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64,1,120,500,334,1040,570,0,155,CW,500,129,47,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +27,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,146,CW,500,140,51,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +28,CT,SIEMENS,Sensation Cardiac 64,1,120,500,368,1040,570,0,166,CW,500,274,101,0,B50f,1,MONOCHROME2,"['0.71875', '0.71875']" +29,CT,SIEMENS,Sensation Cardiac 64,1,120,500,359,1040,570,0,204,CW,500,180,66,0,B50f,1,MONOCHROME2,"['0.701171875', '0.701171875']" +30,CT,SIEMENS,Sensation Cardiac 64,1,120,500,388,1040,570,0,131,CW,500,402,148,0,B50f,1,MONOCHROME2,"['0.7578125', '0.7578125']" +31,CT,SIEMENS,Sensation Cardiac 64,1,120,500,311,1040,570,0,127,CW,500,40,14,0,B50f,1,MONOCHROME2,"['0.607421875', '0.607421875']" +32,CT,SIEMENS,Sensation Cardiac 64,1,120,500,319,1040,570,0,182,CW,500,51,18,0,B50f,1,MONOCHROME2,"['0.623046875', '0.623046875']" +34,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,145,CW,500,130,48,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +35,CT,SIEMENS,Sensation Cardiac 64,1,120,500,270,1040,570,0,154,CW,500,172,63,0,B50f,1,MONOCHROME2,"['0.52734375', '0.52734375']" +36,CT,SIEMENS,Sensation Cardiac 64,1,120,500,354,1040,570,0,162,CW,500,111,41,0,B50f,1,MONOCHROME2,"['0.69140625', '0.69140625']" +37,CT,SIEMENS,Sensation Cardiac 64,1,120,500,368,1040,570,0,156,CW,500,157,58,0,B50f,1,MONOCHROME2,"['0.71875', '0.71875']" +38,CT,SIEMENS,Sensation Cardiac 64,1,120,500,255,1040,570,0,179,CW,500,103,38,0,B50f,1,MONOCHROME2,"['0.498046875', '0.498046875']" +39,CT,SIEMENS,Sensation Cardiac 64,1,120,500,359,1040,570,0,191,CW,500,263,97,0,B50f,1,MONOCHROME2,"['0.701171875', '0.701171875']" +40,CT,SIEMENS,Sensation Cardiac 64,1,120,500,299,1040,570,0,173,CW,500,107,39,0,B50f,1,MONOCHROME2,"['0.583984375', '0.583984375']" +41,CT,SIEMENS,Sensation Cardiac 64,1,120,500,308,1040,570,0,208,CW,500,81,29,0,B50f,1,MONOCHROME2,"['0.6015625', '0.6015625']" +42,CT,SIEMENS,Sensation Cardiac 64,1,120,500,313,1040,570,0,141,CW,500,170,62,0,B50f,1,MONOCHROME2,"['0.611328125', '0.611328125']" +43,CT,SIEMENS,Sensation Cardiac 64,1,120,500,313,1040,570,0,169,CW,500,199,73,0,B50f,1,MONOCHROME2,"['0.611328125', '0.611328125']" +44,CT,SIEMENS,Sensation Cardiac 64,1,120,500,262,1040,570,0,135,CW,500,171,63,0,B50f,1,MONOCHROME2,"['0.51171875', '0.51171875']" +45,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,153,CW,500,308,114,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +46,CT,SIEMENS,Sensation Cardiac 64,1,120,500,381,1040,570,0,128,CW,500,354,131,0,B50f,1,MONOCHROME2,"['0.744140625', '0.744140625']" +47,CT,SIEMENS,Sensation Cardiac 64,1,120,500,333,1040,570,0,181,CW,500,146,54,0,B50f,1,MONOCHROME2,"['0.650390625', '0.650390625']" +48,CT,SIEMENS,Sensation Cardiac 64,1,120,500,365,1040,570,0,173,CW,500,240,88,0,B50f,1,MONOCHROME2,"['0.712890625', '0.712890625']" +49,CT,SIEMENS,Sensation Cardiac 64,1,120,500,367,1040,570,0,125,CW,500,234,86,0,B50f,1,MONOCHROME2,"['0.716796875', '0.716796875']" +50,CT,SIEMENS,Sensation Cardiac 64,1,120,500,268,1040,570,0,240,CW,500,47,17,0,B50f,1,MONOCHROME2,"['0.5234375', '0.5234375']" +51,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,161,CW,500,76,28,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +52,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,127,CW,500,197,72,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +53,CT,SIEMENS,Sensation Cardiac 64,1,120,500,452,1040,570,0,209,CW,500,242,89,0,B50f,1,MONOCHROME2,"['0.8828125', '0.8828125']" +54,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,170,CW,500,150,55,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +55,CT,SIEMENS,Sensation Cardiac 64,1,120,500,374,1040,570,0,162,CW,500,206,76,0,B50f,1,MONOCHROME2,"['0.73046875', '0.73046875']" +56,CT,SIEMENS,Sensation Cardiac 64,1,120,500,313,1040,570,0,157,CW,500,254,94,0,B50f,1,MONOCHROME2,"['0.611328125', '0.611328125']" +57,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,156,CW,500,313,115,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +58,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,161,CW,500,107,39,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +59,CT,SIEMENS,Sensation Cardiac 64,1,120,500,328,1040,570,0,169,CW,500,181,67,0,B50f,1,MONOCHROME2,"['0.640625', '0.640625']" +60,CT,SIEMENS,Sensation Cardiac 64,1,120,500,361,1040,570,0,172,CW,500,302,111,0,B50f,1,MONOCHROME2,"['0.705078125', '0.705078125']" +61,CT,SIEMENS,Sensation Cardiac 64,1,120,500,344,1040,570,0,149,CW,500,224,82,0,B50f,1,MONOCHROME2,"['0.671875', '0.671875']" +62,CT,SIEMENS,Sensation Cardiac 64,1,120,500,362,1040,570,0,169,CW,500,292,108,0,B50f,1,MONOCHROME2,"['0.70703125', '0.70703125']" +63,CT,SIEMENS,Sensation Cardiac 64,1,120,500,422,1040,570,0,182,CW,500,219,81,0,B50f,1,MONOCHROME2,"['0.82421875', '0.82421875']" +64,CT,SIEMENS,Sensation Cardiac 64,1,100,500,334,1040,570,0,187,CW,500,270,100,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +65,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,191,CW,500,105,38,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +66,CT,SIEMENS,Sensation Cardiac 64,1,120,500,366,1040,570,0,174,CW,500,144,53,0,B50f,1,MONOCHROME2,"['0.71484375', '0.71484375']" +67,CT,SIEMENS,Sensation Cardiac 64,1,120,500,361,1040,570,0,159,CW,500,197,72,0,B50f,1,MONOCHROME2,"['0.705078125', '0.705078125']" +68,CT,SIEMENS,Sensation Cardiac 64,1,120,500,337,1040,570,0,207,CW,500,106,39,0,B50f,1,MONOCHROME2,"['0.658203125', '0.658203125']" +69,CT,SIEMENS,Sensation Cardiac 64,1,120,500,304,1040,570,0,137,CW,500,117,43,0,B50f,1,MONOCHROME2,"['0.59375', '0.59375']" +70,CT,SIEMENS,Sensation Cardiac 64,1,120,500,272,1040,570,0,173,CW,500,324,120,0,B50f,1,MONOCHROME2,"['0.53125', '0.53125']" +71,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,196,CW,500,203,75,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +72,CT,SIEMENS,Sensation Cardiac 64,1,120,500,378,1040,570,0,158,CW,500,248,91,0,B50f,1,MONOCHROME2,"['0.73828125', '0.73828125']" +73,CT,SIEMENS,Sensation Cardiac 64,1,120,500,394,1040,570,0,157,CW,500,64,23,0,B50f,1,MONOCHROME2,"['0.76953125', '0.76953125']" +74,CT,SIEMENS,Sensation