Edge AI System for Pneumonia and Lung Cancer Detection
Venkata Tulasiramu Ponnada1, S.V. Naga Srinivasu2
1Venkata Tulasiramu Ponnada, Research Scholar, Acharya Nagarjuna University, Nagarjuna Nagar, Guntur, Andhra Pradesh 522510, India.
2Dr. S. V. Naga Srinivasu, Professor, Computer Science and Engineering, Narasaraopeta Engineering College, Narasaraopet, Andhra Pradesh 522601, India.
Manuscript received on 20 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1908-1915 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8584078919/19©BEIESP | DOI: 10.35940/ijitee.I8584.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The fabulous success of machine learning algorithms for medical image analysis lead the computer aided disease detection systems for medical diagnosis. This paper presents a system “Edge AI System for Pneumonia and Lung Cancer Detection (EASPLD)”. The EASPLD is a unique and one stop solution to detect Pneumonia and Lung cancer. The system is used as a clinician decision supporting system or user system to detect the pneumonia and lung cancer. EASPLD uses deep learning techniques such as convolution neural network (CNN). The proposed solution uses medical image analysis techniques and or methods to develop the system. EASPLD proposed a CNN (EASPLD-CNN) EASPLD-CNN uses seven convolution layers and one max pool layer with 3×3 and 5×5 convolutions, whereas other proposed solutions uses either 3X3 or 5X5 convolutions. In our paper, we used the lung X-Ray and CT scan images from LIDC-IDRI and Mendeley. EASPLD consists of Input image capturing system (IICS), Image enhancement system (IES), EASPLD engine and Results reporting engine (RRE. The EASPLD system output is notified to the end user, i.e. clinician and or a patient in the form of visual, text and email notification.
Index Terms: Edge AI System, Artificial Intelligence, CNN, Deep Learning, Neural Networks, Pneumonia Detection, Lung Cancer Detection, Medical Image Analysis
Scope of the Article: Deep Learning