Medical Imaging

We propose a new hierarchical approach to resolution scalable lossless and near-lossless (NLS) compression. It combines the adaptability of DPCM schemes with new hierarchical oriented predictors to provide resolution scalability with better compression performances than the usual hierarchical interpolation predictor or the wavelet transform. Because the proposed hierarchical oriented prediction (HOP) is not really efficient on smooth images, we also

In the modern world, people are beliving videos as part of social communication; as camera editing
techniques are advanced, video doctoring is a technique for editing and recreating new details in the footage.
Identifying these doctored videos poses a problem for the media source, the court of law, and the framework of
evidence service. The research on video forensics, and specifically on the automatic recognition of object-based
detection of video forgery, is still in its infancy. The approach proposed in this paper uses noise properties,
extracted from each frame of the video using Wavelet Transform and nonlinear thresholding such as optimal
SURE shrinkage. Gaussian Mixture Density (GMD) uses this as a Gaussian classifier, and the ExpectationMaxima algorithm sets the GMD parameter. Results of the output matrix show that we get excellent precision
99.36 percent recall 99.80 and precision 97.34 percent respectively for object removal and frame duplication
detection compared to subsisting methods. The proposed approach effectively detects traces in the forensic video
dataset and recognizes these.

We present a model of energy consumption in IP networks. Using this model, we identify energy ldquohotspotsrdquo and estimate how energy consumption will grow with increasing network capacity. Todaypsilas Internet uses less than 1% of the available electricity supply. However, network energy consumption could grow substantially as access rates increase.

Skin diseases are among the most common health problems worldwide. In this article we proposed a method that uses computer vision based techniques to detect various kinds of dermatological skin diseases. We have used different types of image processing algorithms for feature extraction and feed forward artificial neural network for training and testing purpose. The system works on two phases- first pre-process the colour skin images to extract significant features and later identifies the diseases. The system successfully detects 9 different types of dermatological skin diseases with an accuracy rate of 90%.

Following the development and publication of the JCAMP-DX protocol 4.24 and its successful implementation in the field of infrared spectroscopy, data exchange without loss of information, between systems of different origin and internal format, has become a reality. The benefits of this system-independent data transfer standard have been recognized by workers in other areas who have expressed a wish for an equivalent, compatible standard in their own fields. This publication details a protocol for the exchange of Nuclear Magnetic Resonance (NMR) spectral data without any loss of information and in a format that is compatible with all storage media and computer systems. The protocol detailed below is designed for spectral data transfer, and its use for NMR imaging data transfer has not as yet been investigated.

Detecting the position of retinal structures, including the fovea center and macula, in retinal images plays a key role in diagnosing eye diseases such as optic nerve hypoplasia, amblyopia, diabetic retinopathy, and macular edema. However, current detection methods are unreliable for infants or certain ethnic populations. Thus, a methodology is proposed here that may be useful for infants and across ethnicities that automatically localizes the fovea center and segments the macula on digital fundus images. First, dark structures and bright artifacts are removed from the input image using preprocessing operations, and the resulting image is transformed to polar space. Second, the fovea center is identified, and the macula region is segmented using the proposed dynamic identification and classification of edges (DICE) model. The performance of the method was evaluated using 1200 fundus images obtained from the relatively large, diverse, and publicly available Messidor database. In 96.1...

Aim-To determine the gender using mental foramen as landmark on a panoramic radiographs in selected North Gujarat population. Objective-1. To evaluate and compare the superior border of mental foramen to lower border of mandible(S-L) and inferior border of mental foramen to lower border of mandible(I-L) value in males and females bilaterally. 2. To compare the S-L and I-L between right and left side in males and female 3. To utilize above measurements for gender determination. Materials and Method-Sixty panoramic radiographs were selected for the analysis of mental foramen. Tangents were drawn through the superior and inferior borders of the foramen (S-L and I-L respectively) and perpendicular from the tangents to the lower border of the mandible bilaterally. Digital verniar caliper was used for the distance measurement from S-L and I-L. The data obtained was tabulated and subjected to statistical analysis. Result-The analyzed data of study showed that the mean values of comparison of S-L as well as I-L in males and females were significantly higher in males as compared to females. The comparison of SL and IL on right and left side in the same patient was without any significant difference. Conclusion-The results of present study concluded a definite sexual dimorphism in the position of the mental foramen from the base of the mandible; this method can applied in mass disaster where the fragments of mandible are available.