Classification of Human Bones Using Deep Convolutional Neural Network

International Conference on Startup Ventures: Technology Developments and Future Strategies

社会科学（总论）

Pradhan, Nitesh^1 ; Singh Dhaka, Vijaypal^2 ; Chaudhary, Himanshu^3

Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur

303007, India^1

Department of Computer and Communication Engineering, Manipal University Jaipur, Jaipur

303007, India^2

Department of Electronics and Communication Engineering, Manipal University Jaipur, Jaipur

303007, India^3

关键词: Classification methods;    Convolutional neural network;    Human bodies;    Human bones;    Radiographic images;    Training sets;    X-ray image;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/594/1/012024/pdf
DOI  :  10.1088/1757-899X/594/1/012024

学科分类：社会科学、人文和艺术（综合）

来源: IOP

【 摘 要 】

In human body, there are total 206 types of different bones. Each bone has its own importance. It is very important to correctly identify human bone and then suggest treatment. To classify the human bones, we will use Musculoskeletal Radiographs (MURA) dataset. MURA dataset is one of the largest public radiographic image datasets. MURA dataset contains total 40,005 x-ray images of 14,052 patients, in which 36,808 images use as a training set and rest 3197 images use the testing set. These all images belong to seven different categories of bones such as finger, elbow, hand, forearm, humerus, wrist and shoulder. This paper aims to present a novel classification method using a deep convolutional neural network (DCNN). Dataset is freely available at https://stanfordmlgroup.github.io/competitions/mura.