Cardiac 64,1,120,500,374,1040,570,0,173,CW,500,124,45,0,B50f,1,MONOCHROME2,"['0.73046875', '0.73046875']" +75,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,161,CW,500,237,87,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +76,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,170,CW,500,66,24,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +77,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,154,CW,500,206,76,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +78,CT,SIEMENS,Sensation Cardiac 64,1,140,500,458,1040,570,0,136,CW,500,324,120,0,B50f,1,MONOCHROME2,"['0.89453125', '0.89453125']" +79,CT,SIEMENS,Sensation Cardiac 64,1,120,500,375,1040,570,0,194,CW,500,116,42,0,B50f,1,MONOCHROME2,"['0.732421875', '0.732421875']" +80,CT,SIEMENS,Sensation Cardiac 64,1,120,500,356,1040,570,0,138,CW,500,101,37,0,B50f,1,MONOCHROME2,"['0.6953125', '0.6953125']" +81,CT,SIEMENS,Sensation Cardiac 64,1,120,500,320,1040,570,0,172,CW,500,210,77,0,B50f,1,MONOCHROME2,"['0.625', '0.625']" +82,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,134,CW,500,207,76,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +83,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,136,CW,500,215,79,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +84,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,146,CW,500,55,20,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +85,CT,SIEMENS,Sensation Cardiac 64,1,120,500,319,1040,570,0,133,CW,500,132,48,0,B50f,1,MONOCHROME2,"['0.623046875', '0.623046875']" +86,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,170,CW,500,228,84,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +87,CT,SIEMENS,Sensation Cardiac 64,1,120,500,371,1040,570,0,175,CW,500,380,140,0,B50f,1,MONOCHROME2,"['0.724609375', '0.724609375']" +88,CT,SIEMENS,Sensation Cardiac 64,1,120,500,380,1040,570,0,140,CW,500,294,108,0,B50f,1,MONOCHROME2,"['0.7421875', '0.7421875']" +89,CT,SIEMENS,Sensation Cardiac 64,1,120,500,354,1040,570,0,154,CW,500,319,118,0,B50f,1,MONOCHROME2,"['0.69140625', '0.69140625']" +90,CT,SIEMENS,Sensation Cardiac 64,1,120,500,393,1040,570,0,180,CW,500,298,110,0,B50f,1,MONOCHROME2,"['0.767578125', '0.767578125']" +91,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,175,CW,500,183,67,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +92,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,189,CW,500,120,44,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +93,CT,SIEMENS,Sensation Cardiac 64,1,120,500,373,1040,570,0,182,CW,500,67,24,0,B50f,1,MONOCHROME2,"['0.728515625', '0.728515625']" +94,CT,SIEMENS,Sensation Cardiac 64,1,120,500,353,1040,570,0,186,CW,500,108,40,0,B50f,1,MONOCHROME2,"['0.689453125', '0.689453125']" +95,CT,SIEMENS,Sensation Cardiac 64,1,120,500,340,1040,570,0,176,CW,500,177,65,0,B50f,1,MONOCHROME2,"['0.6640625', '0.6640625']" +96,CT,SIEMENS,Sensation Cardiac 64,1,120,500,312,1040,570,0,149,CW,500,54,20,0,B50f,1,MONOCHROME2,"['0.609375', '0.609375']" +97,CT,SIEMENS,Sensation Cardiac 64,1,120,500,379,1040,570,0,176,CW,500,238,88,0,B50f,1,MONOCHROME2,"['0.740234375', '0.740234375']" +98,CT,SIEMENS,Sensation Cardiac 64,1,120,500,340,1040,570,0,148,CW,500,170,62,0,B50f,1,MONOCHROME2,"['0.6640625', '0.6640625']" +99,CT,SIEMENS,Sensation Cardiac 64,1,120,500,363,1040,570,0,194,CW,500,318,117,0,B50f,1,MONOCHROME2,"['0.708984375', '0.708984375']" +100,CT,SIEMENS,Sensation Cardiac 64,1,120,500,329,1040,570,0,148,CW,500,156,57,0,B50f,1,MONOCHROME2,"['0.642578125', '0.642578125']" +101,CT,SIEMENS,Sensation Cardiac 64,1,120,500,351,1040,570,0,188,CW,500,234,86,0,B50f,1,MONOCHROME2,"['0.685546875', '0.685546875']" +102,CT,SIEMENS,Sensation Cardiac 64,1,120,500,358,1040,570,0,186,CW,500,146,54,0,B50f,1,MONOCHROME2,"['0.69921875', '0.69921875']" +103,CT,SIEMENS,Sensation Cardiac 64,1,120,500,380,1040,570,0,153,CW,500,96,35,0,B50f,1,MONOCHROME2,"['0.7421875', '0.7421875']" +104,CT,SIEMENS,Sensation Cardiac 64,1,120,500,351,1040,570,0,189,CW,500,211,78,0,B50f,1,MONOCHROME2,"['0.685546875', '0.685546875']" +105,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,389.353000000026,983,535,0,168,CW,533,105,56,None,"['Br60f', '3']",1,MONOCHROME2,"['0.613095703125', '0.6131543307']" +106,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,302.8,983,535,0,137,CW,533,106,56,None,"['Br60f', '3']",1,MONOCHROME2,"['0.59140625', '0.59140625']" +107,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,354,1085.6,595,0,146.5,CW,500,164,68,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.69140625', '0.69140625']" +108,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,326,1085.6,595,0,160.5,CW,500,213,88,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.63671875', '0.63671875']" +109,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,348.8,983,535,0,136,CW,533,51,27,None,"['Br64f', '3']",1,MONOCHROME2,"['0.68125', '0.68125']" +110,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,367.8,983,535,0,165,CW,533,97,51,None,"['Br64f', '3']",1,MONOCHROME2,"['0.718359375', '0.718359375']" +111,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,370.049000000154,983,535,0,153,CW,533,103,54,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5674921875', '0.56755981595092']" +112,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,380,983,535,0,159,CW,533,102,54,None,"['Br64f', '3']",1,MONOCHROME2,"['0.7421875', '0.7421875']" +113,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,387.0,983,535,0,140,CW,533,94,50,None,"['Br64f', '3']",1,MONOCHROME2,"['0.755859375', '0.755859375']" +114,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,387.999999999984,983,535,0,155,CW,533,167,89,None,"['Br64f', '3']",1,MONOCHROME2,"['0.651533203125', '0.6510067114']" +115,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,319,1085.6,595,0,200,CW,285,1522,143,WEDGE_2,B31f,1,MONOCHROME2,"['0.623046875', '0.623046875']" +116,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,299.4,983,535,0,158,CW,533,65,34,None,"['Br60f', '3']",1,MONOCHROME2,"['0.584765625', '0.584765625']" +117,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,330,983,535,0,139,CW,533,50,26,None,"['Br60f', '3']",1,MONOCHROME2,"['0.64453125', '0.64453125']" +118,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,364,1085.6,595,0,164,CW,285,592,84,WEDGE_2,B50f,1,MONOCHROME2,"['0.7109375', '0.7109375']" +119,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,344.216000000056,983,535,0,144,CW,533,52,27,None,"['Br64f', '3']",1,MONOCHROME2,"['0.535732421875', '0.5353281493']" +120,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,345,1085.6,595,0,161,CW,500,90,37,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.673828125', '0.673828125']" +121,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,403.203000000084,983,535,0,181,CW,533,238,126,None,"['Br64f', '3']",1,MONOCHROME2,"['0.72442578125', '0.7238833034']" +122,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,413.8,983,535,0,176,CW,1000,59,59,None,"['Br64f', '3']",1,MONOCHROME2,"['0.808203125', '0.808203125']" +123,CT,SIEMENS,Sensation