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Fifty sets of photographs showing facial features of Caucasian males aged 18 to 60 years were examined to establish a morphological classification of the face. It is suggested that such a classification coudl assist facial identification by photocomparison. The selection criteria stress the importance of interassessor agreement and discrimination among feature subset units in formulating the proposed classification.

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The objective of this research was to develop an automated system using image processing and statistical modeling techniques to identify and enumerate bacteria on slides containing Salmonella typhimurium. Pictures of bacterial cells were acquired with a CCD camera attached to a motorized fluorescence microscope. A shape boundary modeling technique, based on the use of circular autoregressive model parameters, was used. A minimum‐distance classifier was trained with ten images belonging to each shape class (rod shape and circle shape). Experimental results showed that the model parameters could be used as descriptors of shape boundaries detected in digitized binary images of bacterial cells. In spite of the advantages of human vision, the differences between the computer and a bacteriologist in recognizing and counting of Salmonella cells were less than 8%. The computer analyzed each image in approximately 5 s (a total of 2 h including sample preparation), while the bacteriologist spent an average of 1 min for each image.

Sangrado digestivo bajo masivo por tumor de GIST en un divertículo de Meckel Bleed digestive under severe for tumor of GIST in a Meckel diverticulum