Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry.

Information about the size of a tumor and its temporal evolution is needed for diagnosis as well as treatment of brain tumor patients. The aim of the study was to investigate the potential of a fully-automatic segmentation method, called BraTumIA, for longitudinal brain tumor volumetry by comparing the automatically estimated volumes with ground truth data acquired via manual segmentation. Longitudinal Magnetic Resonance (MR) Imaging data of 14 patients with newly diagnosed glioblastoma encompassing 64 MR acquisitions, ranging from preoperative up to 12 month follow-up images, was analysed. Manual segmentation was performed by two human raters. Strong correlations (R = 0.83-0.96, p < 0.001) were observed between volumetric estimates of BraTumIA and of each of the human raters for the contrast-enhancing (CET) and non-enhancing T2-hyperintense tumor compartments (NCE-T2). A quantitative analysis of the inter-rater disagreement showed that the disagreement between BraTumIA and each of the human raters was comparable to the disagreement between the human raters. In summary, BraTumIA generated volumetric trend curves of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments comparable to estimates of human raters. These findings suggest the potential of automated longitudinal tumor segmentation to substitute manual volumetric follow-up of contrast-enhancing and non-enhancing T2-hyperintense tumor compartments.

A conserved mode of head segmentation in arthropods revealed by the expression pattern of Hox genes in a spider

Chelicerates constitute a basic arthropod group with fossil representatives from as early as the Cambrian period. Embryonic development and the subdivision of the segmented body region into a prosoma and an opisthosoma are very similar in all extant chelicerates. The mode of head segmentation, however, has long been controversial. Although all other arthropod groups show a subdivision of the head region into six segments, the chelicerates are thought to have the first antennal segment missing. To examine this problem on a molecular level, we have compared the expression pattern of Hox genes in the spider Cupiennius salei with the pattern known from insects. Surprisingly, we find that the anterior expression borders of the Hox genes are in the same register and the same relative segmental position as in Drosophila. This contradicts the view that the homologue of the first antennal segment is absent in the spider. Instead, our data suggest that the cheliceral segment is homologous to the first antennal segment and the pedipalpal segment is homologous to the second antennal (or intercalary) segment in arthropods. Our finding implies that chelicerates, myriapods, crustaceans, and insects share a single mode of head segmentation, reinforcing the argument for a monophyletic origin of the arthropods.

The conserved role of Krox-20 in directing Hox gene expression during vertebrate hindbrain segmentation.

Transient segmentation in the hindbrain is a fundamental morphogenetic phenomenon in the vertebrate embryo, and the restricted expression of subsets of Hox genes in the developing rhombomeric units and their derivatives is linked with regional specification. Here we show that patterning of the vertebrate hindbrain involves the direct upregulation of the chicken and pufferfish group 2 paralogous genes, Hoxb-2 and Hoxa-2, in rhombomeres 3 and 5 (r3 and r5) by the zinc finger gene Krox-20. We identified evolutionarily conserved r3/r5 enhancers that contain high affinity Krox-20. binding sites capable of mediating transactivation by Krox-20. In addition to conservation of binding sites critical for Krox-20 activity in the chicken Hoxa-2 and pufferfish Hoxb-2 genes, the r3/r5 enhancers are also characterized by the presence of a number of identical motifs likely to be involved in cooperative interactions with Krox-20 during the process of hindbrain patterning in vertebrates.

Testing for market segmentation in the A and B share markets of China

Recent research has suggested that the A and B share markets of China may be informationally segmented. In this paper volatility patterns in the A and B share market are studied to establish whether volatility changes to the A and B share markets are synchronous. A consequence of new information, when investors act upon it is that volatility rises. This means that if the A and B markets are perfectly integrated volatility changes to each market would be expected to occur at the same time. However, if they are segmented there is no reason for volatility changes to occur on the same day. Using the iterative cumulative sum of squares across the different markets. Evidence is found of integration between the two A share markets but not between the A and B markets. © 2005 Taylor & Francis Group Ltd.

Benefit segmentation of international travelers to Macau, China

The purpose of this study is threefold: (1) to identify the underlying benefits sought by international visitors to Macau, China, which has emerged as a popular gambling destination in Asia; (2) to segment tourists visiting Macau by employing a cluster analysis based on the benefits sought; and (3) to examine any salient differences between the segment groups with regard to their behavioral characteristics, socio-economic characteristics, and demographic profiles. A convenience sample was used to collect data in the Macau International Airport, in the Macau Ferry Terminal, and at the border gate with Mainland China. A total 1,513 useful surveys were retained for data analysis. Cluster analysis discloses four distinct clusters: "convention and business seekers," "family and vacation seekers," "gambling and shopping seekers," and "multi-purpose seekers." Based on the results of our findings, several managerial implications are discussed. © Taylor & Francis Group, LLC.

Fuzzy c-means variants for medical image segmentation

Segmentation is an important step in many medical imaging applications and a variety of image segmentation techniques exist. One group of segmentation algorithms is based on clustering concepts. In this article we investigate several fuzzy c-means based clustering algorithms and their application to medical image segmentation. In particular we evaluate the conventional hard c-means (HCM) and fuzzy c-means (FCM) approaches as well as three computationally more efficient derivatives of fuzzy c-means: fast FCM with random sampling, fast generalised FCM, and a new anisotropic mean shift based FCM. © 2010 by IJTS, ISDER.

A high efficient biometrics approach for unconstrained iris segmentation and recognition

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineates the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.