The development of skin lesion detection application in smart handheld devices using deep neural networks
| Autor: | Yee Kai Tee, Khin Wee Lai, Maheza Irna Mohd Salim, Hou Ren Tan, Tian Swee Tan, Wun-She Yap, Yan Chai Hum |
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| Rok vydání: | 2021 |
| Předmět: |
Computer Networks and Communications
Computer science business.industry Deep learning 020207 software engineering Computational intelligence 02 engineering and technology Machine learning computer.software_genre Object detection Workflow Hardware and Architecture 0202 electrical engineering electronic engineering information engineering Media Technology Artificial intelligence Android (operating system) Transfer of learning Skin lesion business computer Mobile device Software |
| Zdroj: | Multimedia Tools and Applications. 81:41579-41610 |
| ISSN: | 1573-7721 1380-7501 |
| DOI: | 10.1007/s11042-021-11013-9 |
| Popis: | Early detection of malignant skin lesions improves patient survival rates. Conventional self-detection method for public invariably suffers from limitations: subjectivity, inaccuracy, and expert dependent variability. Therefore, this study presents a detailed development workflow to establish a multimedia-based healthcare systems using computational intelligence, specifically, a mobile application with skin lesion detection capability by integrating state-of-the-art deep learning frameworks that facilitates the global users to execute malignant skin lesions self-detection using a smartphone. We applied transfer learning on various object detection models using ISIC skin lesions dataset with TensorFlow Object Detection API. The selected object detection model is SSD MobileNetV2 with 93.9% of evaluation accuracy. The trained object detection model has been successfully integrated into the mobile application using Firebase ML Kit and has reported low detection time on smartphones. The mobile application has tested to be compatible with various Android versions and screen sizes after we experimented with Firebase Test Lab using seven different smartphones. The trained deep learning model and mobile application development project can be obtained from Github ( https://github.com/UTARSL1/ ). |
| Databáze: | OpenAIRE |
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