[Gate-users] Using Medcon to convert NCAT to uint16
Siti Salasiah MusNMey
ctsalasiah1950 at gmail.com
Fri Jan 25 07:05:48 CET 2013
Hi & Good day,
This is my first time using Vgate. I would like to convert NCAT phantom to
uint16 using Medcon. Is my definition right below? The image should be
64x64x64(slices). Why does the generated image is 64x64x2 (each slice).
Thank you so much.
-----------------------------------------------------------------------------------------------------------------------------
gate at vgate:~/Simulation$ medcon -f cuba1_act_av.bin -c intf -i
(process:3511): (X)MedCon-WARNING **: Enabling negative pixels & disabling
quantification
-------------------------------------------------------------------------------
INTERACTIVE PROCEDURE
-------------------------------------------------------------------------------
Filename: cuba1_act_av.bin
Number of images [1]? 64
General header offset to binary data [0 bytes]?
Image header offset to binary data [0 bytes]?
Image header repeated before each image [No]?
Swap the pixel bytes [No]?
Same characteristics for all images [Yes]?
ALL IMAGES
----------
Absolute offset in bytes [0]?
Image columns [0]? 64
Image rows [0]? 64
Pixel data type:
1 -> bit
2 -> Int8 3 -> Uint8
4 -> Int16 5 -> Uint16
6 -> Int32 7 -> Uint32
10 -> float 11 -> double
12 -> ascii
20 -> RGB
Your choice [4]? 5
-------------------------------------------------------------------------------
SUMMARY OF IMAGE LAYOUT
-------------------------------------------------------------------------------
#------------------#
! Image #1 ! (64x64x2)
! Image #2 ! (64x64x2)
! Image #3 ! (64x64x2)
! Image #4 ! (64x64x2)
! Image #5 ! (64x64x2)
! Image #6 ! (64x64x2)
! Image #7 ! (64x64x2)
! Image #8 ! (64x64x2)
! Image #9 ! (64x64x2)
! Image #10 ! (64x64x2)
! Image #11 ! (64x64x2)
! Image #12 ! (64x64x2)
! Image #13 ! (64x64x2)
! Image #14 ! (64x64x2)
! Image #15 ! (64x64x2)
! Image #16 ! (64x64x2)
! Image #17 ! (64x64x2)
! Image #18 ! (64x64x2)
! Image #19 ! (64x64x2)
! Image #20 ! (64x64x2)
! Image #21 ! (64x64x2)
! Image #22 ! (64x64x2)
! Image #23 ! (64x64x2)
! Image #24 ! (64x64x2)
! Image #25 ! (64x64x2)
! Image #26 ! (64x64x2)
! Image #27 ! (64x64x2)
! Image #28 ! (64x64x2)
! Image #29 ! (64x64x2)
! Image #30 ! (64x64x2)
! Image #31 ! (64x64x2)
! Image #32 ! (64x64x2)
! Image #33 ! (64x64x2)
! Image #34 ! (64x64x2)
! Image #35 ! (64x64x2)
! Image #36 ! (64x64x2)
! Image #37 ! (64x64x2)
! Image #38 ! (64x64x2)
! Image #39 ! (64x64x2)
! Image #40 ! (64x64x2)
! Image #41 ! (64x64x2)
! Image #42 ! (64x64x2)
! Image #43 ! (64x64x2)
! Image #44 ! (64x64x2)
! Image #45 ! (64x64x2)
! Image #46 ! (64x64x2)
! Image #47 ! (64x64x2)
! Image #48 ! (64x64x2)
! Image #49 ! (64x64x2)
! Image #50 ! (64x64x2)
! Image #51 ! (64x64x2)
! Image #52 ! (64x64x2)
! Image #53 ! (64x64x2)
! Image #54 ! (64x64x2)
! Image #55 ! (64x64x2)
! Image #56 ! (64x64x2)
! Image #57 ! (64x64x2)
! Image #58 ! (64x64x2)
! Image #59 ! (64x64x2)
! Image #60 ! (64x64x2)
! Image #61 ! (64x64x2)
! Image #62 ! (64x64x2)
! Image #63 ! (64x64x2)
! Image #64 ! (64x64x2)
#------------------#
Redo input [no]?
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