An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.

Comparison of LIMPET contra-rotating wells turbine with theoretical and model test predictions

The performance of the contra-rotating Wells turbine installed in the LIMPET wave power station is compared to the predicted performance from theoretical analysis and model tests. A reasonable agreement was found between the predicted and measured turbine damping characteristic, however the turbine efficiency was found to be poorly predicted. It is postulated that this is due to the unsteady nature and mal-distribution of flow through the LIMPET turbine, which were not considered in the predictions. It is suggested that the reduced performance of the contra-rotating Wells turbine makes biplane or monoplane Wells turbines with guide vanes better solutions for OWC's.

Development of a rapid screening test for veterinary sedatives and the beta-blocker carazolol in porcine kidney by ELISA

Sedatives and tranquillisers are frequently used to reduce stress during the transportation of food producing animals. The most widely used classes of sedatives include the butyrophenone azaperone, the phenothiazines acepromazine, propionylpromazine, chlorpromazine and the beta-blocker, carazolol. For regulatory control purposes, tolerances for azaperone and carazolol have been set by the European Union as 100 and 25 mug kg(-1), respectively. Furthermore, the use of the phenothiazines is prohibited and therefore has a zero tolerance. A method for the detection of residues of five tranquillisers and one beta-blocker using a single ELISA plate has been developed. Kidney samples (2.5 g) were extracted with dichloromethane and applied to a competitive enzyme immunoassay using three polyclonal antibodies raised in rabbits against azaperol, propionylpromazine and carazolol conjugates. In sample matrix, the azaperol antibody cross-reacted 28.0% with azaperone and the propionylpromazine antibody cross-reacted 24.9% with acepromazine and 11.7% with chlorpromazine. In the ELISA, the detection capabilities of the six sedatives, azaperol, azaperone, carazolol, acepromazine, chlorpromazine, and propionylpromazine are 5, 15, 5, 5, 20 and 5 mug kg(-1), respectively. The proposed method is a sensitive and rapid multi-residue technique that offers a cost effective alternative to current published procedures, without any concession on the ability to detect sedative misuse.