Cardiac 64,1,120,500,334,1040,570,0,153,CW,500,140,51,0,B50f,1,MONOCHROME2,"['0.65234375', '0.65234375']" +124,CT,SIEMENS,Sensation Cardiac 64,1,120,500,364,1040,570,0,161,CW,500,298,110,0,B50f,1,MONOCHROME2,"['0.7109375', '0.7109375']" +125,CT,SIEMENS,Sensation Cardiac 64,1,100,500,262,1040,570,0,144,CW,500,118,43,0,B50f,1,MONOCHROME2,"['0.51171875', '0.51171875']" +126,CT,SIEMENS,Sensation Cardiac 64,1,120,500,345,1040,570,0,189,CW,500,234,86,0,B50f,1,MONOCHROME2,"['0.673828125', '0.673828125']" +127,CT,SIEMENS,Sensation Cardiac 64,1,120,500,344,1040,570,0,194,CW,500,176,65,0,B50f,1,MONOCHROME2,"['0.671875', '0.671875']" +128,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,449,1085.6,595,0,239.5,CW,500,421,175,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.876953125', '0.876953125']" +129,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,379,1085.6,595,0,177,CW,500,176,73,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.740234375', '0.740234375']" +130,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,321,1085.6,595,0,184,CW,500,207,86,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.626953125', '0.626953125']" +131,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,164,CW,500,301,125,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +132,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,164,CW,500,196,81,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +133,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,320,1085.6,595,0,115.5,CW,500,89,37,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.625', '0.625']" +134,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,325,1085.6,595,0,159,CW,500,182,75,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.634765625', '0.634765625']" +135,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,419,1085.6,595,0,175.5,CW,285,1577,224,WEDGE_2,B50f,1,MONOCHROME2,"['0.818359375', '0.818359375']" +136,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,452.300999999772,983,535,0,155,CW,1000,71,71,None,"['Br64f', '3']",1,MONOCHROME2,"['0.714384765625', '0.714535545']" +137,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,342.000000000024,983,535,0,197,CW,533,70,37,None,"['Br64f', '3']",1,MONOCHROME2,"['0.552625', '0.5525040388']" +138,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,336,1085.6,595,0,181,CW,500,210,87,WEDGE_3,"['I70f', '2']",1,MONOCHROME2,"['0.65625', '0.65625']" +139,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,385.852000000094,983,535,0,143,CW,533,96,51,None,"['Br64f', '3']",1,MONOCHROME2,"['0.53518359375', '0.5351622746']" +140,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,377.509000000108,983,535,0,141,CW,533,59,31,None,"['Br64f', '3']",1,MONOCHROME2,"['0.57175390625', '0.5719833333']" +141,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,295.110999999998,983,535,0,134,CW,533,47,25,None,"['Br64f', '3']",1,MONOCHROME2,"['0.473337890625', '0.47369341894061']" +142,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,361.999999999812,983,535,0,180,CW,533,114,60,None,"['Br64f', '3']",1,MONOCHROME2,"['0.626810546875', '0.6262975779']" +143,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,357.681000000004,983,535,0,152,CW,533,70,37,None,"['Br64f', '3']",1,MONOCHROME2,"['0.589349609375', '0.5892602965']" +144,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,380.925000000132,983,535,0,164,CW,533,67,35,None,Br64f,1,MONOCHROME2,"['0.616626953125', '0.6163834951']" +145,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,358,1085.6,595,0,187,CW,285,1028,145,WEDGE_2,B50f,1,MONOCHROME2,"['0.69921875', '0.69921875']" +146,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,383,1085.6,595,0,163.5,CW,500,225,93,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.748046875', '0.748046875']" +147,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,339,1085.6,595,0,164,CW,500,192,80,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.662109375', '0.662109375']" +148,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,392.037000000038,983,535,0,135,CW,533,106,56,None,"['Br64f', '3']",1,MONOCHROME2,"['0.609826171875', '0.6096998445']" +149,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,332,1085.6,595,0,164,CW,500,92,38,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.6484375', '0.6484375']" +150,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,369.460000000094,983,535,0,136,CW,533,89,47,None,"['Br64f', '3']",1,MONOCHROME2,"['0.488654296875', '0.4887037037']" +151,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,297,1085.6,595,0,164,CW,500,137,57,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.580078125', '0.580078125']" +152,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,360.669999999808,983,535,0,133,CW,533,82,43,None,"['Br64f', '3']",1,MONOCHROME2,"['0.48583203125', '0.4860781671']" +153,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,379.355000000122,983,535,0,154,CW,533,113,60,None,"['Br64f', '3']",1,MONOCHROME2,"['0.576904296875', '0.5765273556231']" +154,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,345.389999999994,983,535,0,172,CW,533,110,58,None,"['Br64f', '3']",1,MONOCHROME2,"['0.601197265625', '0.6006782609']" +155,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,333.76