def loaddata(dicomdata):
indata = pydicom_series.read_files(dicomdata,showProgress=True)[0]
pixelsize = float(indata.info["0028","0030"].value[0])
rows = indata.info["0028","0010"].value
cols = indata.info["0028","0011"].value
newshape = (rows,cols)
print "shape of dataslices: ", newshape
bitdepth = indata.info["0028","0100"].value #bits allocated
if bitdepth == 16:
bv = np.int16
elif bitdepth == 8:
bv = np.int8
elif bitdepth == 32:
bv = np.int32
elif bitdepth == 64:
bv = np.int64
datlist = []
sequence = indata.__dict__['_datasets']
for i in range(len(sequence)):
tmpkeys = sequence[i].keys()
datlist.append(np.reshape(np.fromstring(sequence[i][dicom.tag.Tag("7fe0","0010")].value,dtype=bv),newshape))
array = np.array(datlist)
print "loaddata complete"
return pixelsize, array, indata
def dataSlicing(dataPath, masks=None):
#Gui init
startTime = time.time()
global app, win, imv1, imv2, imv3, hLine1, hLine2, hLine3, vLine1, vLine2, vLine3
app = QtGui.QApplication([])
win = QtGui.QMainWindow()
win.setWindowTitle('DataSlicing')
win.resize(600,800)
cw = QtGui.QWidget()
win.setCentralWidget(cw)
l = QtGui.QGridLayout()
cw.setLayout(l)
imv1 = pg.ImageView()
imv2 = pg.ImageView()
imv3 = pg.ImageView()
l.addWidget(imv1, 0, 0)
l.addWidget(imv2, 1, 0)
l.addWidget(imv3, 2, 0)
win.show()
#Get 3D data
vol = diSeries.read_files(dataPath)
data = vol[0].get_pixel_array()
img1RGBA = np.zeros((data.shape[0],data.shape[1],4),dtype=np.ubyte)
img2RGBA = np.zeros((data.shape[0],data.shape[2],4),dtype=np.ubyte)
img3RGBA = np.zeros((data.shape[1],data.shape[2],4),dtype=np.ubyte)
#input mask is a np array with numbered regions, 0 specifies no colour
if masks is not None:
alpha = int(255/float(len(masks)))
#every mask in the list gets its own lookup table to avoid problems
#with reset numbering of regions in different masks and
# different number of regions in each of the masks
masksCol = []
for j in range(len(masks)):
if data.shape != masks[j].shape:
raise Exception('The dimensions of the mask%d and data do not match.',j)
#command np.unique(someArray) returns list of unique values in array
colCount = len(np.unique(masks[j]))
lookupTable = np.zeros((colCount,4),dtype=np.ubyte)
lookupTable[0] = [0,0,0,0]
for i in range(1,colCount):
lookupTable[i]=np.random.randint(1,256,size=3).tolist()+[alpha]
masksCol.append(pg.applyLookupTable(masks[j],lookupTable))
maskBack = masksCol.pop(0)
mask = np.zeros(maskBack.shape,dtype=np.ubyte)
for m in masksCol:
mask[:,:,:,3]=((m[:,:,:,3].astype(float)/255)+(maskBack[:,:,:,3].astype(float)/255)*(1-(m[:,:,:,3].astype(float)/255)))*255
#when the alpha is zero, RGBs should be zero too
#dividing by large number in float will produce int zero values
mask[mask==0]=1000
mask[:,:,:,0]=(m[:,:,:,0]*(m[:,:,:,3].astype(float)/255)+maskBack[:,:,:,0]*(maskBack[:,:,:,3].astype(float)/255)*(1-(m[:,:,:,3].astype(float)/255)))/(mask[:,:,:,3].astype(float)/255)
mask[:,:,:,1]=(m[:,:,:,1]*(m[:,:,:,3].astype(float)/255)+maskBack[:,:,:,1]*(maskBack[:,:,:,3].astype(float)/255)*(1-(m[:,:,:,3].astype(float)/255)))/(mask[:,:,:,3].astype(float)/255)
