This paper is published in Volume-4, Issue-2, 2018
Area
Image Processing
Author
Fanendra Kumar Patel, Manoj Singh
Org/Univ
Disha Institute of Management and Technology, Raipur, Chhattisgarh, India
Keywords
Knee cartilage, Dicom images, Watershed segmentation etc.
Citations
IEEE
Fanendra Kumar Patel, Manoj Singh. Segmentation of cartilage from knee MRI images using the watershed algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Fanendra Kumar Patel, Manoj Singh (2018). Segmentation of cartilage from knee MRI images using the watershed algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.
MLA
Fanendra Kumar Patel, Manoj Singh. "Segmentation of cartilage from knee MRI images using the watershed algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.
Fanendra Kumar Patel, Manoj Singh. Segmentation of cartilage from knee MRI images using the watershed algorithm, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Fanendra Kumar Patel, Manoj Singh (2018). Segmentation of cartilage from knee MRI images using the watershed algorithm. International Journal of Advance Research, Ideas and Innovations in Technology, 4(2) www.IJARIIT.com.
MLA
Fanendra Kumar Patel, Manoj Singh. "Segmentation of cartilage from knee MRI images using the watershed algorithm." International Journal of Advance Research, Ideas and Innovations in Technology 4.2 (2018). www.IJARIIT.com.
Abstract
We present here watershed segmentation method for the segmentation of knee cartilage. Watershed segmentation is a state of the art method and involves great simplicity of application. MRI images of the knee cartilages are used for segmenting and early detection of the osteoarthritis. MRI images offer better visualization of the soft tissues like cartilage still visualization of the tissues prone to damage is needed to be detected earlier. However, the method incorporates noise while segmentation stills its great simplicity attracts researchers for its use.