100000010,983,535,0,125,CW,533,73,38,None,"['Br64f', '3']",1,MONOCHROME2,"['0.47876953125', '0.4788536585']" +156,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,356.000000000114,983,535,0,136,CW,533,58,30,None,"['Br64f', '3']",1,MONOCHROME2,"['0.518677734375', '0.5189504373']" +157,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,355.049999999872,983,535,0,167,CW,533,67,35,None,"['Br64f', '3']",1,MONOCHROME2,"['0.561720703125', '0.5617879747']" +158,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,320.654999999910,983,535,0,190,CW,533,52,27,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5855078125', '0.5851368613']" +159,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,364.999999999862,983,535,0,151,CW,533,92,49,None,"['Br64f', '3']",1,MONOCHROME2,"['0.610125', '0.610367893']" +160,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,400.695000000192,983,535,0,184,CW,1000,71,71,None,"['Br64f', '3']",1,MONOCHROME2,"['0.607107421875', '0.6071136364']" +161,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,309,1085.6,595,0,164,CW,500,243,101,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.603515625', '0.603515625']" +162,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,294,1085.6,595,0,122,CW,500,36,15,WEDGE_3,B50f,1,MONOCHROME2,"['0.57421875', '0.57421875']" +163,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,345.993000000096,983,535,0,132,CW,533,147,78,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5335859375', '0.5339398148']" +164,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,332,1085.6,595,0,162.5,CW,285,147,76,WEDGE_3,B70f,1,MONOCHROME2,"['0.6484375', '0.6484375']" +165,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,352.981999999856,983,535,0,144,CW,533,237,126,None,"['Br64f', '3']",1,MONOCHROME2,"['0.56851171875', '0.5684090177']" +167,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,327,1085.6,595,0,149.5,CW,500,75,31,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.638671875', '0.638671875']" +168,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,373.617999999908,983,535,0,167,CW,533,70,37,None,"['Br64f', '3']",1,MONOCHROME2,"['0.62420703125', '0.623736227']" +169,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,206,CW,500,283,117,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +170,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,185,CW,500,228,95,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +171,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,368.088999999922,983,535,0,191,CW,533,74,39,None,"['Br64f', '3']",1,MONOCHROME2,"['0.63399609375', '0.6335438898']" +172,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,356.999999999958,983,535,0,134,CW,533,60,32,None,"['Br64f', '3']",1,MONOCHROME2,"['0.44420703125', '0.4440298507']" +174,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,340.939000000002,983,535,0,155,CW,533,64,34,None,"['Br64f', '3']",1,MONOCHROME2,"['0.554220703125', '0.5543723577']" +175,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,290.000000000134,983,535,0,152,CW,533,51,27,None,"['Br64f', '3']",1,MONOCHROME2,"['0.4880703125', '0.4882154882']" +177,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,368.99999999992,983,535,0,161,CW,533,111,59,None,"['Br64f', '3']",1,MONOCHROME2,"['0.619576171875', '0.6191275168']" +178,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,320.529000000172,983,535,0,156,CW,533,53,28,None,"['Br64f', '3']",1,MONOCHROME2,"['0.44871875', '0.4489201681']" +179,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,307.000000000150,983,535,0,153,CW,533,78,41,None,"['Br64f', '3']",1,MONOCHROME2,"['0.53978515625', '0.539543058']" +180,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,400.695000000192,983,535,0,184,CW,1000,99,99,None,"['Br64f', '3']",1,MONOCHROME2,"['0.607107421875', '0.6071136364']" +181,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,309,1085.6,595,0,164,CW,500,202,84,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.603515625', '0.603515625']" +182,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,294,1085.6,595,0,122,CW,500,21,8,WEDGE_3,B50f,1,MONOCHROME2,"['0.57421875', '0.57421875']" +183,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,345.993000000096,983,535,0,132,CW,533,56,29,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5335859375', '0.5339398148']" +184,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,332,1085.6,595,0,162.5,CW,285,62,32,WEDGE_3,B70f,1,MONOCHROME2,"['0.6484375', '0.6484375']" +185,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,352.981999999856,983,535,0,144,CW,533,99,52,None,"['Br64f', '3']",1,MONOCHROME2,"['0.56851171875', '0.5684090177']" +186,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,164,CW,500,421,175,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +187,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,327,1085.6,595,0,149.5,CW,500,150,62,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.638671875', '0.638671875']" +188,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,373.617999999908,983,535,0,167,CW,533,106,56,None,"['Br64f', '3']",1,MONOCHROME2,"['0.62420703125', '0.623736227']" +189,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,206,CW,500,204,85,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +190,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,402,1085.6,595,0,185,CW,500,196,81,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.78515625', '0.78515625']" +191,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,368.088999999922,983,535,0,191,CW,533,74,39,None,"['Br64f', '3']",1,MONOCHROME2,"['0.63399609375', '0.6335438898']" +192,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,356.999999999958,983,535,0,134,CW,533,80,42,None,"['Br64f', '3']",1,MONOCHROME2,"['0.44420703125', '0.4440298507']" +194,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,340.939000000002,983,535,0,155,CW,533,55,29,None,"['Br64f', '3']",1,MONOCHROME2,"['0.554220703125', '0.5543723577']" +195,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,290.000000000134,983,535,0,152,CW,533,41,21,None,"['Br64f', '3']",1,MONOCHROME2,"['0.4880703125', '0.4882154882']" +198,CT,SIEMENS,SOMATOM