Transformation model plays a vital role in medical image processing. This paper describes a new Transformation model (NTM) which is hybrid of linear and non linear Transformations techniques for the detection of tumor. In NTM, patient image is compared with reference images, which is block based. An image similarity measure quantifies the degree of similarity between intensity patterns in two i...

This chapter describes the steps involved in registering images of different subjects into roughly the same co-ordinate system, where the co-ordinate system is defined by a template image (or series of images). The method only uses up to a few hundred parameters, so can only model global brain shape. It works by estimating the optimum coefficients for a set of bases, by minimizing the sum of sq...

The sum of squared differences (SSD) cost function has generally been overlooked for multimodal registration problems. More recently, methods that employ SSD have been developed to efficiently evaluate the global optimal shift and intensity remapping. However, these methods estimate translations and not rotations. In this paper we propose a method to extend the efficiency of the Least Squares M...

The influence of mobile phase composition on the retention of selected test analytes in different normal- and reversed-phase chromatographic systems is studied. A novel adsorption model for an accurate prediction of the analyte retention in the column chromatography with binary mobile phase is proposed. Performance of the model is compared with the retention model reported in the literature. Bo...

In this work we evaluate a novel method for multi-modal image registration of MR images. The key feature of our approach is a new distance measure that allows for comparing modalities that are related by an arbitrary gray-value mapping. The novel measure is formulated as least square problem for minimizing the sum of squared differences of two images with respect to changing gray-values of one ...

Figure 3: Simulated metabolism using an outer region with ρP=0.027, kP-L=0.018, kL-P=0.125, P∞=1.733, and an inner region with ρP=0.027, kP-L=0.088, kL-P=0.17, P∞=2.5. The default sampling is 30 samples between t=0 and 29 s and a flip angle of 10°. The optimal sampling over the range given above suggests samples at 0, 2.9, 13.1, 41.9 s and flip angles of 23.2, 36.6, 47.3, and 90°. Note the decr...

In computer vision applications, point correspondence plays an important role. Here, we present a technique called geometric blur to find point correspondences between two different images, even in the presence of affine distortions. We compare the results of this technique with other prevalent techniques for finding point correspondences, such as SSD (Sum of Squared Differences) with uniform G...

A novel exemplar-based image inpainting algorithm using the Non-Local Means (NLM) algorithm and Criminisi algorithm is proposed. In order to decrease the error in match rate, the new algorithm adopts the sum of squared differences (SSD) search method for several exemplars to generate a candidate exemplar set. Then it determines the Hausdorff distance as measurement criterion to find a match blo...