This study attempted to accurately segment tumors in mammograms. Although this task is considered to be a preprocessing step in a computer analysis program, it plays an important role for further analysis of breast lesions. The region of interest (ROI) was segmented using the pixel aggregation and region growing techniques combined with maximum likelihood analysis. A fast segmentation algorithm...

In this paper, an automatic seeded region growing algorithm is proposed for cellular image segmentation. First, the regions of interest (ROIs) extracted from the preprocessed image. Second, the initial seeds are automatically selected based on ROIs extracted from the image. Third, the most reprehensive seeds are selected using a machine learning algorithm. Finally, the cellular image is segment...

This paper details work undertaken on the application of JPEG 2000, the recent ISO/ITU-T image compression standard based on wavelet technology, to region of interest (ROI) coding. The paper briefly outlines the JPEG 2000 encoding algorithm and explains how the packet structure of the JPEG 2000 bit-stream enables an encoded image to be decoded in a variety of ways dependent upon the application...

This paper discusses the use of neural networks to locate regions of interest (ROIs) for fingerprint classification using feature-encoded fingerprint images. The target areas are those useful for the classification of fingerprints: whorls, loops, arches, and deltas. Our approach is to limit the amount of data which a classification algorithm must consider by determining with high accuracy those...

Region Of Interest Based Image Classification (ROIBIC) is a mechanism for categorising images according to some specific component or object that features across a given image set. This paper describes and compares two such approaches. The first is founded on a weighted graph mining technique whereby the ROI is represented using a tree structure which allows the application of a weighted graph ...

Medical image repositories contain very large amounts of computer tomography (CT) scans. When querying a particular CT scan, the user is often not interested in the complete scan but in a certain region of interest (ROI). Unfortunately, specifying the ROI in terms of scan coordinates is usually not an option because an ROI is usually specified w.r.t. the scan content, e.g. an example region in ...

The wavelet localization technique was recently applied to the application of Region-of-Interest tomography. It achieves a signi cant saving in the required projections if only a small region of a tomographic image is of interest. In this paper, we rstly show that, with the same sampling requirement, a simple interpolation scheme applied on the samples can give a result at least as good as that...

Standard direct image registration consists in estimating the geometric warp between a source and a target images by maximizing the photometric similarity for the pixels of a Region of Interest (ROI). The ROI must be included in the real overlap between the images otherwise standard registration algorithms fail. Determining a proper ROI is a hard ‘chicken-and-egg’ problem since the overlap is o...

A novel technique to detect regions of interest in a time series as deviation from the characteristic behavior is proposed. The deterministic form of a signal is obtained using a reliably trained MLP neural network with detailed complexity management and cross-validation based generalization assurance. The proposed technique is demonstrated with simulated and real data.