go.Up,1,130.000,499.8,307.000000000150,983,535,0,153,CW,533,81,43,None,"['Br64f', '3']",1,MONOCHROME2,"['0.53978515625', '0.539543058']" +200,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,354,1085.6,595,0,186,CW,500,147,61,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.69140625', '0.69140625']" +201,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,366.104077633556,983,535,0,168.000,CW,533,183,97,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5914458805', '0.5914453125']" +202,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,352.977442584048,983,535,0,157.000,CW,533,97,51,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5506677067', '0.55066796875']" +203,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,384.488664865494,983,535,0,176.000,CW,533,201,107,None,"['Br64f', '3']",1,MONOCHROME2,"['0.7120148148', '0.712015625']" +205,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,359,1085.6,595,0,173.5,CW,500,261,108,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.701171875', '0.701171875']" +207,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,381,1085.6,595,0,171.5,CW,500,156,65,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.744140625', '0.744140625']" +208,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,305,1085.6,595,0,189,CW,500,145,60,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.595703125', '0.595703125']" +209,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,315.697737169008,983,535,0,156.000,CW,533,56,29,None,"['Br64f', '3']",1,MONOCHROME2,"['0.61659765625', '0.61659765625']" +210,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,366,983,535,0,184.500,CW,533,91,48,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6192893401', '0.6192890625']" +211,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,388,983,535,0,160.000,CW,1000,91,91,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6843051146', '0.6843046875']" +212,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,387.045549752672,983,535,0,156.000,CW,533,164,87,SN,"['Br60f', '3']",1,MONOCHROME2,"['0.4886957071', '0.4886953125']" +213,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,367,983,535,0,163.000,CW,533,82,43,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5663595679', '0.566359375']" +214,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,388,983,535,0,183.500,CW,533,111,59,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6879414894', '0.68794140625']" +215,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,324.806324110672,983,535,0,172.500,CW,533,61,32,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5514533107', '0.551453125']" +216,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,388,983,535,0,176.000,CW,533,121,64,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6329526917', '0.632953125']" +217,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,323,983,535,0,160.000,CW,533,81,43,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5383316667', '0.53833203125']" +218,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,344,983,535,0,155.000,CW,533,130,69,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5383395931', '0.53833984375']" +219,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,373.000000000002,983,535,0,157.000,CW,533,151,80,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6045397083', '0.6045390625']" +220,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,383,1085.6,595,0,168.5,CW,500,157,65,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.748046875', '0.748046875']" +221,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,315.749525616698,983,535,0,154.000,CW,533,56,29,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5369880952', '0.53698828125']" +222,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,347.067193675888,983,535,0,129.000,CW,533,68,36,None,"['Br64f', '3']",1,MONOCHROME2,"['0.48540979020979', 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go.Up,1,130,499.8,356.290985107424,983,535,0,169.000,CW,533,73,38,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5850426929', '0.58504296875']" +237,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,373,983,535,0,157.500,CW,533,65,34,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5061058345', '0.50610546875']" +238,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,356.999999999998,983,535,0,172.500,CW,533,114,60,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5767382876', '0.57673828125']" +239,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,321,983,535,0,177.500,CW,533,65,34,None,"['Br64f', '3']",1,MONOCHROME2,"['0.4938476923', '0.49384765625']" +240,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,340.722719141322,983,535,0,178.000,CW,533,214,114,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5864406196', '0.58644140625']" +243,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,356.096603393554,983,535,0,165.000,CW,533,119,63,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6557937385', '0.65579296875']" +244,CT,SIEMENS,SOMATOM 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go.Up,1,130,499.8,340.000000000002,983,535,0,166.500,CW,533,88,46,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5271333333', '0.5271328125']" +260,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,375,983,535,0,173.000,CW,533,101,53,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6097577236', '0.6097578125']" +261,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,375,983,535,0,158.500,CW,533,118,62,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6590509666', '0.65905078125']" +262,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,372.999999999998,983,535,0,167.000,CW,533,93,49,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5828125', '0.5828125']" +263,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,326.572972972974,983,535,0,143.500,CW,533,56,29,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5216837061', '0.52168359375']" +264,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,335,1085.6,595,0,149,CW,500,81,33,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.654296875', '0.654296875']" +265,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,353,1085.6,595,0,143,CW,500,163,67,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.689453125', '0.689453125']" +266,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,321.000000000002,983,535,0,177.500,CW,533,98,52,None,"['Br64f', '3']",1,MONOCHROME2,"['0.626953125', '0.626953125']" +267,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,363,1085.6,595,0,164,CW,500,233,97,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.708984375', '0.708984375']" +268,CT,SIEMENS,SOMATOM