Abstract
The main aim of this research is the feature vector of the cruciate ligaments finding. This feature vector has to clearly define the ligaments structure and make easier diagnose their. The feature vector finding is based on the successive steps in extraction process of both anterior and posterior cruciate ligaments. In the first stage a region of interest including cruciate ligaments (CL) is outlined. The automatic method of location of the CL on the T1-weighted (T1W) MRI knee images is based on fuzzy C-means (FCM) algorithm with median modification. The next step of that process is an extraction of the cruciate ligament structure using the fuzzy connectedness approach. In the last stage the feature vector is built.
| Original language | English |
|---|---|
| Pages (from-to) | 71-80 |
| Number of pages | 10 |
| Journal | Advances in Intelligent Systems and Computing |
| Volume | 283 |
| DOIs | |
| Publication status | Published - 2014 |
Keywords
- Cruciate ligaments
- Feature vector of the cruciate ligaments
- Fuzzy c-means
- Fuzzy connectedness
ASJC Scopus subject areas
- Control and Systems Engineering
- General Computer Science
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