The localization of four neuropeptidelike substances during embryonic development in amphibian was studied by using immuno cytochemical technique. The cells with positive reaction appeared firstly in the endoderm ce...The localization of four neuropeptidelike substances during embryonic development in amphibian was studied by using immuno cytochemical technique. The cells with positive reaction appeared firstly in the endoderm cells during early tailbud stage, and then were detected in connective tissue at the outer portion of gastrointestinal tract during tadpole stage. In the nervous system, the cells with positive reaction were observed in cranial ganglion and glial cells at the outer margin of the brain and in the inner wall of ventricles. They were also frequently observed in the epidermis during late tailbud stage. The relationship between the appearance of neuropeptides in timespatial sequences and the development of nervous system, the neural crest origin of the cells with positive reaction, and the role of epidermal conductivity in neuropeptidelike cells in epiderms were discussed.展开更多
Severe sex ratio imbalance at birth is now becoming an important issue in several Asian countries. Its leading immediate cause is prenatal sex-selective abortion following illegal sex identification by ultrasound scan...Severe sex ratio imbalance at birth is now becoming an important issue in several Asian countries. Its leading immediate cause is prenatal sex-selective abortion following illegal sex identification by ultrasound scanning. In this paper, a fast automatic recognition and location algorithm for fetal genital organs is proposed as an effective method to help prevent ultrasound technicians from unethically and illegally identifying the sex of the fetus. This automatic recognition algorithm can be divided into two stages. In the 'rough' stage, a few pixels in the image, which are likely to represent the genital organs, are automatically chosen as points of interest (POIs) according to certain salient characteristics of fetal genital organs. In the 'fine' stage, a specifically supervised learning framework, which fuses an effective feature data preprocessing mechanism into the multiple classifier architecture, is applied to every POI. The basic classifiers in the framework are selected from three widely used classifiers: radial basis function network, backpropagation network, and support vector machine. The classification results of all the POIs are then synthesized to determine whether the fetal genital organ is present in the image, and to locate the genital organ within the positive image. Experiments were designed and carried out based on an image dataset comprising 658 positive images (images with fetal genital organs) and 500 negative images (images without fetal genital organs). The experimental results showed true positive (TP) and true negative (TN) results from 80.5% (265 from 329) and 83.0% (415 from 500) of samples, respectively. The average computation time was 453 ms per image.展开更多
文摘The localization of four neuropeptidelike substances during embryonic development in amphibian was studied by using immuno cytochemical technique. The cells with positive reaction appeared firstly in the endoderm cells during early tailbud stage, and then were detected in connective tissue at the outer portion of gastrointestinal tract during tadpole stage. In the nervous system, the cells with positive reaction were observed in cranial ganglion and glial cells at the outer margin of the brain and in the inner wall of ventricles. They were also frequently observed in the epidermis during late tailbud stage. The relationship between the appearance of neuropeptides in timespatial sequences and the development of nervous system, the neural crest origin of the cells with positive reaction, and the role of epidermal conductivity in neuropeptidelike cells in epiderms were discussed.
文摘Severe sex ratio imbalance at birth is now becoming an important issue in several Asian countries. Its leading immediate cause is prenatal sex-selective abortion following illegal sex identification by ultrasound scanning. In this paper, a fast automatic recognition and location algorithm for fetal genital organs is proposed as an effective method to help prevent ultrasound technicians from unethically and illegally identifying the sex of the fetus. This automatic recognition algorithm can be divided into two stages. In the 'rough' stage, a few pixels in the image, which are likely to represent the genital organs, are automatically chosen as points of interest (POIs) according to certain salient characteristics of fetal genital organs. In the 'fine' stage, a specifically supervised learning framework, which fuses an effective feature data preprocessing mechanism into the multiple classifier architecture, is applied to every POI. The basic classifiers in the framework are selected from three widely used classifiers: radial basis function network, backpropagation network, and support vector machine. The classification results of all the POIs are then synthesized to determine whether the fetal genital organ is present in the image, and to locate the genital organ within the positive image. Experiments were designed and carried out based on an image dataset comprising 658 positive images (images with fetal genital organs) and 500 negative images (images without fetal genital organs). The experimental results showed true positive (TP) and true negative (TN) results from 80.5% (265 from 329) and 83.0% (415 from 500) of samples, respectively. The average computation time was 453 ms per image.
