Abstract
The rapid increase in medical images makes it more difficult and time-consuming to find relevant images when they are needed. This opens an opportunity to develop technological solutions to solve this problem and help the medical field. This paper proposes a solution for content-based medical image retrieval using a pre-trained deep convolutional neural network. In this work, the Inception V3 model was used with ImageNet weights modifying the last layer to fit the data used. These comprise an open dataset with six classes. The model has been optimized using regularization techniques to obtain 99.98% accuracy in the classification stage and 99% accuracy in the image retrieval stage.
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Ashwath Rao, B., Kini, G.N., Nostas, J. (2022). Content-Based Medical Image Retrieval Using Pretrained Inception V3 Model. In: Dua, M., Jain, A.K., Yadav, A., Kumar, N., Siarry, P. (eds) Proceedings of the International Conference on Paradigms of Communication, Computing and Data Sciences. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-5747-4_55
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DOI: https://doi.org/10.1007/978-981-16-5747-4_55
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