Confidence Region Identification and Contour Detection in MRI Image

Algorithm 1

Contour detection with confidence region.

	Input: sequence of image: T1, T2, Flair, T1CE
	MAIN()
	1. INPUT IMAGE
	2. STORE INPUT IMAGE IN AN ARRAY
	3. ADJUST INPUT IMAGE INTENSITIES
	4. BINARISE THE INPUT IMAGE
	5. LABEL IMAGE LABEL-CONNECTED COMPONENT OF BINARY IMAGE
	6. BLOB MEASUREMENT = BY THE MEASURE OF CONNECTED COMPONENTS AREA-WISE AND CENTROID-WISE.
	7. ALL AREA = CALCULATED MEASURE OF ALL INDIVIDUAL CONNECTED COMPONENT
	8. FOR K = 1 TO NO. OF BLOBS
	9.   DISPLAY(ALL_AREA); K = K + 1;
	END
	10. IF THE NUMBER OF BLOBS >0
	11. CALL FUNCTION OF EXTRACT BIGGEST AREA()
	A. SORT ALL AREAS
	B. CHECK AREA IS FROM A MEMBER OF LIST INDEX
	C. SORT THE LIST AND RETURN THE BIGGEST BLOB
	D. RETURN(BIGGEST BLOB)
	E. END
	12.    ELSE CLOSE
	13. L←RESULTANT IMAGE OF THE BIGGEST BLOB STORE IN AN ARRAY
	14. COLOUR THE PIXEL OF THE LARGEST BLOB
	15. ADD THE BIGGEST BLOB TO THE ARRAY
	16. REPEAT
	17. COMBINE BIGGEST BLOBS
	18. EVALUATE FINAL COMBINED BIGGEST BLOB THROUGH DICE, JACQUARD, MEAN SQUARE ERROR, PEAK SIGNAL-TO-NOISE RATIO,
	19. END