Bone Fracture Detection Using Image Processing Methods

Author(s):  
M. Uma Devi ◽  
Sweta Nayak ◽  
Aman Gupta
2019 ◽  
Vol 8 (2S3) ◽  
pp. 1246-1249 ◽  

The bone fracture is the most common problem and is likely to occur due to traumatic incidents like vehicle accidents, sporting injuries or due to conditions like osteoporosis, cancer related to bones. Fracture cannot be viewed by naked eye and so X-ray, CT, ultrasound, MRI images are used to detect it. These images cannot be diagnosed directly and henceforth image processing plays a very important role in fracture detection. This paper presents an image processing technique that uses Laplacian method of edge detection for accurate identification of fractured bone area from the X-ray/CT images. From the fractured bone area several parameters like mean, standard deviation are calculated in order to analyze the accuracy and sensitivity of the used technique. NIVISION assistant software is used and the statistical parameters are calculated.


2021 ◽  
Vol 11 (12) ◽  
pp. 3117-3122
Author(s):  
A. Sasidhar ◽  
M. S. Thanabal

Deep learning plays a key role in medical image processing. One of the applications of deep learning models in this domain is bone fracture detection from X-ray images. Convolutional neural network and its variants are used in wide range of medical image processing applications. MURA Dataset is commonly used in various studies that detect bone fractures and this work also uses that dataset, in specific the Humerus bone radiograph images. The humerus dataset in the MURA dataset contains both images with fracture and without fracture. The image with fracture includes images with metals which are removed in this work. Experimental analysis was made with two variants of convolutional neural network, DenseNet169 Model and the VGG Model. In case of the DenseNet169 model, a model with the pre trained weights of ImageNet and one without it is experimented. Results obtained with these variants of CNN are comparedand it shows that DenseNet169 model that uses pre-trained weights of ImageNet model performs better than the other two models.


Quickly creating innovations are developing each day in various fields, particularly in restorative condition. Notwithstanding, still some old strategies are very famous. XRays are one of these systems for identification of bone cracks. By the way, here and there the span of breaks isn't huge and couldn't be recognized effectively. So for the efficient recognition of the crack has become more important . This venture plans to build up an sharp characterization framework that would be equipped for identifying and characterizing the bone cracks. The created framework involves two important stages. In the main stage, the pictures of the breaks are prepared utilizing distinctive picture handling systems in request to identify their area and shapes and the following stage is the arrangement stage, where the sample image is filtered through various filtration stages to obtain the crack effectively, the framework was tried on various bone break pictures and the outcomes show high proficiency what's more, an arrangement rate.


Author(s):  
Iza Sazanita Isa ◽  
Mohamad Khairul Faizi Mat Saad ◽  
Muhammad Haris Khusairi Mohmad Kadir ◽  
Ahmad Afifi Ahmad Afandi ◽  
Noor Khairiah A. Karim ◽  
...  

1989 ◽  
Vol 1989 (14B) ◽  
pp. 25-39
Author(s):  
Katsuaki KOIKE ◽  
Hiroyuki ITOH ◽  
Michito OHMI

2014 ◽  
Vol 2014 ◽  
pp. 1-23 ◽  
Author(s):  
Leonid P. Yaroslavsky

Transform image processing methods are methods that work in domains of image transforms, such as Discrete Fourier, Discrete Cosine, Wavelet, and alike. They proved to be very efficient in image compression, in image restoration, in image resampling, and in geometrical transformations and can be traced back to early 1970s. The paper reviews these methods, with emphasis on their comparison and relationships, from the very first steps of transform image compression methods to adaptive and local adaptive filters for image restoration and up to “compressive sensing” methods that gained popularity in last few years. References are made to both first publications of the corresponding results and more recent and more easily available ones. The review has a tutorial character and purpose.


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