Advantages and disadvantages of medical image processing Essay

Image processing refers to the analysis and the manipulation of a digitized image, in order to improve the quality of the software. The action of acquiring images is referred to as imaging. In the present scenario, images also gain much broader scopes due to the ever growing importance of scientific visualization.
Image sharpening and restoration, Medical field, Remote sensing, Transmission and encoding, Machine/Robot vision, Color processing, Pattern recognition, Video processing, Microscopic Imaging are the application which are used in the digital image processing . Image processing basically includes the following three steps Importing the image via image acquisition tools Analyzing and manipulating the image Output in which result can be altered image or report that is based on image analysis.
ADVANTAGES OF MEDICAL IMAGE PROCESSING
Reasonable computing times
Smallest interpolation error
Superior Fourier properties
Interoperable
consistency
Security.
Cost effective and user friendly development of software for medical image processing
Disease diagnosis
Exploits hardware resources , Space and computation efficient
23.4x increase in speed in registration
Computationally cost effective
ADVANCED DIGITAL IMAGE PROCESSING TECHNIQUE
Neural Network based Image Processing.
Statistical approach for texture analysis.
Segmentation in color and B/W images.
Expert system based Image Processing.
Application of object oriented programming techniques in Image Processing environments.
Shape in machine vision.
Multispectral classification techniques.
Auto focusing techniques for MRI images.
Thresholding technique for finding contours of objects.
Sequential segmentation technique to find out thin vessels in medical images and
hair line cracks in NDT.
Fractal method for texture classification.
Data compression techniques using fractals and Discrete Cosine Transformers.
Image restoration methods using Point Spread functions and Wiener filter etc.
COMPUTER- AIDED IMAGE DIAGNOSIS PROCESSING
CAD are procedures in medicines that accompany doctors to show the significance of medical images. . CAD systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. Computer- aided diagnosis is also called as computer aided detection .CAD is fundamentally composed of highly complex pattern recognition. CAD systems seek to highlight suspicious structures. Today's CAD systems cannot detect100% of pathological changes. Some of the applications used in the CAD are Pathological Brain Detection (PBD) ,Breast Cancer , lung cancer, colon cancer ,prostate, bone metastases , coronary artery disease , congenital heart defect and Alzheimer's disease. Digital image data are copied to a CAD server in a DICOM-format and are prepared and analyzed in to various steps. They are
A. Preprocessing for
Reduction of artifacts.
Image noise reduction.
Leveling of image quality.
B. Segmentation for
Differentiation of different structures in the images e.g., heart, ribcage and so on.
Matching with anatomic databank.
C. Structures/Region of Interest analyze for
Compactness.
Form, Size and location.
Proportion of grey levels.
D. Evaluation/Classification after the structure is analyzed
Nearest-neighbor Rule.
Minimum distance classifier.
Cascade classifier.
Artificial Neural Network.