Volume 14, number 2
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Watershed Algorithm and Adaptive Threshold Canny Edge Detection Based Automatic Segmentation of Tibio Femoral Cartilage from MRI Images

Punit Kumar Singh1, Garima Sharma2 and Prashant Kumar Pandey3

1Department of Biomedical Engineering, BBDNITM, Lucknow, India.

2Department of Biomedical Engineering, Bundelkhand University, Jhansi, India.

3Department of  Electronics and Communication Engineering, Ansal Technical Campus, Lucknow, India.

Corresponding Author E-mail: waytopunit@yahoo.com

DOI : http://dx.doi.org/10.13005/bbra/2517

ABSTRACT: Restorative Analysis of the femoral ligament by thickness estimation utilizing the strategies of picture division has demonstrated very viable device for joint ailment determination. There is a lot of work has been done in different procedures of division of MRI pictures of ligament. In this review we have created Watershed calculation for programmed division of knee ligament pictures along with application of versatile shrewd edge discovery which has made it more compelling. The space amongst tibia and femur in knee joint is portioned by Watershed Algorithm. Extra separating through morphological operations-picture widening and disintegration with double picture opening capacities is then connected to expel uproarious locales to precisely segmentthe required area from the generally portioned district. Edges in the harsh district were removed out by the versatile limit watchful edge identifier. At last the precise division was accomplished by extricating the picture information in the highlighted area.

KEYWORDS: Automatic Segmentation; MR Images; Watershed Algorithm; Edge Canny Detection

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Singh P. K, Sharma G, Pandey P. K. Watershed Algorithm and Adaptive Threshold Canny Edge Detection Based Automatic Segmentation of Tibio Femoral Cartilage from MRI Images. Biosci Biotech Res Asia 2017;14(2).

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Singh P. K, Sharma G, Pandey P. K. Watershed Algorithm and Adaptive Threshold Canny Edge Detection Based Automatic Segmentation of Tibio Femoral Cartilage from MRI Images. Biosci Biotech Res Asia 2017;14(2). Available from: https://www.biotech-asia.org/?p=24774

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