Ownership structure, customer satisfaction and brand equity

This paper studies the interaction between ownership structure, taken as a proxy for shareholders commitment, and customer satisfaction - the main driver of consumer loyalty - and their impact on a firm s brand equity. The results show that customer satisfaction has a positive direct effect on brand equity but an indirect negative one because of reductions in ownership concentration. This latter effect emerges when managers are mainly customer-oriented. Such result gives out a warning signal that highlights the perverse effect of implementing policies, focused excessively on satisfying customers at the expense of shareholders, on a firm s brand equity. The empirical analysis uses an incomplete panel data comprising 69 firms from 11 nations, for the period 2002-2005.

Customer Focus Newsletter, May-June, 2009, Vol. 6, no.3

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, July-August, 2009, Vol. 6, no.4

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.

Customer Focus Newsletter, September-October, 2009, Vol. 6, no.5

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

Customer Focus Newsletter, January-February, 2010, Vol. 7, no.1

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, November-December, 200, Vol. 6, no.6

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, March/April, 2009, Vol. 6, no. 2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

Customer Focus Newsletter, March-April, 2010, Vol. 7, no.2

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.

Customer Focus Newsletter, May-June, 2010, Vol. 7, no.3

A bi-monthly bulletin to keep the department/agency management teams of state government better informed. We hope to consolidate most of the service update messages we send throughout the month and keep you updated about the work of the Customer Councils. If yours is one of the many departments who participated in the second annual DAS customer satisfaction survey recently, we thank you for taking the time to give us this important feedback. We look forward to sharing survey results with you, and pledge to consider responses carefully as we work to determine benchmarks and set future priorities.