Chromosome Image Enhancement

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Image processing has been used in almost all the areas such as remote sensing, military, biomedical, industrial applications. The world is growing more crowded all the time, with a fragile environment that needs protection. Natural resources are becoming increasingly precious and hard to find. This paper is mainly focused on chromosome image enhancement and future extraction based on karyotyping. The features computed and used for analysis include: centromeric index, chromosome size and banding pattern features including total number of bands. A method that is discussed is enhance the image by applying filtering technique and finds the future of centromere detection. This paper is covered the procedure of enhancement and detection of centromere and presented some of results. The results are obtained by different algorithms using MATLAB. 

In the past few years, immense improvement was obtained in the field of content based image retrieval (CBIR); nevertheless, existing systems still fail when applied to medical image databases. Simple feature extraction algorithms that operate on the entire image for characterization of color, texture or shape cannot be related to descriptive semantics of medical knowledge that is extracted from images by human experts. Content based image retrieval (CBIR) system is required to effectively and efficiently use information from these image repositories. Such a system helps user (even though unfamiliar with the database) retrieve relevant images based on their contents. Application areas in which CBIR principles activity are numerous diverse.

Art galleries museum management, architectural and engineering design, interior design remote sensing and management of earth resources geographic information systems scientific database management weather forecasting retailing, fabric and fashion design, trademark and copyright database management, law enforcement and criminal investigation, picture archiving and communication systems. The most important aspect of CBIR is Feature extraction. The features must efficiently describe the most important information conveyed to users in images. In a broad sense features may include both text based description (keywords annotations etc.) and visual features (color, texture, shape, spatial relationship etc.). Since text based feature extraction is already a well-defined field within information retrieval research communities. Visual features can be classified into general features and domain specific features. The formal include color, texture and shape features while the later are application dependent and may include, for example human faces and fingerprints, medical image.

Image processing in medical applications

Image processing has been used in almost all the areas such as remote sensing, military, biomedical, industrial applications. The world is growing more crowded all the time, with a fragile environment that needs protection. Natural resources are becoming increasingly precious and hard to find. Remote sensing images are obtained from satellite and aircraft sensors to study the natural resources available on the earth surface. Space probes are flown to other planets such as Mars, Venus, and Jupiter etc., to get the images of these planets. Various types of satellites are deputed to get high resolution reconnaissance images for military, applications. All these images require Image Processing to increase contrast to get the information by suppressing the noise signals arising out of platform motion, atmosphere and sensor non-linearities.

With the advent of Image Processing techniques, network processing facilities and high resolution and high speed display work stations, doctors all over the world are able to interpret images of patients transmitted from remote areas for clinical diagnosis. Micro surgery is becoming popular due to the availability of Image Processing techniques to display human parts on 3D display systems. Imaging has become an essential component in many fields of medical and laboratory research and clinical practice. Biologists study cells and generate 3D confocal microscopy datasets, virologists generate 3D reconstructions of viruses from micrographs, radiologists identify and quantify tumours from MRI and C T scan, and neuroscientists detect regional metabolic brain activity from PET and functional MRI scan. The use of medical imaging for diagnostic purposes as well as for evaluation of pharmaceutical trials has increased exponentially in recent years.

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Download this file (chromosome image enhancement.doc)Chromosome Image Enhancement[Seminar Report]177 Kb