Image Processing of Ultrasound Color Doppler to Characterize Malignant Breast Lesion

Breast cancer, the most common cancer in women, is one of the major causes for the increase in mortality among women especially in developed countries. Doppler ultrasound is an important noninvasive diagnostic tool for identifying breast malignancies. We present a novel technique for segmenting blood vessels in ultrasound color Doppler images based on image processing techniques. The proposed technique decomposes a complex object representing either two or more vessels artificially linked together or a main vessel with its branches. We segment out the blood vessels in ultrasound color Doppler images and count the number of vessels to detect breast malignancy. Matlab has been used to simulate the algorithm and the results obtained are presented in this paper. The result represents distinct vessels that can be used in further object recognition and quantification applications.

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Color Doppler to Characterize Malignant Breast Lesion

International Journal of Life Science and Medical Research ◽

10.5963/lsmr0202003 ◽

2012 ◽

Vol 2 (2) ◽

pp. 24-27 ◽

Cited By ~ 2

Author(s):

Subarna Chatterjee ◽

Ajoy Kumar Ray ◽

Rezaul Karim ◽

Arindam Biswas

Keyword(s):

Breast Lesion ◽

Color Doppler ◽

Malignant Breast Lesion ◽

Malignant Breast

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Correlation of expression of hormone and HER2 receptors with various clinico-pathological prognostic parameters and with each other in malignant breast lesion

Annals of Diagnostic Pathology ◽

10.1016/j.anndiagpath.2020.151659 ◽

2021 ◽

Vol 50 ◽

pp. 151659

Author(s):

Swati Sucharita Mohanty

Keyword(s):

Breast Lesion ◽

Prognostic Parameters ◽

Malignant Breast Lesion ◽

Malignant Breast

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Retinal vessel feature extraction from fundus image using image processing techniques

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.8892 ◽

2018 ◽

Vol 7 (2) ◽

pp. 687

Author(s):

R. Lavanya ◽

G. K. Rajini ◽

G. Vidhya Sagar

Keyword(s):

Image Processing ◽

Diabetic Retinopathy ◽

Early Detection ◽

Blood Vessels ◽

Retinal Vessel ◽

Retinal Images ◽

Image Processing Techniques ◽

Vessel Detection ◽

Proper Diagnosis ◽

Processing Techniques

Retinal Vessel detection for retinal images play crucial role in medical field for proper diagnosis and treatment of various diseases like diabetic retinopathy, hypertensive retinopathy etc. This paper deals with image processing techniques for automatic analysis of blood vessel detection of fundus retinal image using MATLAB tool. This approach uses intensity information and local phase based enhancement filter techniques and morphological operators to provide better accuracy.Objective: The effect of diabetes on the eye is called Diabetic Retinopathy. At the early stages of the disease, blood vessels in the retina become weakened and leak, forming small hemorrhages. As the disease progress, blood vessels may block, and sometimes leads to permanent vision loss. To help Clinicians in diagnosis of diabetic retinopathy in retinal images with an early detection of abnormalities with automated tools.Methods: Fundus photography is an imaging technology used to capture retinal images in diabetic patient through fundus camera. Adaptive Thresholding is used as pre-processing techniques to increase the contrast, and filters are applied to enhance the image quality. Morphological processing is used to detect the shape of blood vessels as they are nonlinear in nature.Results: Image features like, Mean and Standard deviation and entropy, for textural analysis of image with Gray Level Co-occurrence Matrix features like contrast and Energy are calculated for detected vessels.Conclusion: In diabetic patients eyes are affected severely compared to other organs. Early detection of vessel structure in retinal images with computer assisted tools may assist Clinicians for proper diagnosis and pathology.

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