Further details about CNNs, the significance of each of their components, and how they perform image classification have been described by Karpathy et al. adjusting the coefficients of the linear equations in each layer, until the desired output is achieved. The network is trained by a method of back propagation, i.e. Each layer passes its output to the next layer, with an overlaid nonlinearity. The input image is passed through multiple “layers” in a feed forward manner, each layer comprising multiple, independent, and linear convolutional filters.
Convolutional neural networks (CNNs) are a special class of ANNs which take a whole image as input and classify the image in defined categories. Thus, it has the ability to build up its own rules, referred to as “experience”. It calibrates it's coefficients as to perform a certain task, e.g., pattern recognition. There is a need for a generic image analysis tool for screening liquid based cervical cytology (LBCC) smears.Īrtificial neural networks (ANN) are systems of linear algebra that mimic the way the brain computes information. However, both of these systems are closed source, with proprietary rights and are tightly adherent to their respective devices, and require staining methods directed by the company. Presently, the Focal Point Slide Profiler (FSPS) ® (BD Tripath Imaging) and the ThinPrep Imaging System ® have been approved by FDA as primary screening tools for cervical cytology smears. Thus, there has been interest in automated screening of cervical smears. Screening LBCC for abnormal cells is a demanding and labor intensive task requiring a significant investment in man hours. Liquid based cervical cytology (LBCC) has emerged as the standard of care for screening cervical cancer, due to its higher sensitivity and specificity than conventional smears, reduced artifacts such as blood, mucus, and other debris in the slide, reduced the rate of false negative diagnoses and a reduction in inadequate smears.
In India the incidence rate of cervical cancer is 14.7/100000 women per year, making it the second most common cancer in Indian women. Cancer of the cervix uteri is the second most common cancer among women worldwide.
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