mask[:,:,:,2]=(m[:,:,:,2]*(m[:,:,:,3].astype(float)/255)+maskBack[:,:,:,2]*(maskBack[:,:,:,3].astype(float)/255)*(1-(m[:,:,:,3].astype(float)/255)))/(mask[:,:,:,3].astype(float)/255)
maskBack = mask
maskBack[maskBack==0]=255
maskCol = maskBack
else:
maskCol = None
#creates crosshairs, positioned in the middle of the picture, limited by
#dimensions of the picture
hLine1 = pg.InfiniteLine(angle=0, movable=True, pos=img1RGBA.shape[1]/2, bounds=[0,img1RGBA.shape[1]-1])
vLine1 = pg.InfiniteLine(angle=90, movable=True, pos=img1RGBA.shape[0]/2, bounds=[0,img1RGBA.shape[0]-1])
hLine2 = pg.InfiniteLine(angle=0, movable=True, pos=img2RGBA.shape[1]/2, bounds=[0,img2RGBA.shape[1]-1])
vLine2 = pg.InfiniteLine(angle=90, movable=True, pos=img2RGBA.shape[0]/2, bounds=[0,img2RGBA.shape[0]-1])
hLine3 = pg.InfiniteLine(angle=0, movable=True, pos=img3RGBA.shape[1]/2, bounds=[0,img3RGBA.shape[1]-1])
vLine3 = pg.InfiniteLine(angle=90, movable=True, pos=img3RGBA.shape[0]/2, bounds=[0,img3RGBA.shape[0]-1])
imv1.addItem(vLine1)
imv1.addItem(hLine1)
imv2.addItem(vLine2)
imv2.addItem(hLine2)
imv3.addItem(vLine3)
imv3.addItem(hLine3)
#{v,h}Line{1,2,3}.value() gives only one value, since the angle of lines is
#zero or right
#left upper corner of the picture is [0,0] coordinate
def updateV1():
#updates image views that get affected by dragging in imv1 in vertical dimension
global imv3, img3, img3RGBA, vLine1, vLine2
vLine2.setValue(vLine1.value())
img3 = data[vLine1.value(),:,:]
img3RGBA = pg.makeRGBA(img3,levels=[np.amin(img3),np.amax(img3)])[0]
if maskCol is not None:
maskSlice = maskCol[vLine1.value(),:,:,:]
img3RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img3RGBA[:,:,0:3]
img3RGBA[:,:,3] = 255
imv3.setImage(img3RGBA.astype(int))
def updateH1():
#updates image views that get affected by dragging in imv1 in horizontal
#dimension
global img2, img2RGBA, imv2, hLine1, vLine3
vLine3.setValue(hLine1.value())
img2 = data[:,hLine1.value(),:]
img2RGBA = pg.makeRGBA(img2,levels=[np.amin(img2),np.amax(img2)])[0]
if maskCol is not None:
maskSlice = maskCol[:,hLine1.value(),:,:]
img2RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img2RGBA[:,:,0:3]
img2RGBA[:,:,3] = 255
imv2.setImage(img2RGBA.astype(int))
vLine1.sigDragged.connect(updateV1)
hLine1.sigDragged.connect(updateH1)
def updateV2():
global imv3, img3, img3RGBA, vLine2, vLine1
vLine1.setValue(vLine2.value())
img3 = data[vLine2.value(),:,:]
img3RGBA = pg.makeRGBA(img3,levels=[np.amin(img3),np.amax(img3)])[0]
if maskCol is not None:
maskSlice = maskCol[vLine2.value(),:,:,:]
img3RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img3RGBA[:,:,0:3]
img3RGBA[:,:,3] = 255;
imv3.setImage(img3RGBA.astype(int))
def updateH2():
global imv1, img1, img1RGBA, hLine2, hLine3
hLine3.setValue(hLine2.value())
img1 = data[:,:,hLine2.value()]
img1RGBA = pg.makeRGBA(img1,levels=[np.amin(img1),np.amax(img1)])[0]
if maskCol is not None:
maskSlice = maskCol[:,:,hLine2.value(),:]
img1RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img1RGBA[:,:,0:3]
img1RGBA[:,:,3] = 255
imv1.setImage(img1RGBA.astype(int))
vLine2.sigDragged.connect(updateV2)
hLine2.sigDragged.connect(updateH2)
def updateV3():
global imv2, img2, img2RGBA, vLine3, hLine1
