Mr. Sajendra Nithiananthan Profile

Sajendra Nithiananthan

Graduate Student at Johns Hopkins Univ.

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Publications (12)

Proceedings Article | 15 March 2013 Paper

Deformable image registration with content mismatch: a demons variant to account for added material and surgical devices in the target image

S. Nithiananthan, A. Uneri, S. Schafer, D. Mirota, Y. Otake, J. Stayman, W. Zbijewski, A. Khanna, D. Reh, G. Gallia, J. Siewerdsen

Proceedings Volume 8671, 86712A (2013) https://doi.org/10.1117/12.2008410

KEYWORDS: Image registration, Image segmentation, Tissues, Distortion, Cements, Image processing, Image-guided intervention, Detection and tracking algorithms, Image processing algorithms and systems, Surgery

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Proceedings Article | 8 March 2013 Paper

A gaussian mixture + demons deformable registration method for cone-beam CT-guided robotic transoral base-of-tongue surgery

S. Reaungamornrat, W. Liu, S. Schafer, Y. Otake, S. Nithiananthan, A. Uneri, J. Richmon, J. Sorger, J. Siewerdsen, R. Taylor

Proceedings Volume 8671, 86710J (2013) https://doi.org/10.1117/12.2007937

KEYWORDS: Image registration, Image segmentation, Tongue, Computed tomography, Clouds, Magnetic resonance imaging, Rigid registration, Surgery, Video, Mouth

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Purpose: An increasingly popular minimally invasive approach to resection of oropharyngeal / base-of-tongue cancer is made possible by a transoral technique conducted with the assistance of a surgical robot. However, the highly deformed surgical setup (neck flexed, mouth open, and tongue retracted) compared to the typical patient orientation in preoperative images poses a challenge to guidance and localization of the tumor target and adjacent critical anatomy. Intraoperative cone-beam CT (CBCT) can account for such deformation, but due to the low contrast of soft-tissue in CBCT images, direct localization of the target and critical tissues in CBCT images can be difficult. Such structures may be more readily delineated in preoperative CT or MR images, so a method to deformably register such information to intraoperative CBCT could offer significant value. This paper details the initial implementation of a deformable registration framework to align preoperative images with the deformed intraoperative scene and gives preliminary evaluation of the geometric accuracy of registration in CBCT-guided TORS. Method: The deformable registration aligns preoperative CT or MR to intraoperative CBCT by integrating two established approaches. The volume of interest is first segmented (specifically, the region of the tongue from the tip to the hyoid), and a Gaussian mixture (GM) mode1 of surface point clouds is used for rigid initialization (GMRigid) as well as an initial deformation (GMNonRigid). Next, refinement of the registration is performed using the Demons algorithm applied to distance transformations of the GM-registered and CBCT volumes. The registration accuracy of the framework was quantified in preliminary studies using a cadaver emulating preoperative and intraoperative setups. Geometric accuracy of registration was quantified in terms of target registration error (TRE) and surface distance error. Result: With each step of the registration process, the framework demonstrated improved registration, achieving mean TRE of 3.0 mm following the GM rigid, 1.9 mm following GM nonrigid, and 1.5 mm at the output of the registration process. Analysis of surface distance demonstrated a corresponding improvement of 2.2, 0.4, and 0.3 mm, respectively. The evaluation of registration error revealed the accurate alignment in the region of interest for base-of-tongue robotic surgery owing to point-set selection in the GM steps and refinement in the deep aspect of the tongue in the Demons step. Conclusions: A promising framework has been developed for CBCT-guided TORS in which intraoperative CBCT provides a basis for registration of preoperative images to the highly deformed intraoperative setup. The registration framework is invariant to imaging modality (accommodating preoperative CT or MR) and is robust against CBCT intensity variations and artifact, provided corresponding segmentation of the volume of interest. The approach could facilitate overlay of preoperative planning data directly in stereo-endoscopic video in support of CBCT-guided TORS.

