Digital Image Processing

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DICOM Image Processing for MRI Lung Image using Morphological function and Watershed Segmentation


Affiliations
1 Computer Science & Engg. at Chandigarh Engg. College, Landran, Mohali, India
2 Department of Computer Science & Engineering at Chandigarh Engineering. College, Landran, Mohali, India
     

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The paper describes very efficient method for processing lungs images for detection of abnormality in images. The result of image shows the portion containing abnormality. The process combines various methods for image enhancement including histogram equalization, gabor and fast fourier transform for improving quality of image to optimize the result of segmentation to best configuration. The process further combines morphological functions including tophat, bottomhat and watershed segmentation to effectively separate the region of interest to detect abnormality in image. Finally the portion marked by segmentation is extracted using masking and binary thresholding to obtain the abnormal features from images.

Keywords

Bottom Hat Function, Fast Fourier Transform, Gabor Filter, Histogram Equalization, Masking, Morphological Function, Top Hat Function, Watershed Segmentation.
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  • DICOM Image Processing for MRI Lung Image using Morphological function and Watershed Segmentation

Abstract Views: 238  |  PDF Views: 1

Authors

Poonam Bhayan
Computer Science & Engg. at Chandigarh Engg. College, Landran, Mohali, India
Gagandeep Jindal
Department of Computer Science & Engineering at Chandigarh Engineering. College, Landran, Mohali, India

Abstract


The paper describes very efficient method for processing lungs images for detection of abnormality in images. The result of image shows the portion containing abnormality. The process combines various methods for image enhancement including histogram equalization, gabor and fast fourier transform for improving quality of image to optimize the result of segmentation to best configuration. The process further combines morphological functions including tophat, bottomhat and watershed segmentation to effectively separate the region of interest to detect abnormality in image. Finally the portion marked by segmentation is extracted using masking and binary thresholding to obtain the abnormal features from images.

Keywords


Bottom Hat Function, Fast Fourier Transform, Gabor Filter, Histogram Equalization, Masking, Morphological Function, Top Hat Function, Watershed Segmentation.