Image Processing Ebooks Catalog

Learn Photo Editing

This online course gives professional advice and instructions for how to photoshop pictures for any purpose that you could need them for. If you need to retouch your portraits, this gives you the tools to edit the image so that your model is sure to be happy with the results. If you need to create cartoon characters, you can learn how to do that in a very short amount of time. You can even learn the more advanced skills, like how to make facial features stand out in the picture without having to retouch the photo. You can learn how to take your normal photos and turn them into glossy, high resolution advertisements. Whatever skills you want to learn, and whatever application your photos will be needed in, this course can give you the tools that you need in order to create the most beautiful photoshoot that you've ever done. Continue reading...

Learn Photo Editing Summary


4.8 stars out of 17 votes

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Author: Patrick
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Highly Recommended

I usually find books written on this category hard to understand and full of jargon. But the author was capable of presenting advanced techniques in an extremely easy to understand language.

In addition to being effective and its great ease of use, this eBook makes worth every penny of its price.

How To Render Cars In Photoshop

How To Render Cars In Photoshop is a video-based tutorial created by a professional designer who named Tim. He has worked with some of the largest automotive companies such as Ford and General Motors for over 15 years. The course is broken down into 26 easy-to-understand, step-by-step videos. From the program, you can learn the multiple ways of adding highlights that give your renderings more life, the insider tips on how to create classic chrome reflections, everything you need to know about how design professionals use Photoshop layers, and simple cheat that design pros use to produce perfect rims. The breakdown of the course includes the Introduction, Scanning Your Drawings, Quick Start, Pontiac G8 Rendering, and Le Mans Racer Rendering, to a total of 26 videos. The program also comes with a number of video bonuses such as Applying Color in Photoshop, Adding Object Reflections, Adding Ground Reflections, and Body Reflection Cheat Sheet. Continue reading...

How To Render Cars In Photoshop Summary

Contents: Video Program
Author: Tim Rugendyke
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Price: $67.00

Medical Image Segmentation

Although a radiologist typically begins an examination of a given medical image by scanning it in its entirety, diagnostic features of interest often manifest in local regions. It is not common for a disease to alter an image over its entire extent. In the context of a breast cancer screening program, the radiologist would scan the entire mammographic image(s) presented, and search for abnormal features that could be associated with disease more attention would then be paid to specific regions of interest (ROIs). In a diagnostic application, the radiologist would concentrate on the region of suspected abnormality, and examine its characteristics to decide if the region exhibits signs related to a particular disease. In the situation of computer-aided diagnosis (CAD), an important role for image processing is to detect the ROIs for the specific application considered.1 ' 2 After the ROIs are detected, the subsequent steps could relate to objective characterization and classification of...

Digital images of fluorescent cells

Many scientists bring the captured images into Adobe Photoshop, to create output for publications. In the next section, therefore, we will describe how to use several features in Photoshop and briefly introduce a program available for image quantification (NIH Image, also available as ImageJ). Adobe Photoshop Photoshop can open a wide variety of image files captured from a microscope-mounted camera, including .tiff and .jpg formats, and provides a variety of means to manipulate images. Here we will briefly describe how to set the color mode, alter the image size, create scale bars for an image, adjust the image brightness and contrast, and create color overlays of images. Figure 9.1 Adobe Photoshop Image Size window. (A) Before size adjustment. (B) After size adjustment. Figure 9.1 Adobe Photoshop Image Size window. (A) Before size adjustment. (B) After size adjustment. For a scale bar on your photomicrograph, you can draw a line of a particular length (in pixels) in Photoshop by...

Discussion and Conclusion

A survey of the current medical image processing literature indicates growing interest in interactive user-guided segmentation methods. The methods presented in this chapter are being used in an interactive procedure for the segmentation of medical images. We are working on the development of procedures to determine the seed region and optimal values for the parameters used in the methods the threshold for contour detection, A max, and ACVmax). An automatic method that has been recently proposed to detect breast masses and tumors10 may be used to provide seed regions and statistical parameters for the segmentation methods described in the present work. We intend to extend the definition of the mass

Mustang Terminology Server

SNOMED nomenclature, MeSH thesaurus, ICD-10 and ICPM classification) can be used as a possible basis for standardization. However, these key systems are standalone vocabularies and are inadequately maintained as far as software engineering is concerned. With the aim of creating an ophthalmology platform health service, a suitable architecture of terminological services with a clearly defined server has been established. This server communicates with the information broker and subsystems as well. All TOSCA applications rely on a telemedical infrastructure for communication, based on established and new technical standards, such as XML for data transfer via networks, DICOM for image transfer and HTTPS for the interaction of different application systems within the telemedical communications infrastructure. All sensitive patient-related data is transferred according to European safety standards. The communication platform includes brokering services,...

