Dr. Gouthami Chintalapani Profile

Dr. Gouthami Chintalapani

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Publications (5)

Proceedings Article | 2 March 2011 Paper

Alternative statistical methods for bone atlas modelling

Sharmishtaa Seshamani, Gouthami Chintalapani, Russell Taylor

Proceedings Volume 7964, 79642O (2011) https://doi.org/10.1117/12.878686

KEYWORDS: Principal component analysis, Modeling, Data modeling, Bone, Statistical modeling, Statistical methods, Silicon, Matrices, Error analysis, Shape analysis

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Proceedings Article | 27 February 2010 Paper

Statistical atlas based extrapolation of CT data

Gouthami Chintalapani, Ryan Murphy, Robert Armiger, Jyri Lepisto, Yoshito Otake, Nobuhiko Sugano, Russell Taylor, Mehran Armand

Proceedings Volume 7625, 762539 (2010) https://doi.org/10.1117/12.845570

KEYWORDS: Computed tomography, Image registration, Data modeling, X-rays, Statistical analysis, Phased array optics, X-ray computed tomography, X-ray imaging, Statistical modeling, Error analysis

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Proceedings Article | 31 March 2008 Paper

Dynamic dosimetry and edema detection in prostate brachytherapy: a complete system

A. Jain, A. Deguet, I. Iordachita, G. Chintalapani, J. Blevins, Y. Le, E. Armour, C. Burdette, D. Song, G. Fichtinger

Proceedings Volume 6918, 69181Y (2008) https://doi.org/10.1117/12.772352

KEYWORDS: Prostate, X-rays, Image segmentation, X-ray imaging, Tissues, Calibration, Image registration, 3D modeling, 3D image reconstruction, Distortion

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Purpose: Brachytherapy (radioactive seed insertion) has emerged as one of the most effective treatment options for patients with prostate cancer, with the added benefit of a convenient outpatient procedure. The main limitation in contemporary brachytherapy is faulty seed placement, predominantly due to the presence of intra-operative edema (tissue expansion). Though currently not available, the capability to intra-operatively monitor the seed distribution, can make a significant improvement in cancer control. We present such a system here. Methods: Intra-operative measurement of edema in prostate brachytherapy requires localization of inserted radioactive seeds relative to the prostate. Seeds were reconstructed using a typical non-isocentric C-arm, and exported to a commercial brachytherapy delivery system. Technical obstacles for 3D reconstruction on a non-isocentric C-arm include pose-dependent C-arm calibration; distortion correction; pose estimation of C-arm images; seed reconstruction; and C-arm to TRUS registration. Results: In precision-machined hard phantoms with 40-100 seeds and soft tissue phantoms with 45-87 seeds, we correctly reconstructed the seed implant shape with an average 3D precision of 0.35 mm and 0.24 mm, respectively. In a DoD Phase-1 clinical trial on 6 patients with 48-82 planned seeds, we achieved intra-operative monitoring of seed distribution and dosimetry, correcting for dose inhomogeneities by inserting an average of 4.17 (1-9) additional seeds. Additionally, in each patient, the system automatically detected intra-operative seed migration induced due to edema (mean 3.84 mm, STD 2.13 mm, Max 16.19 mm). Conclusions: The proposed system is the first of a kind that makes intra-operative detection of edema (and subsequent re-optimization) possible on any typical non-isocentric C-arm, at negligible additional cost to the existing clinical installation. It achieves a significantly more homogeneous seed distribution, and has the potential to affect a paradigm shift in clinical practice. Large scale studies and commercialization are currently underway.

Proceedings Article | 22 March 2007 Paper

C-arm calibration: is it really necessary?

Ameet Kumar Jain, Michael An, Nicha Chitphakdithai, Gouthami Chintalapani, Gabor Fichtinger

Proceedings Volume 6509, 65092U (2007) https://doi.org/10.1117/12.712301

KEYWORDS: Calibration, Distortion, Fluoroscopy, 3D modeling, X-ray imaging, X-rays, X-ray sources, Image registration, 3D image processing, Affine motion model

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Proceedings Article | 22 March 2007 Paper

Statistical characterization of C-arm distortion with application to intra-operative distortion correction

Gouthami Chintalapani, Ameet Jain, Russell Taylor

Proceedings Volume 6509, 65092Y (2007) https://doi.org/10.1117/12.711605

KEYWORDS: Distortion, Principal component analysis, Sensors, Statistical analysis, Video, Data modeling, 3D modeling, Error analysis, Image intensifiers, 3D image processing

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