hLine1.setValue(vLine3.value())
img2 = data[:,vLine3.value(),:]
img2RGBA = pg.makeRGBA(img2,levels=[np.amin(img2),np.amax(img2)])[0]
if maskCol is not None:
maskSlice = maskCol[:,vLine3.value(),:,:]
img2RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img2RGBA[:,:,0:3]
img2RGBA[:,:,3] = 255
imv2.setImage(img2RGBA.astype(int))
def updateH3():
global imv1, img1, img1RGBA, hLine3, hLine2
hLine2.setValue(hLine3.value())
img1 = data[:,:,hLine3.value()]
img1RGBA = pg.makeRGBA(img1,levels=[np.amin(img1),np.amax(img1)])[0]
if maskCol is not None:
maskSlice = maskCol[:,:,hLine3.value(),:]
img1RGBA[:,:,0:3] = maskSlice[:,:,0:3].astype(float)/255*img1RGBA[:,:,0:3]
img1RGBA[:,:,3]
imv1.setImage(img1RGBA.astype(int))
vLine3.sigDragged.connect(updateV3)
hLine3.sigDragged.connect(updateH3)
#sets initial images, when script starts
updateV1()
updateH1()
updateH2()
endTime = time.time()
elapsed = endTime - startTime
print "time elapsed: ", elapsed
def prepareInput(instancedict,headers_only,logTag="[prepareInput] "):
"""
Reads inputfile as an EnhancedDICOM object; if an EnhancedDICOM object is detected, prepareEnhancedInput is called.
Checks if the input is as expected: number of slices etc.
If not headers_only, scaling the pixel values according to RescaleIntercept and RescaleIntercept of each frame
and transposing for pyqtgraph format.
Raises ValueError if file cannot be opened as a DICOM object
Returns raw dcmfile, scaled and transposed pixeldata (or None), type of DICOM object.
"""
# compile a list of valid files to read
instancedict = removeBogusDICOMfiles(instancedict)
dcmInfile = None
pixeldataIn = None
# Repair Mapping for MR; not correct for all scanner
keymapping = [
("0040,9096,0040,9224","0028,1052"), # Real World Value Intercept -> Rescale Intercept
("0040,9096,0040,9225","0028,1053"), # Real World Value Slope -> Rescale Slope
]
# Check if input data is as expected: MR needs 3D data
if len(instancedict) == 1:
ModeEnhanced = False
ModeEnhanced = testIfEnhancedDICOM(instancedict[0])
if ModeEnhanced:
return prepareEnhancedInput(instancedict[0],headers_only=headers_only) # scaled and transposed
if dcmInfile is None:
filename = instancedict[0]
dcmInfile = _readSingleImage(filename,headers_only=headers_only)
if dcmInfile is None:
# Not a dicom file
raise ValueError("{} ERROR! {} is not a valid non-Enhanced DICOM object".format(logTag, filename))
modality = dcmInfile.Modality
if not headers_only:
# need scaling for single slice, already done for series in pydicom_series, but not for some MR files
if modality == 'CT' or modality == 'MR':
if not "RescaleIntercept" in dcmInfile: # in wrong place define for some MR files
dcmInfile.RescaleIntercept = readDICOMtag(keymapping[0][0],dcmInfile,0)
dcmInfile.RescaleSlope = readDICOMtag(keymapping[1][0],dcmInfile,0)
pixeldataIn = np.int16(np.transpose(dcmInfile.pixel_array.astype(int),(1,0)))
slope = dcmInfile.RescaleSlope
intercept = dcmInfile.RescaleIntercept
pixeldataIn = intercept + slope*pixeldataIn
elif modality == 'MG' and getDICOMMode(dcmInfile) == stModeBTO:
print '!WARNING! MG BTO dataset! DICOM info is NOT properly adjusted, no scaling applied yet!'
