Ultrasound technologies have grown popular in the medical field because they are more accurate however the image quality of hand-held ultrasound devices is comparably Low. The suggested method uses Convolutional Neural Networks to improve the image standard in handheld devices to high visuals. The suggested Convolutional Neural Networks to improve the image standard in handheld devices leading to High visuals. Through histogram equalization the median filter is used to reduce undesired disturbance and to keep the details while maintaining a high dynamic range. To change the vibrant value's histogram the graph balancing method is applied. It spreads out the most frequent pixel intensity values or stretches out the image's intensity range to improve the image contrast. Contrary to what its name suggests unsharp masking is used to sharpen an image. Sharpening is important when post-processing most digital photos since it helps to Emphasis detail. To accomplish higher resolution a Convolutional Neural Network is often used. CNN was created primarily to handle pixel data. It's a hierarchical model that builds a network similar to a funnel and then outputs a fully-connected layer in which all of the neurons are coupled and the outcome is analyzed. By employing CNN it can provide more accurate training with high accuracy and produce a high-quality reconstruction image with fine details structure and speckle.