Biomedical subjects

Shang-Hong Lai

Publications and source records attributed to Shang-Hong Lai.

3 recordsLinked to original sources

PubMed2006

Robust and efficient image alignment based on relative gradient matching.

In this paper, we present a robust image alignment algorithm based on matching of relative gradient maps. This algorithm consists of two stages; namely, a learning-based approximate pattern search and an iterative energy-minimization procedure for matching relative image gradient. The first stage finds some candidate poses of the pattern from the image through a fast nearest-neighbor search of the best match of the relative gradient features computed from training database of feature vectors, which are obtained from the synthesis of the geometrically transformed template image with the transformation parameters uniformly sampled from a given transformation parameter space. Subsequently, the candidate poses are further verified and refined by matching the relative gradient images through an iterative energy- minimization procedure. This approach based on the matching of relative gradients is robust against nonuniform illumination variations. Experimental results on both simulated and real images are shown to demonstrate superior efficiency and robustness of the proposed algorithm over the conventional normalized correlation method.

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PubMed2005

An adaptive window width/center adjustment system with online training capabilities for MR images.

OBJECTIVE: Adaptive and automatic adjustment of the display window parameters for magnetic resonance images under different viewing conditions is a challenging problem in medical image perception. An adaptive hierarchical neural network-based system with online adaptation capabilities is presented to achieve this goal in this paper. METHODOLOGY: The online adaptation capabilities are primarily attributed to the use of the hierarchical neural networks and the development of a new width/center mapping algorithm. The large training image set is hierarchically organized for efficient user interaction and effective re-mapping of the width/center settings. The width/center mapping functions are estimated from the new user-adjusted width/center values of some representative images by using a global spline function for the entire training images as well as a first-order polynomial function for each selected image sequence. The hierarchical neural networks are then re-trained for the new training data set after this mapping process. RESULTS: The proposed automatic display window parameter adjustment system is implemented as a program on a personal computer for testing its adaptation performance. Experimental results show that the proposed system can successfully adapt its parameter adjustment on a variety of MR images after user re-adjustment and re-training of neural networks. CONCLUSION: This demonstrates the effective adaptation capabilities of the proposed system based on the framework of training data mapping and neural network re-training.

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PubMed2003

A dual image approach for bias field correction in magnetic resonance imaging.

In this paper, we propose a dual image approach to correcting intensity inhomogeneities for MR images acquired using surface coils. Previous methods are usually not satisfactory due to restricted application domains, considerable human interactions, or some undesirable artifacts. The proposed algorithm provides nice correction results for a variety of surface-coil MR images. It is accomplished by using an additional body-coil MR image of a smaller size captured at the same position as that of the surface-coil image to facilitate the estimation of the bias field function. The correction algorithm consists of aligning the surface-coil image with the body-coil image and fitting a spline surface from a sparse set of data points for the associated bias field function. Experiments on some real images show satisfactory correction results by using the proposed algorithm.

Algorithms↗