An FPGA Based Coprocessor for GLCM and Haralick Texture Features and Their Application in Prostate Cancer Classification

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

Interobserver agreement of the Gross Motor Function Classification System in an ambulant population of children with cerebral palsy

Gross Motor Function Classification System (GMFCS) level was reported by three independent assessors in a population of children with cerebral palsy (CP) aged between 4 and 18 years (n=184; 112 males, 72 females; mean age 10y 10mo [SD 3y 7mo]). A software algorithm also provided a computed GMFCS level from a regional CP registry. Participants had clinical diagnoses of unilateral (n=94) and bilateral (n=84) spastic CP, ataxia (n=4), dyskinesia (n=1), and hypotonia (n=1), and could walk independently with or without the use of an aid (GMFCS Levels I-IV). Research physiotherapist (n=184) and parent/guardian data (n=178) were collected in a research environment. Data from the child's community physiotherapist (n=143) were obtained by postal questionnaire. Results, using the kappa statistic with linear weighting (?1w), showed good agreement between the parent/guardian and research physiotherapist (?1w=0.75) with more moderate levels of agreement between the clinical physiotherapist and researcher (?1w=0.64) and the clinical physiotherapist and parent/guardian (?1w=0.57). Agreement was consistently better for older children (>2y). This study has shown that agreement with parent report increases with therapists'experience of the GMFCS and knowledge of the child at the time of grading. Substantial agreement between a computed GMFCS and an experienced therapist (?1w=0.74) also demonstrates the potential for extrapolation of GMFCS rating from an existing CP registry, providing the latter has sufficient data on locomotor ability.

Vegetation history at the multi-period prehistoric complex at Ballynahatty, Co. Down, Northern Ireland.

Palaeoecological methods can provide an environmental context for archaeological sites, enabling the nature of past human activity to be explored from an indirect but alternative perspective. Through a palynological study of a small fen wetland located within the catchment of a multi-period prehistoric complex at Ballynahatty, Co. Down, Northern Ireland, we reconstruct the vegetation history of the area during the early prehistoric period. The pollen record reveals tentative evidence for Mesolithic activity in the area at 6410-6220 cal. BC, with woodland disturbance identified during the Mesolithic-Neolithic transitional period ca. 4430-3890 cal. BC. A more significant impact on the landscape is observed in the Early Neolithic from 3944-3702 cal. BC, with an opening up of the forests and the establishment of a mixed agricultural economy. This activity precedes and continues to be evident during the Mid-Neolithic during which megalithic tombs and related burial sites were constructed at Ballynahatty. Due to chronological uncertainties and a possible hiatus in peat accumulation in the fen, the contemporary environment of the Ballynahatty timber circle complex (constructed and used ca. 3080-2490 cal. BC) and henge (dating to the third millennium cal. BC) cannot certainly be established. Nevertheless, the pollen record suggests that the landscape remained open through to the Bronze Age, implying a long continuity of human activity in the area. These findings support the idea that the Ballynahatty prehistoric complex was the product of a gradual and repeated restructuring of the ritual and ceremonial landscape whose significance continued to be recognised throughout the early prehistoric period.

Support vector machine classification for large data sets via minimum enclosing ball clustering

Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitable for classification of large data sets, because the training complexity of SVM is highly dependent on the size of data set. This paper presents a novel SVM classification approach for large data sets by using minimum enclosing ball clustering. After the training data are partitioned by the proposed clustering method, the centers of the clusters are used for the first time SVM classification. Then we use the clusters whose centers are support vectors or those clusters which have different classes to perform the second time SVM classification. In this stage most data are removed. Several experimental results show that the approach proposed in this paper has good classification accuracy compared with classic SVM while the training is significantly faster than several other SVM classifiers.