I'm interested in extraction of transformation matrix from image coordinate to patient coordinate from DICOM header of a RTDOSE matrix.
I just have a RTDOSE as a single DICOM file.
When I get the imageorigin patient it seems that the origin for just the first slice is given.
How can I get the origin for the last slice?
(or maybe its better to said: I mean how can I extract this .dcm file to its separate slices?)
Any help will appreciated.
Zahra
Grid Frame Offset Vector (3004,000c) defines the offset (in mm) for each dose slice. Combining the Image Position (Patient) (0020,0032), and the offset for the last slice you can calculate the position of the last slice. Direction of the offset is perpendicular to the plane on which the dose has been defined.
More details in chapter C.8.8.3.2 in Part 3 of the DICOM standard.
http://medical.nema.org/medical/dicom/2014a/output/pdf/part03.pdf
Related
I would like to calculate the Horizontal and Vertical field of view from the camera intrinsic matrix for the cameras used in the KITTI dataset. The reason I need the Field of view is to convert a depth map into 3D point clouds.
Though this question has been asked quite a long time ago, I felt it needed an answer as I ran into the same issue and was unable to find any info on it.
I have however solved it using the information available in this document and some more general camera calibration documents
Firstly, we need to convert the supplied disparity into distance. This can be done through fist converting the disp map into floats through the method in the dev_kit where they state:
disp(u,v) = ((float)I(u,v))/256.0;
This disparity can then be converted into a distance through the default stereo vision equation:
Depth = Baseline * focal length/ Disparity
Now come some tricky parts. I searched high and low for the focal length and was unable to find it in documentation.
I realised just now when writing that the baseline is documented in the aforementioned source however from section IV.B we can see that it can be found in P(i)rect indirectly.
The P_rects can be found in the calibration files and will be used for both calculating the baseline and the translation from uv in the image to xyz in the real world.
The steps are as follows:
For pixel in depthmap:
xyz_normalised = P_rect \ [u,v,1]
where u and v are the x and y coordinates of the pixel respectively
which will give you a xyz_normalised of shape [x,y,z,0] with z = 1
You can then multiply it with the depth that is given at that pixel to result in a xyz coordinate.
For completeness, as P_rect is the depth map here, you need to use P_3 from the cam_cam calibration txt files to get the baseline (as it contains the baseline between the colour cameras) and the P_2 belongs to the left camera which is used as a reference for occ_0 files.
I need to get relative lateral coordinates (distance to the vehicle from one side of the lane i.e Px) of vehicles.
I know that SUMO provides absolute x,y coordinates and distance traveled (Py).
Is there a way to get Px information at each timestep directly like Py?
This information is part of the raw dump (or netstate dump, see https://sumo.dlr.de/wiki/Simulation/Output/RawDump) but only if the sublane model is active. It is given as an absolute deviation from the center line of the line (which is always 0 if the sublane model is not active).
I have a raster image with multiple polyline feature classes over it. The lines are not overlapping but they are in multiple different orientations. For every pixel in the raster, I want to calculate the length of the line through that pixel so that the result would be a raster with cells assigned a float value of zero to 2^0.5 times the cell size. What's the best way to do this? I'm using ArcPro with an advanced license.
You can have a look at the answers to a similar question here (using R --- but you have a license for that too)
https://gis.stackexchange.com/questions/119993/convert-line-shapefile-to-raster-value-total-length-of-lines-within-cell/120175
I have a large dicom mri dataset for several patients. For each patient, there is a folder including many 2d slices of .dcm files and the data of each patient has different sizes. For example:
patient1: PixelSpacing=0.8mm,0.8mm, SliceThickness=2mm, SpacingBetweenSlices=1mm, 400x400 pixels
patient2: PixelSpacing=0.625mm,0.625mm, SliceThickness=2.4mm, SpacingBetweenSlices=1mm, 512x512 pixels
So my question is how can I convert all of them into {Pixel Spacing} = 1mm,1mm and {Slice Thickness = 1mm}?
Thanks.
These are two different questions:
About harmonizing positions and pixel spacing, these links will be helpful:
Finding the coordinates (mm) of identical slice locations for two MR datasets acquired in the same scanning session
Interpolation between two images with different pixelsize
http://nipy.org/nibabel/dicom/dicom_orientation.html
Basically, you want to build your target volume and interpolate each of its pixels from the nearest neighbors in the source volumes.
About modifying the slice thickness: If you really want to modify the slice thickness rather than the slice distance, I do not see any chance to do this correctly with the source data you have. This is because the thickness says which width of the raw data was used to calculate the values for a slice in your stack (e.g. by averaging or calculating an integral). With a slice thickness of 2 or 2.4mm in the source volumes, you will not be able to reconstruct the gray values with a thickness of 1 mm. If your question was referring to slice distance rather than slice thickness, answer 1 applies.
I am working on rate control algorithms in HEVC. I have a problem. Can any one help me with how can I find each frame of an input video in HEVC? (Because I need to work on each frame as a distinct image but I don't know in what variable in HEVC each input frame is stored an processed.)
To find new frame
Parse the input data as per HEVC draft (annex B) to find start of frame (start_code_prefix_one_3bytes ). This will give you new NAL units.
If you find VCL-NAL parse slice header and find value of first_slice_segment_in_pic_flag equal to 1 specifies that the slice segment is the first slice segment of the picture in decoding order.
Do same process until you will get next vcl nal containing first_slice_segment_in_pic_flag equal to 1. So this will indicate you this is the start of new or next frame.