The Visible Human Project was an effort of the National Library of Medicine (NLM) to build a digital image library of volumetric data representing a complete, normal adult male and female. The data sets were released in 1994 and
In the early 1920’s the Bartlane cable picture transmission system was introduced, thereby reducing the transportation time for a picture from New York to England by days. Digital images were first applied in the newspaper industry when pictures were first set by submarine cable between London and New York, then the Bartlane cable was introduced reducing transmission time from three weeks to three hours. There were different phases in technology improvement; in 1921 the method used for receiving images through a coded tape by a telegraph printer was abandoned in favor of a technique based on photographic reproduction made from tapes perforated at the telegraph receiving terminal with evident improvement in both tonal quality and resolution.
Medical imaging is a rich field with multidiscipline nature, involving nuclear physics, quantum mechanics, fluid dynamics, advanced mathematics, biology, chemistry, computer science and computer engineering. It has become a primary component of modern medicine. It is still a relatively new field with many unknown effects and unanswered questions. The technologies are evolving, and new equipment, modality, study methodology have been constantly developed. Excellent opportunities for research and career development.
The invention in the early 1970 s of computerized axial tomography (CAT) is one of the most important events in the application of image processing in medical diagnosis. Tomography consists of algorithms that use the sensed data to construct an image that represents a slice through the object which compose a threedimensional (3 -D) version of the inside of the object.
CONTINUED Tomography was invented independently by Sir Godfrey N. Hounsfield and Professor Allan M. Cormack, who shared the 1979 Nobel Prize in Medicine for their invention. X-rays were discovered in 1895 by Wilhelm Conrad Roentgen, for which he received the 1901 Nobel Prize in Physics. These two inventions, nearly 100 years apart led to some of the most active application areas of image processing today. Computer procedures are also used to enhance the contrast or code the intensity levels into color for easier interpretation of Xrays and other images used in industry, medicine, and the biological sciences.
Besides the natural images acquired from conventional optical cameras, computer synthesized images become more and more important in many application fields. Non-invasive imaging modalities allow people to view objects that can not be seen by human eye or camera,
Geographers use the same or similar techniques to study pollution patterns from aerial and satellite imagery. Image enhancement and restoration procedures are used to process degraded images of unrecoverable objects or experimental results too expensive to duplicate. In archaeology, image processing methods have successfully restored blurred pictures that were the only available records of rare artifacts lost or damaged after being photographed.
Image acquisition- is the first process which involves preprocessing such as scaling. Image enhancement- this is bringing out obscured detail or highlighting certain features of interest in an image. This technique deals with a number of mathematical functions such as the Fourier Transform. Image restoration- it improves the appearance of an image but is objective in the sense that this technique tends to be based on mathematical or probabilistic models of image degradation. Color image processing- this is used as a basis for extracting features of interest in an image.
Image analysis is to identify and extract useful information from an image or a video scene, typically with the ultimate goal of forming a decision. Image analysis is the center piece of many applications such as remote sensing, robotic vision and medical imaging. Image analysis generally involves basic operations:
Image segmentation is an important pre-processing tool. It produces a binary representation of the object with features of interest such as shapes and edges. Common operations include: Thresholding: to segment an object from its background through a simple pixel amplitude based decision. Complicated thresholding methods may be used when the background is not homogeneous. Edge detection: to identify edges of an object through a set of high-pass filtering. Directional filters and adaptive filters are frequently used to achieve reliable results.
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