Quantitative Measurements of Hippocampal Sclerosis

Because of the relative anisotropy of the hippocampus, slices 3 mm thick or less are probably necessary for accurate estimation of hippocampal volume (207). Van Paeschen showed that a sampling strategy of one in every three slices is accurate to the degree required for the diagnosis of HS (130, 218, 247, 250-252). Volumetry is a simple, reliable method of detecting hippocampal asymmetries that can be carried out in almost all centers with little or no advanced image processing or technical expertise. In centers with excellent expertise in visual assessment of optimized images acquired for the purpose of assessing the hippocampus, the sensitivity from visual diagnosis is such that volumetric assessment usually adds little. Without this expertise, volumes are a very sensitive means of detecting hippocampal abnormality. There are some pitfalls, however, and we will discuss these now.

Techniques For Detection Of Spectral Signatures In Mr Images And Their Applications

5Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland, Baltimore County, Baltimore, MD 21250 6Computer Center Hospital, VACRS, Taichung, Taiwan, 407, ROC 7Department of Electrical Engineering, Da-Yeh University, Changhua, Taiwan, ROC Most recently, remote sensing image processing techniques have been also explored where two hyperspectral image processing techniques, orthogonal subspace projection (OSP) and constrained energy minimization (CEM) have been shown promise in applications of MR image classification.21-24 Unlike traditional image classification methods which are pure pixel-based techniques, the OSP25-27 and CEM25'27-30 are mixed pixel classification techniques which consider an image pixel as a pixel linearly mixed by several substances resident in the pixel. The classification is then carried out by the estimated abundance fractions of these substances present in the pixel. These remote...

Virtual Intraluminal Endoscopy

Pseudo Aneursym Aorta

In terms of image processing, the first step necessary to quantitatively evaluate a vessel is to separate it from surrounding structures. This procedure is called segmentation . Two main approaches to vessel segmentation have been suggested. The first approach relies on purely photometric criteria and focuses mainly on thresholding and region-growing techniques 23-26 . The major advantage of this technique is that it is reasonably easy to implement. However, an additional modeling step is necessary to extract meaningful measurements from the segmented images.

Classification of Masses Using the Results of Segmentation

An interactive graphical interface has been developed in Java, using an object-oriented architecture with controller classes, to integrate the programs that apply the segmentation methods, implemented in the C language, to mammographic images.42 Some of the features of the interface are fast and easy upgradability, portability, and threads to support parallelism between tasks. The interface is ergonomic, easy to use, and includes online help. The interface integrates procedures to detect contours using fuzzy preprocessing and region growing, extract fuzzy regions using fuzzy region growing, compute statistical parameters, and classify masses and tumors as benign or malignant. The interface also provides access to basic image processing procedures including zooming in or out, filters, histogram operations, the Bezier method to manipulate or revise contours, and image format conversion.

Image normalization and GSM calculation

Echolucent Plaque

GSM is calculated using Adobe Photoshop (5.0 or higher). In Adobe Photoshop both the B-mode and the color image should be open. In the B-mode image the color information should be discarded from the Image menu, click on Mode , then Grayscale . Using the Lasso tool, drag the pointer to outline the plaque. Then, click on Histogram in the Image menu. The median value shown in the panel is the GSM. In Adobe Photoshop, the straight line shown in the panel should be modified so that the new line crosses a new point with the input value corresponding to measured adventitial GSM value and the output value corresponding to 190.

Phased Array Transducer

Phased Array Transducer

Originally, echocardiographic data were displayed in analog form on a standard oscilloscope, transferred to a video monitor by a television camera, and hard-copied onto videotape or paper. Currently, computerized analog-to-digital scan conversion is standard, so that the polar signals of individual scan lines are converted to a series of numerical gray-level values for individual box-like picture elements (pixels) aligned along X-Y coordinates.33 The ability of a digital step-gradation technique to reproduce the continuous gradation of analog methods is a function of the density of pixels in the matrix and the shades of gray levels available. No loss of data can be detected in current digitally converted images, and the digital format provides the opportunity for image processing, enhancement, and quantitation. More importantly, storage in digital format can avoid the image degradation inherent in videotape, provide random access and easy comparison of studies, enable rapid image...

Elspeth Garman and Robert M Sweet

Instruments, methods, and software for modern macromolecular crystallography is becoming so effective that molecular biologists often can solve structures from their crystals by working without a license. In this chapter, the authors attempt to demystify some of the apparatus and techniques by providing a roadmap. Current methods for collecting X-ray diffraction data from macromolecular crystals are described. The principles of operation of the required X-ray sources, optics, goniometers, and detectors are outlined, and a typical data collection protocol is presented. Optimization of data quality is a pivotal stage in the whole crystallographic process, so much attention is given to the detailed setting up of the experiment. This is followed by a summary of the basic ideas behind the diffraction image-processing packages and their application to data reduction. Despite the increasingly black box nature of these computer programs, understanding how they extract the intensities, errors,...