Proceedings Article | 17 February 2012 Paper

High-performance C-arm cone-beam CT guidance of thoracic surgery

Sebastian Schafer, Yoshito Otake, Ali Uneri, Daniel Mirota, Sajendra Nithiananthan, J. Stayman, Wojciech Zbijewski, Gerhard Kleinszig, Rainer Graumann, Marc Sussman, Jeffrey Siewerdsen

Proceedings Volume 8316, 83161I (2012) https://doi.org/10.1117/12.911811

KEYWORDS: Lung, Video, Surgery, Image registration, Visibility, Tissues, Computed tomography, Visualization, Tumors, Cameras

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Proceedings Article | 17 February 2012 Paper

Tracker-on-C for cone-beam CT-guided surgery: evaluation of geometric accuracy and clinical applications

S. Reaungamornrat, Y. Otake, A. Uneri, S. Schafer, D. Mirota, S. Nithiananthan, J. W. Stayman, A. J. Khanna, D. Reh, G. Gallia, R. Taylor, J. Siewerdsen

Proceedings Volume 8316, 831609 (2012) https://doi.org/10.1117/12.911454

KEYWORDS: Video, Fluoroscopy, Surgery, X-rays, Optical tracking, Visualization, Spine, Radiography, Image registration, X-ray computed tomography

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Conventional surgical tracking configurations carry a variety of limitations in line-of-sight, geometric accuracy, and mismatch with the surgeon's perspective (for video augmentation). With increasing utilization of mobile C-arms, particularly those allowing cone-beam CT (CBCT), there is opportunity to better integrate surgical trackers at bedside to address such limitations. This paper describes a tracker configuration in which the tracker is mounted directly on the Carm. To maintain registration within a dynamic coordinate system, a reference marker visible across the full C-arm rotation is implemented, and the "Tracker-on-C" configuration is shown to provide improved target registration error (TRE) over a conventional in-room setup - (0.9±0.4) mm vs (1.9±0.7) mm, respectively. The system also can generate digitally reconstructed radiographs (DRRs) from the perspective of a tracked tool ("x-ray flashlight"), the tracker, or the C-arm ("virtual fluoroscopy"), with geometric accuracy in virtual fluoroscopy of (0.4±0.2) mm. Using a video-based tracker, planning data and DRRs can be superimposed on the video scene from a natural perspective over the surgical field, with geometric accuracy (0.8±0.3) pixels for planning data overlay and (0.6±0.4) pixels for DRR overlay across all C-arm angles. The field-of-view of fluoroscopy or CBCT can also be overlaid on real-time video ("Virtual Field Light") to assist C-arm positioning. The fixed transformation between the x-ray image and tracker facilitated quick, accurate intraoperative registration. The workflow and precision associated with a variety of realistic surgical tasks were significantly improved using the Tracker-on-C - for example, nearly a factor of 2 reduction in time required for C-arm positioning, reduction or elimination of dose in "hunting" for a specific fluoroscopic view, and confident placement of the x-ray FOV on the surgical target. The proposed configuration streamlines the integration of C-arm CBCT with realtime tracking and demonstrated utility in a spectrum of image-guided interventions (e.g., spine surgery) benefiting from improved accuracy, enhanced visualization, and reduced radiation exposure.

Proceedings Article | 14 February 2012 Paper

Deformable registration of the inflated and deflated lung for cone-beam CT-guided thoracic surgery

Ali Uneri, Sajendra Nithiananthan, Sebastian Schafer, Yoshito Otake, J. Webster Stayman, Gerhard Kleinszig, Marc Sussman, Russell Taylor, Jerry Prince, Jeffrey Siewerdsen

Proceedings Volume 8316, 831602 (2012) https://doi.org/10.1117/12.911440

KEYWORDS: Lung, Image registration, Surgery, Image segmentation, Tumors, Detection and tracking algorithms, Visualization, Computed tomography, Lung cancer, Image-guided intervention

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Proceedings Article | 2 March 2011 Paper

Incorporating tissue excision in deformable image registration: a modified demons algorithm for cone-beam CT-guided surgery

S. Nithiananthan, D. Mirota, A. Uneri, S. Schafer, Y. Otake, J. W. Stayman, J. H. Siewerdsen

Proceedings Volume 7964, 796404 (2011) https://doi.org/10.1117/12.878258

KEYWORDS: Image registration, Tissues, Algorithm development, Computed tomography, Surgery, Head, Neck, 3D image processing, 3D modeling, Prototyping

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Proceedings Article | 2 March 2011 Paper

Architecture of a high-performance surgical guidance system based on C-arm cone-beam CT: software platform for technical integration and clinical translation

Ali Uneri, Sebastian Schafer, Daniel Mirota, Sajendra Nithiananthan, Yoshito Otake, Sureerat Reaungamornrat, Jongheun Yoo, J. Webster Stayman, Douglas Reh, Gary Gallia, A. Jay Khanna, Gregory Hager, Russell Taylor, Gerhard Kleinszig, Jeffrey Siewerdsen

Proceedings Volume 7964, 796422 (2011) https://doi.org/10.1117/12.878191

KEYWORDS: Surgery, Video, Image registration, Computer architecture, Visualization, Fluoroscopy, Endoscopy, 3D image processing, Imaging systems, Computed tomography

