Exploiting the Self-Organizing Map for Medical Image Segmentation

2007 ◽  
Author(s):  
Ping-Lin Chang ◽  
Wei-Guang Teng
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
The Self ◽  
Self Organizing Map ◽  
Self Organizing

Segmentasi pada Citra Panoramik Gigi dengan Metode Two-Stage SOM dan T-CLUSTER

2014 ◽  
Vol 6 (1) ◽  
pp. 7-13
Author(s):  
Khoirul Umam ◽  
Fidi Wincoko Putro ◽  
Gulpi Qorik Oktagalu Pratamasunu
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation ◽  
Cluster Method ◽  
Segmentation Result ◽  
Self Organizing Map ◽  
Panoramic Image ◽  
Two Stage ◽  
Segmentation Quality ◽  
Novel Method

Segmentation on medical image requires good quality due to affect the interpretation and diagnosis of medical experts. On medical image segmentation, there is merging phase to increase the quality of the segmentation result. However, stopping criteria on merging phase was determined manually by medical experts. It implied the subjectivity of segmentation result. To increase the objectivity of segmentation result, a method to automate merging phase on medical image segmentation is required. Therefore, we propose a novel method on medical image segmentation which combine two-stage SOM and T-cluster method. Experiments were performed on dental panoramic as medical image sample and evaluated by using segmentation quality formula. Experiments show that the proposed method can perform segmentation on dental panoramic image automatically and objectively with the best average of segmentation quality value is 4,40. Index Terms—dental panoramic image, image segmentation, medical image, Self-Organizing Map, T-cluster

Colour image segmentation using the self-organizing map and adaptive resonance theory

2005 ◽  
Vol 23 (12) ◽  
pp. 1060-1079 ◽  
Author(s):  
N.C. Yeo ◽  
K.H. Lee ◽  
Y.V. Venkatesh ◽  
S.H. Ong
Keyword(s):  
Image Segmentation ◽  
Adaptive Resonance Theory ◽  
The Self ◽  
Self Organizing Map ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Colour Image ◽  
Colour Image Segmentation ◽  
Self Organizing

Design of Superpiexl U-Net Network for Medical Image Segmentation

2019 ◽  
Vol 31 (6) ◽  
pp. 1007 ◽  
Author(s):  
Haiou Wang ◽  
Hui Liu ◽  
Qiang Guo ◽  
Kai Deng ◽  
Caiming Zhang
Keyword(s):  
Image Segmentation ◽  
Medical Image ◽  
Medical Image Segmentation
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