Local contrast enhancement of the medical image based on multiscale morphology
	    		
		   		
	    	
    	
    	
   		
        
        	
        		- VernacularTitle:基于多尺度形态学的医学图像局部对比度增强
 
        	
        	
        	
        		- Author:
	        		
		        		
		        		
			        		Derong YE
			        		
			        		;
		        		
		        		
		        		
			        		Yuanyuan ZHAO
			        		
			        		;
		        		
		        		
		        		
			        		Yanhong CHEN
			        		
			        		
		        		
		        		
		        		
		        		
		        		
			        		
			        		
		        		
	        		
        		 
        	
        	
        	
        		- Publication Type:Journal Article
 
        	
        	
            
            
            	- From:
	            		
	            			Chinese Journal of Tissue Engineering Research
	            		
	            		 2006;10(45):200-202,封3
	            	
            	
 
            
            
            	- CountryChina
 
            
            
            	- Language:Chinese
 
            
            
            	- 
		        	Abstract:
			       	
			       		
				        
				        	AIM: To find a more efficient and accurate method for medical image enhancement to resolve the problem of low local contrast, which often appears in magnetic resonance (MR) images.METHODS: Based on the investigation into the previous methods, a new algorithm was presented. The main features were as follows: Non-dual was used in the morphological operations and addition instead of multiplication was used in the contrast stretching operations. To avoid some gray-level bias, the method of normalized gray-level under condition was proposed.RESULTS: The new algorithm was tested by real MR images and simulated experiments. Compared with the previous method, the new method is more accurate, faster and less sensitive to noise.CONCLUSION: Non-dual morphological operations can achieve local contrast enhancement in a more accurate way, and the gray level bias can be eliminated by normalization.