Automatic identification of fungi in microscopic leucorrhea images
Jing Zhang, Songhan Lu, Xiangzhou Wang, Xiaohui Du, Guangming Ni, Juanxiu Liu, Lin Liu, Yong Liu · Journal of the Optical Society of America A · 2017
Identifying fungi in microscopic leucorrhea images provides important information for evaluating gynecological diseases. Subjective judgment and fatigue can greatly affect recognition accuracy. This paper proposes an automatic identification system to detect fungi in leucorrhea images that incorporates a convolutional neural network, the histogram of oriented gradients algorithm, and a binary support vector machine. In experiments, the detection rate of the positive samples was as high as 99.8%. The experimental results demonstrate the effectiveness of the proposed method and its potential as a primary software component of a completely automated system.