TY - GEN
T1 - Feature vectors of the cruciate ligaments of the knee joint
AU - Zarychta, Piotr
N1 - Publisher Copyright:
Copyright © 2015 Department of Microelectronics and Computer Science, Lodz Univeristy of Technology.
PY - 2015/8/17
Y1 - 2015/8/17
N2 - The most important and primary aims of this article are two elements. The first one is a presentation of the feature vectors of the anterior and posterior cruciate ligaments of the knee joint and the second element is a discussion on the choice of the most effective features. In order to build the feature vectors, the extraction of the cruciate ligaments structures from the MRI images of the knee joint was necessary. This operation has been made on the basis of the following fuzzy methods: fuzzy C-means algorithm with median modification (in order to find a region of interest including cruciate ligaments), and fuzzy connectedness (in order to extract the cruciate ligaments). The presented methodology has been tested on 74 clinical T1-weighted MRI slices of the knee joint. On the basis of the described methodology a software application has been built. This software application is dedicated for the anterior and posterior cruciate ligaments diagnostics and it seems to be a very helpful for the orthopedists.
AB - The most important and primary aims of this article are two elements. The first one is a presentation of the feature vectors of the anterior and posterior cruciate ligaments of the knee joint and the second element is a discussion on the choice of the most effective features. In order to build the feature vectors, the extraction of the cruciate ligaments structures from the MRI images of the knee joint was necessary. This operation has been made on the basis of the following fuzzy methods: fuzzy C-means algorithm with median modification (in order to find a region of interest including cruciate ligaments), and fuzzy connectedness (in order to extract the cruciate ligaments). The presented methodology has been tested on 74 clinical T1-weighted MRI slices of the knee joint. On the basis of the described methodology a software application has been built. This software application is dedicated for the anterior and posterior cruciate ligaments diagnostics and it seems to be a very helpful for the orthopedists.
KW - feature vectors of the cruciate ligaments of the knee joint
KW - fuzzy C-means algorithm with median modification
KW - fuzzy connectedness
KW - medical image segmentation
UR - https://www.scopus.com/pages/publications/84953791146
U2 - 10.1109/MIXDES.2015.7208487
DO - 10.1109/MIXDES.2015.7208487
M3 - Conference contribution
AN - SCOPUS:84953791146
T3 - Proceedings of the 22nd International Conference Mixed Design of Integrated Circuits and Systems, MIXDES 2015
SP - 88
EP - 92
BT - Proceedings of the 22nd International Conference Mixed Design of Integrated Circuits and Systems, MIXDES 2015
A2 - Napieralski, Andrzej
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference Mixed Design of Integrated Circuits and Systems, MIXDES 2015
Y2 - 25 June 2015 through 27 June 2015
ER -