] use raster image formats such as tiff. These raster image formats are much more computationally expensive than the vector formats listed in Table 4 and are not accelerated by the rapid advances in graphical processing units. Research and clinical pathology both use 3D reconstruction of whole slide images. Recent clinical examples include classification of lung adenocarcinomas, diagnosis of colorectal pathologies from small biopsies, and metastasis of breast cancer to lymph nodes.

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Serial tissue sectioning is the most significant obstacle due to the labor and time-intensive nature associated with optimizing the process of alignment of tissue sections. High-end commercial scanners are used by archeologists and preservationists to acquire models of remains, historical artifacts and large excavations.

However, 3D scanners are currently nearly absent in anatomic and clinical pathology. An exception to this would be their use in forensic pathology, for the documentation of specific injuries and as means of virtual autopsy. Presumably, 3D scanning of gross surgical pathology specimens can reproduce realistic models of pathologic entities. These models can be used in medical training, clinical research, education, and clinicopathological correlation at multidisciplinary conferences.

Furthermore, the application of 3D scanning techniques need not be confined to the macro level. Datasets of varying levels of resolution, from sub-millimeter radiographic studies to sub-micron pathologic investigations, can be combined and rendered into an integrated, fully-comprehensive 3D model. These models would undoubtedly prove useful for many processes including tumor staging, margin assessment, pathologic-radiologic correlation, macro-microscopic correlation, and better insights into disease processes. Their broad range of applications has the potential to expand into pathology practice.

Driven by technological advances these tools continue to get cheaper, smaller, more reliable, and easier to use. Future 3D scanners will benefit from significant gains in scan rates. Currently, low scan rates represent a major technical bottleneck for many low-end desktop and handheld 3D scanners. Recently, Kadambi et al. Furthermore, the resolution of the images produced by this form of 3D scanning is much higher than that produced by high-precision laser scanners.

While still in development, techniques like polarized 3D scanning will inevitably usher in the higher-resolution 3D models that can be acquired rapidly and cost effectively. Related technologies are also materializing and poised to profoundly change how we view and interact with 3D data. Chief among them are virtual and augmented reality wearable headsets and controllers e. National Center for Biotechnology Information , U.

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Published online Sep 7. Navid Farahani 1 3Scan, Inc. Alex Braun 1 3Scan, Inc. Dylan Jutt 1 3Scan, Inc. Todd Huffman 1 3Scan, Inc. Author information Article notes Copyright and License information Disclaimer. Address for correspondence: Dr. E-mail: moc.

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