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Biomedical subjects

Radhika Sivaramakrishna

Publications and source records attributed to Radhika Sivaramakrishna.

3 recordsLinked to original sources

Breast image registration techniques: a survey.

Breast cancer is the most common type of cancer in women worldwide. Image registration plays an important role in breast cancer detection. This paper gives an overview of the current state-of-the-art in the breast image registration techniques. For the intramodality registration techniques, X-ray, MRI, and ultrasound are the primary focuses of interest. Intermodality techniques will cover the combination of different modalities. Validation of breast registration methods is also discussed.

Breast↗

3D breast image registration--a review.

Image registration is an important problem in breast imaging. It is used in a wide variety of applications that include better visualization of lesions on pre- and post-contrast breast MRI images, speckle tracking and image compounding in breast ultrasound images, alignment of positron emission, and standard mammography images on hybrid machines et cetera. It is a prerequisite to align images taken at different times to isolate small interval lesions. Image registration also has useful applications in monitoring cancer therapy. The field of breast image registration has gained considerable interest in recent years. While the primary focus of interest continues to be the registration of pre- and post-contrast breast MRI images, other areas like breast ultrasound registration have gained more attention in recent years. The focus of registration algorithms has also shifted from control point based semi-automated techniques, to more sophisticated voxel based automated techniques that use mutual information as a similarity measure. This paper visits the problem of breast image registration and provides an overview of the current state-of-the-art in this area.

Breast Neoplasms↗

Texture analysis of lesions in breast ultrasound images.

We investigate the use of Haralick's texture features and posterior acoustic attenuation descriptors (PAAD) for the characterization of ultrasound (US) breast lesions. 71 lesions (24 cyst, 21 benign solid mass and 26 malignant solid masses) were manually segmented on two-dimensional breast US images. 28 Haralick's descriptors and two PAAD were evaluated on these segmented lesions. Mean of Sum Average, Range of Sum Entropy and the second PAAD best discriminated cysts from noncysts. Range of Correlation and the second PAAD best discriminated solid malignant from benign lesions. Computerized analysis of breast US images can increase the specificity of breast sonography by providing a better characterization of solid lesions.

Breast Neoplasms↗