pixeldataIn = np.transpose(dcmInfile.pixel_array,(0,2,1))
elif modality == 'MG' or modality == 'CR':
pixeldataIn = dcmInfile.pixel_array.transpose()
elif modality == 'RF': # fixme! 2D and 3D
pixeldataIn = dcmInfile.pixel_array.transpose()
elif modality == 'US':
rgbmode = (dcmInfile.SamplesPerPixel == 3)
if not rgbmode:
if len(np.shape(dcmInfile.pixel_array)) == 2:
pixeldataIn = dcmInfile.pixel_array.transpose()
elif len(np.shape(dcmInfile.pixel_array)):
pixeldataIn = np.transpose(dcmInfile.pixel_array,(0,2,1))
pixeldataIn = pixeldataIn[0]
else:
# AS: this fix is needed in pydicom < 1.0; maybe solved in later versions?
try:
nofframes = dcmInfile.NumberOfFrames
except AttributeError:
nofframes = 1
if dcmInfile.PlanarConfiguration==0:
pixel_array = dcmInfile.pixel_array.reshape(nofframes, dcmInfile.Rows, dcmInfile.Columns, dcmInfile.SamplesPerPixel)
else:
pixel_array = dcmInfile.pixel_array.reshape(dcmInfile.SamplesPerPixel, nofframes, dcmInfile.Rows, dcmInfile.Columns)
if len(np.shape(pixel_array)) == 3: #2d rgb
pixeldataIn = pixel_array[:,:,0].transpose()
pixeldataInR = (pixel_array[:,:,0]).transpose()
pixeldataInG = (pixel_array[:,:,1]).transpose()
pixeldataInB = (pixel_array[:,:,2]).transpose()
elif len(np.shape(pixel_array)) == 4: #3d rgb
pixeldataIn = (pixel_array[-1,:,:,0]).transpose()
pixeldataInR = (pixel_array[-1,:,:,0]).transpose()
pixeldataInG = (pixel_array[-1,:,:,1]).transpose()
pixeldataInB = (pixel_array[-1,:,:,2]).transpose()
# remove rgb info
for y in range(dcmInfile.Rows):
for x in range(dcmInfile.Columns):
r = pixeldataInR[x,y]
g = pixeldataInG[x,y]
b = pixeldataInB[x,y]
ma = max(r,g,b)
mi = min(r,g,b)
if ma != mi:
pixeldataIn[x,y] = 0
else:
path = os.path.dirname(instancedict[0])
for ip in instancedict:
if os.path.dirname(ip) != path:
raise ValueError("{} ERROR! multiple would-be dicom files scattered over multiple dirs!".format(logTag))
try:
dcmInfile = dcmseries.read_files(path, True, readPixelData=False)[0]
if not headers_only: # NOTE: Rescaling is already done pydicom_series, but maybe not for stupid MR
pixeldataIn = np.transpose(dcmInfile.get_pixel_array(),(0,2,1))
except:
raise ValueError("{} ERROR! {} is not a valid non-Enhanced DICOM series".format(logTag, path))
return dcmInfile,pixeldataIn,getDICOMMode(dcmInfile)
def prepareInput(instancedict,headers_only,logTag="[prepareInput] "):
"""
Reads inputfile as an EnhancedDICOM object; if an EnhancedDICOM object is detected, prepareEnhancedInput is called.
Checks if the input is as expected: number of slices etc.
If not headers_only, scaling the pixel values according to RescaleIntercept and RescaleIntercept of each frame
and transposing for pyqtgraph format.
Raises ValueError if file cannot be opened as a DICOM object
Returns raw dcmfile, scaled and transposed pixeldata (or None), type of DICOM object.
