Need for Different Imaging Techniques

Using a particular imaging technique, we can only diagnose a single organ or the organ which is only detectable by a particular technique. CT scan is able to detect only the existence of stones in kidney plus any peculiarities in our urinary tract [1]. But to get a view of arteries in kidney we need Magnetic Resonance Angiogram but to find the whereabouts of some tumor, infection or cyst we need to use CT scan. Although many imaging techniques are there, we use only a particular one based on the patient’s history and problem.

Different techniques have its own usage and properties to detect particular problem. Also, all these techniques have its own cons too; as CT scan cannot provide with the blood gush and action of cerebrum cell, whereas MRI can [1]. Also due to emerging technologies these techniques can be combined to get more finer information about the disease or problem. Some coupled techniques that are in usage are PET-MRI or CT-PET, CT-MRI; all these provide the practical characterization of body parts and tissues along with complete information about the flesh thickness, length of the organ and more [1]. Therefore, coupling of the procedures gives much better diagnosis.

Image Processing System

The images that we get from different imaging techniques are further used by the clinician to think for an operation, remedy and to determine the issue [I]. Image processing is very much important as the whole treatment is based on the image we get through image techniques. A small variation in the image can totally change the treatment which has to be done by the doctor. For exact diagnosis image quality and processing play a vital role.

Elements of Image Preparing

The data prevailed out of in-patient’s anatomy through imaging to the display of picture. All these play significant role in image processing.

  • Image sensors: Sensors such as camera, videos or scanner are used to capture the images. And these captured images are later converted to digital form using digitizer.
  • Image processing hardware: Its purpose is to speed up the process.
  • Computer: As an image processing system, we can use a normal PC to highly specialized computer based on our needs.
  • Mass storage: This is used for the storage of the image we obtain from the patient. Therefore, we require better storage system so as to store thousands to millions of images obtained from patients.
  • Hardcopy devices: This is used for recording the images.
  • Image processing software: Commercial software are available in the market which can be used for further processing of images.
  • Image display: To display the output or the information we use devices like monitors or television, screens, etc.

Sensor Fusion

As mentioned above in image processing sensors are used to capture the image that we get from the patient. Nowadays in image processing sensor fusion is the widely used technology.

Sensor fusion is the association of sensory statistics or facts resulting out of diverse origins in order for the subsequent statistics has much lesser ambiguity that ought to be viable while those assets have been used personally [2]. Sensor fusion can be defined as the combination of two or more data sources in a way that generates a better understanding of the system. Data fusion systems are actually widespread and are used in numerous areas which include sensor web works, robotics, video and photo processing, and intelligent machine layout, one or two more. We can address this with many names such as sensor data fusion, information fusion, multisensory fusion, etc..

Advantages of Sensor Fusion

Generally, performing data fusion has specific benefits. These benefits mostly contain improvements in information genuinity and accessibility. Illustration of the data fusion helps progressed sensing, conviction and dependability, also limiting of facts and figures obscurity, while expanding dimensional and transient assurance pertaining to the ultimate class of advantages. Information merging is capable to offer particular advantages for a few software conditions. For example, cordless sensor internet mechanism is regularly made of a great amount of sensor nodules, consequently presenting a latest extensibility challenges produced by capability collisions and spreading of unnecessary statistics. Concerning power limitations, conversation must be minimized to expand the existence period of the sensor nodules. When statistics fusion takes place at some stage in the routing method, this sensor record is merged and the most effective end outcome is conveyed, the variety of text is decreased, strikes are averted and power is conserved.

 
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