Ramkrishnan Narayanan

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OBJECTIVE Image-guided prostate biopsy has become routine in medical diagnosis. Although it improves biopsy outcome, it mostly operates in 2 dimensions, therefore lacking presentation of information in the complete 3-dimensional (3D) space. Because prostatic carcinomas are nonuniformly distributed within the prostate gland, it is crucial to accurately guide(More)
Due to lack of imaging modalities to identify prostate cancer in vivo, current TRUS guided prostate biopsies are taken randomly. Consequently, many important cancers are missed during initial biopsies. The purpose of this study was to determine the potential clinical utility of a high-speed registration algorithm for a 3D prostate cancer atlas. This 3D(More)
OBJECTIVE For a follow-up prostate biopsy procedure, it is useful to know the previous biopsy locations in anatomic relation to the current transrectal ultrasound (TRUS) scan. The goal of this study was to validate the performance of a 3-dimensional TRUS-guided prostate biopsy system that can accurately relocate previous biopsy sites. METHODS To correlate(More)
Many types of transformations are used to model deformations in medical image registration. While some focus on modeling local changes, some on continuity and invertibility, there is no closed-form nonlinear parametric approach that addresses all these properties. This paper presents a class of nonlinear transformations that are local, continuous and(More)
Image-guided procedures have become routine in medicine. Due to the nature of three-dimensional (3-D) structure of the target organs, two-dimensional (2-D) image acquisition is gradually being replaced by 3-D imaging. Specifically in the diagnosis of prostate cancer, biopsy can be performed using 3-D transrectal ultrasound (TRUS) image guidance. Because(More)
The interest in registering a set of images has quickly risen in the field of medical image analysis. Mutual information (MI) based methods are well-established for pairwise registration but their extension to higher dimensions (multiple images) has encountered practical implementation difficulties. We extend the use of alpha mutual information (alphaMI) as(More)
It is widely established that prostate cancer is a multifocal disease and cancerous lesions are not uniformly distributed within the gland. Current imaging methods cannot detect prostate cancer with sufficient sensitivity and specificity, especially localized cancers. A cancer atlas was previously demonstrated. However the atlas must be registered with a(More)
OBJECTIVE The purpose of this study was to achieve 3D registration of digital tomosynthesis mammographic volumes using mutual information. CONCLUSION Registration of digital breast tomosynthesis mammographic volumes was achieved with an average error of 1.8 +/- 1.4 mm.
Prostate cancer is the most commonly diagnosed cancer in males in the United States and the second leading cause of cancer death. While the exact cause is still under investigation, researchers agree on certain risk factors like age, family history, dietary habits, lifestyle and race. It is also widely accepted that cancer distribution within the prostate(More)