End to end system for Pneumonia and lung cancer detection using deep learning

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Abstract

The Deep learning solutions for medical image analysis are offered a promising alternative solution to self-learning problem-specific features and gave a new facet for computer vision challenges. The early detection of pneumonia and lung cancer plays big role in saving the life. Any method or system contributing to early disease detection is likely to reduce the dearth rate of diseases. Our previous work [3] proposed an efficient CNN (EFFI-CNN) for Lung cancer detection. This paper presents a system to detect the pneumonia and lung cancer using deep leaning techniques (ESPLDUDL). The system leverages the EFFI-CNN, Raspberry Pi and Tensor processing Unit (TPU). The system configuration raises the bar in detection results and technology front.

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Ponnada, V. T., & Naga Srinivasu, S. V. (2019). End to end system for Pneumonia and lung cancer detection using deep learning. International Journal of Engineering and Advanced Technology, 8(6), 2888–2893. https://doi.org/10.35940/ijeat.F8791.088619

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