# README #
## Overview
A viewer to scroll through slices of 2D, 3D and 4D medical data sets
(CT, PET, MRI...)
Supports files than can be read by SimpleITK:
* Nifti: .nii .nii.gz .nia .img .img.gz .hdr
* Nrrd: .nrrd .nhdr
* Meta Image: .mhd .mha
And probably some more types as long as they are supported by the SimpleITK
file reader.
In addition there is support for reading folders with dicom data.
Sorting dicom data into 3D volume is tricky and may depend on modality, vendor
and model of the imaging device. Basic support is offered that works well with
CT, PET and MRI. For Siemens PET the PET data is read in SUV.
A second image can be loaded and is displayed as fusion on top of the first.
Works well with PET/CT and PET/MRI data.
##Usage
pip install simple-slice-viewer
### Command Line
simple-slice-viewer
simple-slice-viewer ct.nii
simple-slice-viewer ct.nii --fusion pet.nii
or use ssv as shorthand:
ssv
ssv ct.nii
ssv ct.nii --fusion pet.nii
ssv --image ct.nii --fusion pet.nii
### Inside Python
In Python images should be read to SimpleITK Image objects first.
import simple_slice_viewer as ssv
import SimpleITK as sikt
image = sitk.ReadImage('ct.nii')
fusion = sitk.ReadImage('pet.nii')
ssv.display(image=image, fusion=fusion)
To display a numpy array convert it to SimpleITK first
import SimpleITK as sitk
import simple_slice_viewer as ssv
image = sitk.GetImageFromArray(np_array)
ssv.display(image)
Raw data
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"description": "# README #\r\n\r\n## Overview\r\n\r\nA viewer to scroll through slices of 2D, 3D and 4D medical data sets \r\n(CT, PET, MRI...)\r\n\r\nSupports files than can be read by SimpleITK:\r\n\r\n* Nifti: .nii .nii.gz .nia .img .img.gz .hdr\r\n* Nrrd: .nrrd .nhdr\r\n* Meta Image: .mhd .mha \r\n\r\nAnd probably some more types as long as they are supported by the SimpleITK\r\nfile reader.\r\n\r\nIn addition there is support for reading folders with dicom data. \r\nSorting dicom data into 3D volume is tricky and may depend on modality, vendor\r\nand model of the imaging device. Basic support is offered that works well with\r\nCT, PET and MRI. For Siemens PET the PET data is read in SUV.\r\n\r\nA second image can be loaded and is displayed as fusion on top of the first.\r\nWorks well with PET/CT and PET/MRI data.\r\n\r\n\r\n\r\n##Usage\r\n\r\npip install simple-slice-viewer\r\n\r\n### Command Line\r\n simple-slice-viewer\r\n simple-slice-viewer ct.nii\r\n simple-slice-viewer ct.nii --fusion pet.nii\r\n \r\n\r\nor use ssv as shorthand:\r\n ssv\r\n ssv ct.nii\r\n ssv ct.nii --fusion pet.nii\r\n ssv --image ct.nii --fusion pet.nii\r\n\r\n### Inside Python\r\n\r\nIn Python images should be read to SimpleITK Image objects first.\r\n\r\n import simple_slice_viewer as ssv\r\n import SimpleITK as sikt\r\n\r\n image = sitk.ReadImage('ct.nii')\r\n fusion = sitk.ReadImage('pet.nii')\r\n\r\n ssv.display(image=image, fusion=fusion)\r\n \r\n\r\nTo display a numpy array convert it to SimpleITK first\r\n\r\n import SimpleITK as sitk\r\n import simple_slice_viewer as ssv\r\n image = sitk.GetImageFromArray(np_array)\r\n ssv.display(image)\r\n\r\n\r\n\r\n",
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