Research Article
Abnormality Bone Detection in X-Ray Images Using Convolutional Neural Network
@INPROCEEDINGS{10.1007/978-3-030-67101-3_3, author={Hiep Xuan Huynh and Hang Bich Thi Nguyen and Cang Anh Phan and Hai Thanh Nguyen}, title={Abnormality Bone Detection in X-Ray Images Using Convolutional Neural Network}, proceedings={Context-Aware Systems and Applications, and Nature of Computation and Communication. 9th EAI International Conference, ICCASA 2020, and 6th EAI International Conference, ICTCC 2020, Thai Nguyen, Vietnam, November 26--27, 2020, Proceedings}, proceedings_a={ICCASA \& ICTCC}, year={2021}, month={1}, keywords={Abnormality detection Musculoskeletal radiographs X-ray images Convolutional neural network}, doi={10.1007/978-3-030-67101-3_3} }- Hiep Xuan Huynh
Hang Bich Thi Nguyen
Cang Anh Phan
Hai Thanh Nguyen
Year: 2021
Abnormality Bone Detection in X-Ray Images Using Convolutional Neural Network
ICCASA & ICTCC
Springer
DOI: 10.1007/978-3-030-67101-3_3
Abstract
Medical imaging plays a role as a crucial source of data for disease detection and diagnosis. Recent advancements in machine learning and deep learning have become an efficient tool for medical image analysis. Medical image research laboratories are rapidly creating machine learning systems to achieve the professional performance of humans. However, both machine learning and deep learning methods are complex and require a lot of expertise, resources, knowledge, and time to train. Those create a significant barrier for researchers. In this study, we propose a convolutional neural network architecture to detect abnormalities in bone images. The proposed method provides insight into medical images and explains in detail how the model supports the diagnosis.
