[Development Case] Development of an Object Detection and Tracking System in CT Images
Detecting and tracking specific substances in CT images.
In 2019, we developed a system for detecting and tracking specific substances in medical CT images for Company M. This involved creating an annotation tool, conducting research, implementing models, training and evaluation, and building an inference system. We created a proprietary tool. To meet the client's requirements, we needed special data, but there was no tool available for labeling it. Therefore, we independently developed an annotation tool and generated the data. Detection and tracking of special objects in unclear CT videos. In this case, the CT images in each frame of the video were coarse, making the detection and tracking of specific substances extremely challenging. However, we overcame this through improvements in the neural network architecture, innovations in image preprocessing, and enhancements to the tracking algorithm. *For more details, please refer to the related links or feel free to contact us.*
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Our company is engaged in various artificial intelligence-related businesses, including artificial intelligence development, artificial intelligence consulting, artificial intelligence seminars, and artificial intelligence application development. Since 2013, we have shifted to Deep Learning, working on improvements to CNNs and RNNs, and by 2015, we developed our own model using RNNs. Additionally, starting in 2016, we expanded our focus to deep reinforcement learning, developing numerous simulation models and robot models. Please feel free to contact us if you have any inquiries.