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Anatoly Uvarov
Anatoly Uvarov

Digital Image Processing Book By Sanjay Sharma Pdf 350

Beyond the machine itself, solid image processing is a key component of a diagnostic radiography program. While procurement of consumables for image processing is less of a logistical bottleneck than is the maintenance of the machine itself, analogue processing remains less desirable owing to challenges in storing the films, disposing of waste, and performing distant quality assurance on the images. Several groups have been developing digital retrofits of the WHIS-RAD. The up-front costs of digital technologies are significant, but the long-term benefits are substantial. Except in cases where excellent maintenance and servicing can be assured, however, we recommend having analogue as a back-up. In Nyaya Health's case, we chose analogue to start out of concerns about the costs and reliability of the digital system, though our long-term vision is to go digital (see case study below and table 3).

Digital Image Processing Book By Sanjay Sharma Pdf 350

Subsequently, in 2010, Nyaya Health initiated an X-Ray program with a WHIS-RAD machine from the Spanish company Sedecal (Figure 2). Prior to deployment, our team discussed and investigated options for manufacturers and models extensively, particularly whether to purchase from an in-country (Nepal) or international company. We consulted with numerous experts throughout the world, and in fact our frustration with the current state of knowledge about the scale-up of x-ray services was the primary motivation for this piece. Ultimately we selected the WHIS-RAD system for the reasons we have discussed here. Implementing the x-ray program proved to be significantly more challenging than ultrasound services. Our first challenge was delivering equipment that weighed over 750 kg to an extremely remote region with limited road access. This was further complicated by the need to have a technician onsite to install it; this required a team to travel from Dehli (India) over 2 days away. Onsite challenges included effective training of a local staff member and developing reliable electricity to charge and operate the WHIS-RAD system. We worked with a regional hospital to train a mid-level provider (4 weeks) and have agreed to a 2 year bonding period to ensure the staff member is not drawn to an urban area where work is available and living conditions are far better. The second major challenge onsite was the electricity situation. Even though the WHIS-RAD has a battery source, it requires a 110 or 220 V supply, and the main electricity grid where Nyaya works was only supplying a degraded 170 V signal; this problem was fixed with the addition of a relatively inexpensive voltage stabilizer yet delayed implementation by several months. Presently we are deploying analogue film processing, though we hope to scale to digital in the future. We have documented our work on our wiki [43] and blog [44]. In table 3, we provide the approximate costs of our x-ray deployment, which we used in planning services.

Image pre-processing and feature extraction techniques are mandatory for any image based applications. The accuracy and convergence rate of such techniques must be significantly high in order to ensure the success of the subsequent steps. But, most of the time, the significance of these techniques remain unnoticed which results in inferior results. In this work, the importance of such approaches is highlighted in the context of Magnetic Resonance (MR) brain image classification and segmentation. In this work, suitable pre-processing techniques are developed to remove the skull portion surrounding the brain tissues. Also, texture based feature extraction techniques are also illustrated in this paper. The experimental results are analyzed in terms of segmentation efficiency for pre-processing and distance measure for feature extraction techniques. The convergence rate of these approaches is also discussed in this work. Experimental results show promising results for the proposed approaches.

Because of image acquisition system, different physical phenomena such as illumination cannot be completely evenly distributed, and many other reasons, the obtained edge intensity of image is different. Moreover, in real-world situations, image data is often contaminated by noise. While the scenery features mixed together so that it makes subsequent interpretation very difficult. To achieve the accurate grasp of the picture intent, it needs to study a target recognition method that can not only detect the non-continuity of intensity, but also can determine their exact position. It needs to develop new uncertainty processing methods and algorithms to solve such problems.


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