Robust Techniques For Enhancement Of Microcalcifications In Digital Mammography

Microcalcifications Mammography

Easily interpretable x-ray mammograms have been a clinicians dream for quite a long time. The recent introduction of dedicated digital review workstations for mammography starts the departure from conventional film-based reading. This development opens up new opportunities for medical image processing. Our emphasis is on enhancement of features that are relevant for diagnosis. The earlier a breast cancer is diagnosed, the easier it is to cure it. Microcalcifications are an early sign of a breast carcinoma. In fact, as S. Heywang-Kobrunner et al.23 point out, microcalcifications can be the only mammographic sign of non-palpable breast disease. Microcalcifications account for over 50 of all the non-palpable lesions detected using mammography. For this reason, the reliable detection of microcalcifications is one of the major goals of mammographic image processing.24 Mammographic images pose a tough challenge for image processing. The images have poor signal-to-noise ratio. They are...

Likaki E Radiologist 2011

IEEE Int. Image Processing Conf. (1998) 87-91. 64. M. Antonini, M. Barlaud, P. Mathieu and I. Daubechies, IEEE Trans. Image Processing 1 (1992) 205-220. 67. A. Said and W. Pearlman, IEEE Trans. Image Processing 5 (1996) 1303-1310. 72. J. Villasenor, B. Belzer and J. Liao, IEEE Trans. Image Processing 4 (1995) 1053-1060.

Conditions lor Telemedicine Development

Auditory information of good quality needs to be transmitted in real time. For dermatology applications, a high-resolution camera with either a low frame rate or still image capture capability rather than standard video at 30 frames sec might be required. Many image processing and graphics functions are often necessary when analyzing medical images with intent of establishing a primary diagnosis or a plan of treatment. They range from window and level adjustment, magnification and minification, digital magnifying glass, image mensuration, adaptive histogram equalization, unsharp masking, and convolution to 3-dimensional visualization, texture measurements, volume measurements, spatial registration, lung nodule screening, microcalcification detection and stereotactic surgical planning. Modern digital radiology requires DICOM standard for image processing 20 . It is commonly used by medical equipment vendors and enables sophisticated processing and analysis of digital medical data...

Other Technologies of Importance

Image processing (e.g., miniaturization, three-dimensional, HDTV), changes in the laparoscope function and design, and use of wireless technologies will transform how we procure images in the operating room and use them in the surgical treatment of patients. Photodocumentation is now easy to obtain during any operation, and most are high-quality, digital images. Along with commercial applications, surgery will experience further important improvements in these technologies in the near future. Improvements in these images will accelerate our ability to transmit knowledge and teach new methods of minimally invasive surgery. This will lead to further progress in understanding diseases and progress in the treatment of patients.

Image Analysis And Atlases

After acquisition of the images for a given study, the big question that faces the investigator is how to analyze all the data. The most straightforward method is to use an image processing package to segment the volumes of interest (e.g., NIH Image and Analyze). This then allows for quantitative comparisons between mutant and wildtype mice or between diseased and normal mice. Figure 5.11 shows an example of a whole brain that has been segmented from a 3D image of a live mouse. Three internal structures have also been segmented and the volumes are easily calculated by voxel counting. However, the image data contain much more information beyond simple volumetrics. A mutant can differ from a wildtype through different shapes in structures or appearance of the tissue. This type of analysis requires more sophisticated image processing and leads to the concept of a normal mouse as represented in an MR image. The idea of average or normal is relatively easy to comprehend when considering...


Since the introduction of the first-generation videolaparoscope in 1986,1 many technological improvements have followed. The main components of the laparoscopic surgical system, however, have remained the same 1) an image processing system (a laparoscope coupled to a video camera, a light source, and a monitoring device), 2) a gas insufflator, and 3) a specialized set of instruments designed for the surgical procedures. All laparoscopic team members should have a basic working knowledge of the functions of these equipments and their various parts, to guarantee the most efficient and safe outcomes. As for image processing, recording, and documentation, we are now in a transitional period from analog to digital systems.2,3 Although this digital revolution may not affect the entire laparoscopic system immediately, we should prepare ourselves for the future changes. This chapter outlines the currently available laparoscopic equipment and discusses what kind of equipment is advisable for...