Definition Flash,2,,0,421,1085.6,595,0,150.5,CW,285,256,132,SN_DE,D33f,1,MONOCHROME2,"['0.822265625', '0.822265625']" +269,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,420.218867107602,983,535,0,143.000,CW,1000,60,60,None,"['Br64f', '3']",1,MONOCHROME2,"['0.649488408', '0.64948828125']" +270,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,364.999999999996,983,535,0,137.000,CW,533,68,36,None,"['Br64f', '3']",1,MONOCHROME2,"['0.53834808259587', '0.53834765625']" +271,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,297.344208809134,983,535,0,135.500,CW,533,102,54,None,"['Br64f', '3']",1,MONOCHROME2,"['0.525344523', '0.52534375']" +272,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,300,1085.6,595,0,127,CW,500,71,29,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.5859375', '0.5859375']" +274,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,378,983,535,0,145.000,CW,533,174,92,SN_DE,"['Br56f', '3']",1,MONOCHROME2,"['0.57534398782344', '0.57534375']" +275,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,331,1085.6,595,0,156,CW,500,219,91,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.646484375', '0.646484375']" +276,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,347.740614334472,983,535,0,126.500,CW,533,93,49,None,"['Br64f', '3']",1,MONOCHROME2,"['0.4686522911', '0.46865234375']" +277,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,323.999999999994,983,535,0,127.000,CW,533,57,30,None,"['Br64f', '3']",1,MONOCHROME2,"['0.4582729844', '0.4582734375']" +278,CT,SIEMENS,SOMATOM 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'2']",1,MONOCHROME2,"['0.66796875', '0.66796875']" +285,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,348.273567467652,983,535,0,132.000,CW,533,100,53,SN_DE,"['Br60f', '3']",1,MONOCHROME2,"['0.4331753731', '0.43317578125']" +286,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,336.957264957266,983,535,0,169.000,CW,533,83,44,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5839809359', '0.58398046875']" +287,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,361.999999999998,983,535,0,166.000,CW,533,93,49,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5246362319', '0.52463671875']" +288,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,334.875675675676,983,535,0,144.500,CW,533,77,41,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5073863636', '0.50738671875']" +289,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,341,1085.6,595,0,136.5,CW,500,102,42,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.666015625', '0.666015625']" +290,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,336,1085.6,595,0,156,CW,500,170,70,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.65625', '0.65625']" +291,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,363,1085.6,595,0,164,CW,500,214,89,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.5859375', '0.58548387096774']" +292,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,390,1085.6,595,0,152,CW,500,171,71,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.666015625', '0.66552901023891']" +293,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,349,1085.6,595,0,153,CW,500,334,139,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.681640625', '0.681640625']" +294,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,373,1085.6,595,0,169,CW,500,280,116,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.728515625', '0.728515625']" +295,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,387.806,983,535,0,166.500,CW,533,133,70,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6003204334', '0.6003203125']" +296,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,370.460017948488,983,535,0,189.000,CW,533,108,57,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6268358714', '0.6268359375']" +297,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,350,1085.6,595,0,196.5,CW,500,95,39,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.68359375', '0.68359375']" +298,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,407.883532324042,983,535,0,158.000,CW,1000,36,36,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6526128', '0.65261328125']" +299,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,377.447098976108,983,535,0,141.000,CW,533,80,42,None,"['Br40f', '3']",1,MONOCHROME2,"['0.737203125', '0.737203125']" +300,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,385.16657403647,983,535,0,132.500,CW,533,82,43,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5916528418', '0.59165234375']" +301,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,377.411596203072,983,535,0,145.500,CW,533,118,62,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6038592', '0.603859375']" +302,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,333.831501831502,983,535,0,132.500,CW,533,125,66,SN_DE,"['Br60f', '3']",1,MONOCHROME2,"['0.5877306338', '0.58773046875']" +303,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,379.586591757438,983,535,0,147.000,CW,533,134,71,SN_DE,"['Br60f', '3']",1,MONOCHROME2,"['0.5708090226', '0.57080859375']" +304,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,343.5415896488,983,535,0,159.000,CW,533,112,59,SN_DE,"['Br60f', '3']",1,MONOCHROME2,"['0.541862776', '0.54186328125']" +305,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,396,1085.6,595,0,179,CW,500,285,118,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.7734375', '0.7734375']" +306,CT,SIEMENS,SOMATOM