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Intraoperative imaging modalities are becoming more prevalent in recent years, and the need for integration of these modalities with surgical guidance is rising, creating new possibilities as well as challenges. In the context of such emerging technologies and new clinical applications, a software architecture for cone-beam CT (CBCT) guided surgery has been developed with emphasis on binding open-source surgical navigation libraries and integrating intraoperative CBCT with novel, application-specific registration and guidance technologies. The architecture design is focused on accelerating translation of task-specific technical development in a wide range of applications, including orthopaedic, head-and-neck, and thoracic surgeries. The surgical guidance system is interfaced with a prototype mobile C-arm for high-quality CBCT and through a modular software architecture, integration of different tools and devices consistent with surgical workflow in each of these applications is realized. Specific modules are developed according to the surgical task, such as: 3D-3D rigid or deformable registration of preoperative images, surgical planning data, and up-to-date CBCT images; 3D-2D registration of planning and image data in real-time fluoroscopy and/or digitally reconstructed radiographs (DRRs); compatibility with infrared, electromagnetic, and video-based trackers used individually or in hybrid arrangements; augmented overlay of image and planning data in endoscopic or in-room video; real-time "virtual fluoroscopy" computed from GPU-accelerated DRRs; and multi-modality image display. The platform aims to minimize offline data processing by exposing quantitative tools that analyze and communicate factors of geometric precision. The system was translated to preclinical phantom and cadaver studies for assessment of fiducial (FRE) and target registration error (TRE) showing sub-mm accuracy in targeting and video overlay within intraoperative CBCT. The work culminates in the development of a CBCT guidance system (reported here for the first time) that leverages the technical developments in Carm CBCT and associated technologies for realizing a high-performance system for translation to clinical studies.

Proceedings Article | 2 March 2011 Paper

High-accuracy 3D image-based registration of endoscopic video to C-arm cone-beam CT for image-guided skull base surgery

Daniel Mirota, Ali Uneri, Sebastian Schafer, Sajendra Nithiananthan, Douglas Reh, Gary Gallia, Russell Taylor, Gregory Hager, Jeffrey Siewerdsen

Proceedings Volume 7964, 79640J (2011) https://doi.org/10.1117/12.877803

KEYWORDS: Image registration, Video, Endoscopy, Surgery, 3D acquisition, 3D image processing, Computed tomography, Visualization, Optical tracking, Skull

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Proceedings Article | 2 March 2011 Paper

Clinical implementation of intraoperative cone-beam CT in head and neck surgery

M. Daly, H. Chan, S. Nithiananthan, J. Qiu, E. Barker, G. Bachar, B. J. Dixon, J. Irish, J. H. Siewerdsen

Proceedings Volume 7964, 796426 (2011) https://doi.org/10.1117/12.878976

KEYWORDS: Head, Surgery, Neck, 3D visualizations, Clinical trials, Endoscopy, Imaging systems, Skull, Bone, Visualization

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Proceedings Article | 3 March 2010 Paper

Fusion of intraoperative cone-beam CT and endoscopic video for image-guided procedures

M. Daly, H. Chan, E. Prisman, A. Vescan, S. Nithiananthan, J. Qiu, R. Weersink, J. Irish, J. Siewerdsen

Proceedings Volume 7625, 762503 (2010) https://doi.org/10.1117/12.844212

KEYWORDS: Endoscopy, Image registration, Endoscopes, Video, Calibration, Head, Optical tracking, Neck, Cameras, Imaging systems

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Proceedings Article | 27 February 2010 Paper

Demons deformable registration for cone-beam CT guidance: registration of pre- and intra-operative images

S. Nithiananthan, K. Brock, M. Daly, H. Chan, J. Irish, J. Siewerdsen

Proceedings Volume 7625, 76250L (2010) https://doi.org/10.1117/12.845499

KEYWORDS: Image registration, X-ray computed tomography, Imaging systems, Head, Neck, Distortion, Computed tomography, Tissues, Reconstruction algorithms, Detection and tracking algorithms

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Proceedings Article | 13 March 2009 Paper

High-performance intraoperative cone-beam CT on a mobile C-arm: an integrated system for guidance of head and neck surgery

J. Siewerdsen, M. Daly, H. Chan, S. Nithiananthan, N. Hamming, K. Brock, J. Irish

Proceedings Volume 7261, 72610J (2009) https://doi.org/10.1117/12.813747

KEYWORDS: Surgery, Image registration, 3D image processing, Head, Neck, Imaging systems, Endoscopy, Image visualization, 3D acquisition, Video

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Showing 5 of 12 publications

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