Yongyi Yang

In this chapter we provide a review of some state-of-the-art techniques in detection of microcalcification (MC) clusters in digital mammograms. Clustered MCs can be an important early indicator of breast cancer, a leading cause of death in women. Computer aided diagnosis (CAD) systems have been developed in recent years for providing a second reader opinion in breast cancer diagnosis. In this review we focus on those most recently published computer techniques for MC detection. Based on the underlying image-processing methods used, we divide these techniques into four categories (1) basic image enhancement, (2) multiscale decomposition, (3) stochastic modeling, and (4) machine learning. For each category we begin with an overview of the different existing methods, and then provide an in-depth description of one or two representative methods. We also present some numerical results to illustrate these representative methods. In the end we furnish some evaluation results to demonstrate...


Clustered microcalcifications are important features for early detection of breast cancer. In this chapter, we provided an overview of a number of state-of-the-art computerized methods for detection of MCs in mammograms, ranging from methods based on simple image enhancement, multiscale decomposition, or stochastic modeling, to those based on machine learning. While those methods based on image enhancement are simple and can offer reasonably good performance, more sophisticated methods based on machine learning tend to be more accurate at the expense of increased computational complexity. Despite recent advances in this field, computerized MC detection is still far from being perfect.

Data Analysis

The array images are analyzed to identify the arrayed spots and to measure the relative intensities for each element (see Note 3).The data from each hybridization experiment are processed using Affymetrix GENECHIP 5.0 software, provided by the manufacturer. Most commercially available array scanner manufacturers provide image-processing software.

William A Pearlman

However, the main advantage of conventional mammography is the image quality obtained at low cost. For this reason, the widespread use of digital mammogra-phy devices has been conditioned to evaluate whether the digital modality provides a better diagnostic performance over the conventional technology. Research works carrying out comparative studies have shown that digital mammography systems significantly improve detection of subtle lesions such as microcalcifications, visualization of low-contrast details or dense breast parenchymal tissue, and definition of skin.4-9 Another study comparing detection of breast cancer using hard copy images or soft copy images displayed on a high-resolution monitor found no significant differences in diagnostic interpretation or reporting speed between both modalities.10 The image processing methods included in digital mammography systems permit filtering, contrast enhancement, or other types of digital image manipulation that avoids repeating any...

Lei Zhang

Edge-preserving image enhancement and noise removal are of great interest in medical imaging. This chapter describes schemes for noise suppression of magnetic resonance images using wavelet multiscale thresholding. To sufficiently exploit the wavelet inter-scale dependencies, we multiply the adjacent wavelet subbands of a Canny-edge-detectorlike dyadic wavelet to form a multiscale product function where the significant features in images evolving with high magnitude across wavelet scales are amplified while noises are deteriorated, which facilitates an easy differentiation of edge structures from noise. Thereafter an adaptive threshold is calculated and imposed on the products, instead directly on the wavelet coefficients, to identify important features. Experiments show that the proposed scheme outperforms other wavelet-thresholding denoising methods in suppressing noise and preserving edges.


Image processing functions allow the reduction of the differences in the instrument response across the field of view (flat-field correction), the subtraction of the instrument background, and the enhancement of the image details. For quantitative analysis, the light emission from selected areas of the sample can be measured by summing the total number of photon fluxes from within those areas. The CL intensity is expressed as photons or relative light units per second per surface area unit (usually pixel or mm ).


Arterial phase 3D CE MRA of the thoracic aorta timed using MR fluoroscopic triggering. During the monitoring mode, two-dimensional MR fluoroscopic viewing of the contrast bolus progression (a, pre-contrast b, pulmonary artery enhancement c, thoracic aortic enhancement) is shown. Upon seeing the arrival of the bolus in the thoracic aorta, the operator prompts the patient to hold his or her breath and then triggers the 3D MRA data acquisition to begin. The 3D CE MRA (d, sagittal MIP) in this 71-year-old man with aortic regurgitation demonstrates a mildly dilated ascending aorta, which measured 4.2 cm in maximum diameter, and normal arch vessels but no aneurysm. High spatial resolution imaging was facilitated on this CE MRA by using a torso phased-array coil and SENSE image processing (Reprinted and adapted with permission from 7 ) Fig. 7a-d. Arterial phase 3D CE MRA of the thoracic aorta timed using MR fluoroscopic triggering. During the monitoring mode, two-dimensional MR...

Renato Toffanin

The purpose of this chapter is to provide a perspective on the current techniques in the imaging analysis of the three-dimensional architecture of trabecular bone and their relevance to the diagnosis of osteoporosis. The emphasis lies on the analysis of images obtained by high resolution X-ray-based CT and MRI techniques. The description of these acquisition techniques is followed by a presentation of the most common image processing methods. Different approaches (morphological, topological, fractal, etc.) used to derive the main architectural features of trabecular bone are illustrated and discussed.

Photoshop CS Mastery

Photoshop CS Mastery

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