go.Up,1,110,499.8,362,983,535,0,138.500,CW,533,160,85,SN_DE,"['Br60f', '3']",1,MONOCHROME2,"['0.48202396804261', '0.4820234375']" +307,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,384.114772374514,983,535,0,157.500,CW,533,102,54,None,"['Br64f', '3']",1,MONOCHROME2,"['0.6126251994', '0.612625']" +308,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,340,1085.6,595,0,141.5,CW,500,63,26,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.6640625', '0.6640625']" +309,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,376.910224530746,983,535,0,170.500,CW,533,116,61,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5973201268', '0.5973203125']" +310,CT,SIEMENS,SOMATOM Definition Flash,1,100,500,370,1085.6,595,0,181.5,CW,500,234,97,WEDGE_3,"['I50f', '2']",1,MONOCHROME2,"['0.72265625', '0.72265625']" +311,CT,SIEMENS,SOMATOM Definition Flash,1,120,500,360,1085.6,595,0,161,CW,500,62,25,WEDGE_3,B50f,1,MONOCHROME2,"['0.703125', '0.703125']" +312,CT,SIEMENS,SOMATOM go.Up,1,130,499.8,365.000000000004,983,535,0,136.000,CW,533,99,52,None,"['Br64f', '3']",1,MONOCHROME2,"['0.5274566474', '0.52745703125']" diff --git a/lndb/README.pdf b/lndb/README.pdf new file mode 100644 index 0000000000000000000000000000000000000000..f332b59da47b826282b1751693a74deed80c95fd --- /dev/null +++ b/lndb/README.pdf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5e1601a7775b1ed1aa3a8e355e03bf89568d1de101d0e80175a4b7ae927b63e4 +size 390599 diff --git a/lndb/calcFleischner.py b/lndb/calcFleischner.py new file mode 100644 index 0000000000000000000000000000000000000000..585213ffd1d979628ea2d5ddbc5919927b3ae0b8 --- /dev/null +++ b/lndb/calcFleischner.py @@ -0,0 +1,302 @@ +import numpy as np +import itertools +import math +from utils import readCsv +from readNoduleList import joinNodules + +def calcCTFleischnerProb(nd,nn,v0,v1,v2,t0,t1,t2,verb=False): + # Compute probability of belonging to each Fleischner class if given lists with: + # nd: the probability of each finding being a nodule + # nn: 1-nd + # v0-v2: the probability of each finding belonging to each volume class + # t0-t2: the probability of each finding belonging to each texture class + p0 = 0.0 + p1 = 0.0 + p2 = 0.0 + p3 = 0.0 + + vs = np.sum([v0,v1,v2],axis=0) + ts = np.sum([t0,t1,t2],axis=0) + v0=v0/vs + v1=v1/vs + v2=v2/vs + t0=t0/ts + t1=t1/ts + t2=t2/ts + + # No nodules + p0 += np.prod(nn) + if verb: + print('none',p0,p1,p2,p3) + + # Single nodule + for i in range(len(nd)): + p0 += np.prod(np.delete(nn,i))*nd[i]*v0[i] + p1 += np.prod(np.delete(nn,i))*nd[i]*((v1[i]+v2[i])*t0[i]+v1[i]*t2[i]) + p2 += np.prod(np.delete(nn,i))*nd[i]*((v1[i]+v2[i])*t1[i]) + p3 += np.prod(np.delete(nn,i))*nd[i]*v2[i]*t2[i] + if verb: + print('single',p0,p1,p2,p3) + + # Multiple nodules + if len(nd)>1: + combN = [] + indN = [i for i in range(len(nd))] + for i in range(2,len(nd)+1): + combN.extend(list(itertools.combinations(indN,i))) + combN = [list(c) for c in combN] + for cN in combN: + cNN = [i for i in indN if not i in cN] + # All Non Solid + pans = np.prod(nd[cN]*(t0[cN]+t1[cN]))*np.prod(nn[cNN]) + p3 += pans + if verb: + print('pans',p0,p1,p2,p3) + # All Solid + pas = np.prod(nd[cN]*t2[cN])*np.prod(nn[cNN]) + pasp0 = np.prod(nd[cN]*t2[cN]*v0[cN])*np.prod(nn[cNN]) + combV2 = [] + for i in range(1,len(cN)+1): + combV2.extend(list(itertools.combinations(cN,i))) + pasp3 = 0.0 + + combV2 = [list(c) for c in combV2] + for cV2 in combV2: + cV01 = [i for i in cN if not i in cV2] + pasp3 += np.prod(nd[cV2]*t2[cV2]*v2[cV2])*np.prod(nd[cV01]*t2[cV01]*(v0[cV01]+v1[cV01]))*np.prod(nn[cNN]) + p0 += pasp0 + p3 += pasp3 + p2 += pas-pasp3-pasp0 + if verb: + print('pas',p0,p1,p2,p3) + # Mixed + combT2 = [] + for i in range(1,len(cN)): + combT2.extend(list(itertools.combinations(cN,i))) + combT2 = [list(c) for c in combT2] + for cT2 in combT2: + cT01 = [i for i in cN if not i in cT2] + pcomb = np.prod(nn[cNN])*np.prod(nd[cN])*np.prod(t2[cT2])*np.prod(t0[cT01]+t1[cT01]) + pT2 = calcCTFleischnerProb_Mixed(v0[cT2],v1[cT2],v2[cT2],t0[cT2],t1[cT2],t2[cT2],'allsolid') + pT01 = calcCTFleischnerProb_Mixed(v0[cT01],v1[cT01],v2[cT01],t0[cT01],t1[cT01],t2[cT01],'allnonsolid') + p0 += pT2[0]*pT01[0]*pcomb + p1 += (pT2[1]*pT01[0]+pT2[0]*pT01[1]+pT2[1]*pT01[1])*pcomb + p2 += (pT2[2]*np.sum(pT01[:2])+np.sum(pT2[:2])*pT01[2]+pT2[2]*pT01[2])*pcomb + p3 += (pT2[3]*np.sum(pT01[:3])+np.sum(pT2[:3])*pT01[3]+pT2[3]*pT01[3])*pcomb + if verb: + print('mxd',p0,p1,p2,p3) + + if verb: + print('sum',p0+p1+p2+p3) + return [p0,p1,p2,p3] + +def calcCTFleischnerProb_Mixed(v0,v1,v2,t0,t1,t2,texstr,verb = False): + # Compute probability of belonging to each Fleischner class for mixed nodule lists (called by calcCTFleischnerProb): + p0 = 0.0 + p1 = 0.0 + p2 = 0.0 + p3 = 0.0 + + if texstr=='allsolid': + t0[:]=0 + t1[:]=0 + t2[:]=t2/t2 + t2[np.where(np.isnan(t2))] = 0 + else: + ts = t0+t1 + t0=t0/ts + t1=t1/ts + t0[np.where(np.isnan(t0))] = 0 + t1[np.where(np.isnan(t1))] = 0 + t2[:]=0 + + if len(v0)==1: # Single nodule + p0 += v0[0] + p1 += (v1[0]+v2[0])*t0[0]+v1[0]*t2[0] + p2 += (v1[0]+v2[0])*t1[0] + p3 += v2[0]*t2[0] + if verb: + print('single mixed',p0,p1,p2,p3) + + elif len(v0)>1: # Multiple nodules + # All Non Solid + pans = np.prod((t0+t1)) + p3 += pans + if verb: + print('pans mixed',p0,p1,p2,p3) + # All Solid + pas = np.prod(t2) + pasp0 = np.prod(t2*v0) + + combV2 = [] + indN = [i for i in range(len(v0))] + for i in range(1,len(v0)+1): + combV2.extend(list(itertools.combinations(indN,i))) + pasp3 = 0.0 + + combV2 = [list(c) for c in combV2] + for cV2 in combV2: + cV01 = [i for i in indN if not i in cV2] + pasp3 += np.prod(t2[cV2]*v2[cV2])*np.prod(t2[cV01]*(v0[cV01]+v1[cV01])) + p0 += pasp0 + p3 += pasp3 + p2 += pas-pasp3-pasp0 + if verb: + print('pas mixed',p0,p1,p2,p3) + + return [p0,p1,p2,p3] + +def calcCTFleischnerScore(nd,vclass,tclass,nodprob = 0.5): + # Compute Fleischner class if given lists with: + # nd: the probability of each finding being a nodule + # vclass: each finding's volume class (0,1,2) + # tclass: each finding's texture class (0,1,2) + # nodprob: threshold to use to divide nodules/nonnodules + vclass = vclass[nd>=nodprob] + tclass = tclass[nd>=nodprob] + nd = nd[nd>=nodprob] + + if len(nd)==0:# No nodules + f = 0 + elif len(nd)==1: # Single nodule + if vclass[0]==0: #small + f = 0 + elif tclass[0]==1: #partsolid + f = 2 + elif tclass[0]==0 or vclass[0]==1: #ggo/solid medium + f = 1 + else: + f = 3 #large + else: # Multiple nodules + if np.all(tclass<2): #all nonsolid + f = 2 + elif np.all(tclass==2): #all solid + if np.all(vclass==0): #small + f = 0 + elif np.any(vclass==2): #at least one big + f = 3 + else: #otherwise + f = 2 + else: #mixed nodules + fs = calcCTFleischnerScore(nd[tclass==2],vclass[tclass==2],tclass[tclass==2]) + fns = calcCTFleischnerScore(nd[tclass<2],vclass[tclass<2],tclass[tclass<2]) + f = max(fs,fns) + + return f + +def calcFleischner(nodules): + # Compute Fleischner class for a list of nodules from different CTs (trainNodules_gt.csv): + # nodules: list of nodules read from csv + header = nodules[0] + lines = nodules[1:] + + indlnd = header.index('LNDbID') + LND = np.asarray([line[indlnd] for line in lines]) + + if 'Volume0' in header and 'Text0' in header: + # if probabilities of volume and texture class are given compute Fleischner class probabilities + Nd = np.asarray([float(line[header.index('Nodule')]) for line in lines]) + Nn = 1-Nd + V0 = np.asarray([float(line[header.index('Volume0')]) for line in lines]) + V1 = np.asarray([float(line[header.index('Volume1')]) for line in lines]) + V2 = np.asarray([float(line[header.index('Volume2')]) for line in lines]) + T0 = np.asarray([float(line[header.index('Text0')]) for line in lines]) + T1 = np.asarray([float(line[header.index('Text1')]) for line in lines]) + T2 = np.asarray([float(line[header.index('Text2')]) for line in lines]) + elif 'Volume' in header and 'Text' in header: + # if volume and texture are given compute Fleischner class + Nd = np.asarray([float(line[header.index('Nodule')]) for line in lines]) + V = np.asarray([float(line[header.index('Volume')]) for line in lines]) + T = np.asarray([float(line[header.index('Text')]) for line in lines]) + elif 'VolumeClass' in header and 'TextClass' in header: + # if volume and texture class are given compute Fleischner class + Nd = np.asarray([float(line[header.index('Nodule')]) for line in lines]) + Vclass = np.asarray([float(line[header.index('VolumeClass')]) for line in lines]) + Tclass = np.asarray([float(line[header.index('TextClass')]) for line in lines]) + + p0 = 0; p1 = 0; p2 = 0; p3 = 0 + fleischner = [['LNDbID','Fleischner','Fleischner0','Fleischner1','Fleischner2','Fleischner3']] + for lndU in np.unique(LND): + if 'Volume0' in header and 'Text0' in header: + # if probabilities of volume and texture class are given compute Fleischner class probabilities + nd = Nd[LND==lndU] + nn = Nn[LND==lndU] + v0 = V0[LND==lndU] + v1 = V1[LND==lndU] + v2 = V2[LND==lndU] + t0 = T0[LND==lndU] + t1 = T1[LND==lndU] + t2 = T2[LND==lndU] + [p0,p1,p2,p3] = calcCTFleischnerProb(nd,nn,v0,v1,v2,t0,t1,t2,verb=False) + + vclass = np.ndarray.flatten(np.argmax([v0,v1,v2], axis=0)) + tclass = np.ndarray.flatten(np.argmax([t0,t1,t2], axis=0)) + elif 'Volume' in header and 'Text' in header: + # if volume and texture are given compute Fleischner class + nd = Nd[LND==lndU] + v = V[LND==lndU] + t = T[LND==lndU] + vclass = calcNodVolClass(v) + tclass = calcNodTexClass(t) + + elif 'VolumeClass' in header and 'TextClass' in header: + # if volume and texture class are given compute Fleischner class + nd = Nd[LND==lndU] + vclass = Vclass[LND==lndU] + tclass = Tclass[LND==lndU] + + f = calcCTFleischnerScore(nd,vclass,tclass,nodprob=.5) + + print('LNDb {}'.format(lndU)) + print('Fleischner class: {}'.format(f)) + print('Fleischner class probabilities: {} {} {} {}'.format(p0,p1,p2,p3)) + # return csv with Fleischner score for each CT + fleischner.append([lndU,f,p0,p1,p2,p3]) + return fleischner + +def calcNodVolClass(nodvol): + # Compute volume class from nodule volume nodvol + volthr = [100,250] + if isinstance(nodvol,float) or isinstance(nodvol,int): + if nodvol>=volthr[0] and nodvol=volthr[1]: + vclass = 2 + else: + vclass = 0 + else: #numpy array + vclass = np.zeros(nodvol.shape) + vclass[np.bitwise_and(nodvol>=volthr[0],nodvol=volthr[1]]=2 + return vclass + +def calcNodTexClass(nodtex): + # Compute texture class from texture rating nodtex + texthr = [7/3,11/3] + if isinstance(nodtex,float) or isinstance(nodtex,int): + if nodtex>=texthr[0] and nodtex<=texthr[1]: + vclass = 1 + elif nodtex>texthr[1]: + vclass = 2 + else: + vclass = 0 + else: #numpy array + vclass = np.zeros(nodtex.shape) + vclass[np.bitwise_and(nodtex>=texthr[0],nodtex=texthr[1]]=2 + return vclass + +if __name__ == "__main__": + # Compute Fleischner score for all trainset nodules + fname_gtNodulesFleischner = 'trainNodules.csv' + gtNodules = readCsv(fname_gtNodulesFleischner) + gtNodules = joinNodules(gtNodules) + pdFleischner = calcFleischner(gtNodules) + + # Compute Fleischner score for all predicted nodules (given volume and texture rating/class/probabilities) + fname_pdNodulesFleischner = 'predictedNodules.csv' + pdNodules = readCsv('input/'+fname_pdNodulesFleischner) + pdFleischner = calcFleischner(pdNodules) + + + \ No newline at end of file diff --git a/lndb/chars_trainNodules.csv b/lndb/chars_trainNodules.csv new file mode 100644 index 0000000000000000000000000000000000000000..9b7cc757d5154b06d25eba2168247925125d4f0e --- /dev/null +++ b/lndb/chars_trainNodules.csv @@ -0,0 +1,1528 @@ +LNDbID,RadID,FindingID,calcification,internalStructure,lobulation,malignancy,margin,sphericity,spiculation,subtlety +1.0,1.0,1.0,6.0,1.0,1.0,2.0,4.0,2.0,2.0,5.0 +1.0,1.0,2.0,6.0,1.0,1.0,2.0,4.0,2.0,1.0,3.0 +1.0,2.0,1.0,3.0,1.0,1.0,2.0,2.0,2.0,2.0,2.0 +1.0,3.0,1.0,5.0,1.0,2.0,2.0,3.0,4.0,3.0,4.0 +2.0,1.0,1.0,6.0,1.0,1.0,1.0,5.0,3.0,1.0,5.0 +2.0,1.0,2.0,5.0,1.0,1.0,1.0,5.0,5.0,1.0,5.0 +2.0,1.0,3.0,6.0,1.0,1.0,3.0,5.0,5.0,1.0,3.0 +2.0,1.0,4.0,6.0,1.0,1.0,2.0,4.0,5.0,1.0,3.0 +2.0,1.0,5.0,6.0,1.0,1.0,2.0,3.0,3.0,1.0,4.0 +2.0,2.0,1.0,3.0,1.0,1.0,1.0,5.0,3.0,1.0,5.0 +2.0,2.0,2.0,3.0,1.0,1.0,1.0,2.0,4.0,1.0,3.0 +2.0,3.0,1.0,4.0,1.0,2.0,2.0,3.0,2.0,2.0,4.0 +2.0,3.0,2.0,3.0,1.0,2.0,1.0,5.0,4.0,1.0,5.0 +2.0,3.0,3.0,3.0,1.0,1.0,1.0,5.0,3.0,1.0,5.0 +2.0,3.0,4.0,3.0,1.0,2.0,1.0,4.0,2.0,1.0,4.0 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