Determination and Analysis of Arthritis Using Digital Image Processing Techniques

Project Code :TMMAIP379


Thickness & condition of Arthritis detection using image processing techniques like anisotropic diffusion, B- spline, canny edge detection, log edge detection, control points adjustment.


Arthritis is a common disorder that affects your joints. It can cause pain and inflammation, making it difficult to move or stay active. This may sometimes lead to disability and chronic ill-health. In this study, MRI scans of the knee were analyzed. 

Estimating the volume or thickness of cartilage at the knee is crucial for determining arthritis. Before segmentation, the image is preprocessed with B-Splines creation. After that, canny and log edge detectors are used to fine-tune the edges. Finally, in order to determine cartilage thickness, the distance between the edges is computed. 

The number of pixels between edges is used to calculate the thickness. The abnormality of arthritis is then determined based on the thickness value. This is a quick and easy approach to evaluate if you have arthritis depending on the thickness of your cartilage.

Keywords: Arthritis, B-Spline, Anisotropic diffusion, Articular-cartilage.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram


Software: Matlab 2018a or above


Operating Systems:

  • Windows 10
  • Windows 7 Service Pack 1
  • Windows Server 2019
  • Windows Server 2016


Minimum: Any Intel or AMD x86-64 processor

Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support


Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation

Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space


Minimum: 4 GB

Recommended: 8 GB

Learning Outcomes

  • Introduction to Matlab
  • How to start with MATLAB
  • About Matlab language
  • Matlab coding skills
  • About tools & libraries
  • Application Program Interface in Matlab
  • About Matlab desktop
  • How to use Matlab editor to create M-Files
  • Features of Matlab
  • Basics on Matlab
  • What is an Image/pixel?
  • About image formats
  • Introduction to Image Processing
  • How digital image is formed
  • Importing the image via image acquisition tools
  • Analyzing and manipulation of image.
  • Phases of image processing:
    • Acquisition
    • Image enhancement
    • Image restoration
    • Color image processing
    •  Image compression
    •  Morphological processing
    • Segmentation etc.,
  • How to extend our work to another real time applications
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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