Prof. Narendra Ahuja Profile

Prof. Narendra Ahuja

at Univ of Illinois

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Publications (7)

Proceedings Article | 29 April 2005 Paper

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

Tianli Yu, Jiebo Luo, Amit Singhal, Narendra Ahuja

Proceedings Volume 5747, (2005) https://doi.org/10.1117/12.594662

KEYWORDS: Image segmentation, Lung, Computer programming, Medical imaging, Principal component analysis, Radiography, Statistical analysis, Blood vessels, Chest, Algorithm development

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We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP’s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Proceedings Article | 9 May 2002 Paper

Automated lung nodule segmentation using dynamic programming and EM-based classification

Ning Xu, Narendra Ahuja, Ravi Bansal

Proceedings Volume 4684, (2002) https://doi.org/10.1117/12.467209

KEYWORDS: Expectation maximization algorithms, Lung, Image segmentation, Computer programming, Computed tomography, Tissues, Chest imaging, Distance measurement, Detection and tracking algorithms, Natural surfaces

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Proceedings Article | 17 December 1998 Paper

Gaussian mixture model for human skin color and its applications in image and video databases

Ming-Hsuan Yang, Narendra Ahuja

Proceedings Volume 3656, (1998) https://doi.org/10.1117/12.333865

KEYWORDS: Skin, RGB color model, Expectation maximization algorithms, Statistical analysis, Data modeling, Databases, Statistical modeling, Video, Facial recognition systems, Mahalanobis distance

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Proceedings Article | 6 August 1993 Paper

Use of a nonfrontal camera for extended depth of field in wide scenes

Arun Krishnan, Narendra Ahuja

Proceedings Volume 2056, (1993) https://doi.org/10.1117/12.150186

KEYWORDS: Cameras, Machine vision, Computer vision technology, Robots, Robot vision, Sensors, Lithium, Focus stacking, Information operations, Image sensors

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Proceedings Article | 11 March 1993 Paper

Feature extraction and matching as signal detection

Xiaoping Hu, Narendra Ahuja

Proceedings Volume 1964, (1993) https://doi.org/10.1117/12.141790

KEYWORDS: Signal detection, Feature extraction, Sensors, Evolutionary algorithms, Artificial intelligence, Image processing, Detection and tracking algorithms, Distance measurement, Signal processing, Signal to noise ratio

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Proceedings Article | 1 November 1992 Paper

University of Illinois active vision system

A. Lynn Abbott, Narendra Ahuja

Proceedings Volume 1825, (1992) https://doi.org/10.1117/12.131579

KEYWORDS: Active vision, Imaging systems, Cameras, Image acquisition, Control systems, Visualization, Image processing, Lenses, Zoom lenses, Systems modeling

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Proceedings Article | 1 February 1991 Paper

Dynamic integration of visual cues for position estimation

Subhodev Das, Narendra Ahuja

Proceedings Volume 1382, (1991) https://doi.org/10.1117/12.25227

KEYWORDS: Cameras, Error analysis, Imaging systems, Visualization, Stereoscopic cameras, Biological research, Sensors, Image registration, Robots, Machine vision

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