"""
# compile a list of valid files to read
instancedict = removeBogusDICOMfiles(instancedict)
dcmInfile = None
pixeldataIn = None
# Repair Mapping for MR; not correct for all scanner
keymapping = [
("0040,9096,0040,9224","0028,1052"), # Real World Value Intercept -> Rescale Intercept
("0040,9096,0040,9225","0028,1053"), # Real World Value Slope -> Rescale Slope
]
# Check if input data is as expected: MR needs 3D data
if len(instancedict) == 1:
ModeEnhanced = False
ModeEnhanced = testIfEnhancedDICOM(instancedict[0])
if ModeEnhanced:
return prepareEnhancedInput(instancedict[0],headers_only=headers_only) # scaled and transposed
if dcmInfile is None:
filename = instancedict[0]
dcmInfile = _readSingleImage(filename,headers_only=headers_only)
if dcmInfile is None:
# Not a dicom file
raise ValueError("{} ERROR! {} is not a valid non-Enhanced DICOM object".format(logTag, filename))
modality = dcmInfile.Modality
if not headers_only:
# need scaling for single slice, already done for series in pydicom_series, but not for some MR files
if modality == 'CT' or modality == 'MR':
if not "RescaleIntercept" in dcmInfile: # in wrong place define for some MR files
dcmInfile.RescaleIntercept = readDICOMtag(keymapping[0][0],dcmInfile,0)
dcmInfile.RescaleSlope = readDICOMtag(keymapping[1][0],dcmInfile,0)
pixeldataIn = np.int16(np.transpose(dcmInfile.pixel_array.astype(int),(1,0)))
slope = dcmInfile.RescaleSlope
intercept = dcmInfile.RescaleIntercept
pixeldataIn = intercept + slope*pixeldataIn
elif modality == 'MG' and getDICOMMode(dcmInfile) == stModeBTO:
print('!WARNING! MG BTO dataset! DICOM info is NOT properly adjusted, no scaling applied yet!')
pixeldataIn = np.transpose(dcmInfile.pixel_array,(0,2,1))
elif modality == 'MG' or modality == 'CR' or modality == 'DX':
pixeldataIn = dcmInfile.pixel_array.transpose()
elif modality == 'RF': # fixme! 2D and 3D
pixeldataIn = dcmInfile.pixel_array.transpose()
elif modality == 'US':
rgbmode = (dcmInfile.SamplesPerPixel == 3)
if not rgbmode:
if len(np.shape(dcmInfile.pixel_array)) == 2:
pixeldataIn = dcmInfile.pixel_array.transpose()
elif len(np.shape(dcmInfile.pixel_array)):
pixeldataIn = np.transpose(dcmInfile.pixel_array,(0,2,1))
pixeldataIn = pixeldataIn[0]
else:
# AS: this fix is needed in pydicom < 1.0; maybe solved in later versions?
try:
nofframes = dcmInfile.NumberOfFrames
except AttributeError:
nofframes = 1
if dcmInfile.PlanarConfiguration==0:
pixel_array = dcmInfile.pixel_array.reshape(nofframes, dcmInfile.Rows, dcmInfile.Columns, dcmInfile.SamplesPerPixel)
else:
pixel_array = dcmInfile.pixel_array.reshape(dcmInfile.SamplesPerPixel, nofframes, dcmInfile.Rows, dcmInfile.Columns)
# force using only the RED channel in RGB.
if US_RGB_USE_RED == True:
if len(np.shape(pixel_array)) == 3: #2d rgb
pixeldataIn = pixel_array[:,:,0].transpose()
elif len(np.shape(pixel_array)) == 4: #3d rgb
pixeldataIn = (pixel_array[-1,:,:,0]).transpose()
else:
# remove all data where there is a difference between R,G,B
if len(np.shape(pixel_array)) == 3: #2d rgb
pixeldataIn = pixel_array[:,:,0].transpose()
pixeldataInR = (pixel_array[:,:,0]).transpose()
pixeldataInG = (pixel_array[:,:,1]).transpose()
pixeldataInB = (pixel_array[:,:,2]).transpose()
elif len(np.shape(pixel_array)) == 4: #3d rgb
pixeldataIn = (pixel_array[-1,:,:,0]).transpose()
pixeldataInR = (pixel_array[-1,:,:,0]).transpose()
pixeldataInG = (pixel_array[-1,:,:,1]).transpose()
pixeldataInB = (pixel_array[-1,:,:,2]).transpose()
# remove rgb info
for y in range(dcmInfile.Rows):
for x in range(dcmInfile.Columns):
r = pixeldataInR[x,y]
g = pixeldataInG[x,y]
b = pixeldataInB[x,y]
ma = max(r,g,b)
mi = min(r,g,b)
if ma != mi:
pixeldataIn[x,y] = 0
else:
path = os.path.dirname(instancedict[0])
for ip in instancedict:
if os.path.dirname(ip) != path:
raise ValueError("{} ERROR! multiple would-be dicom files scattered over multiple dirs!".format(logTag))
try:
dcmInfile = dcmseries.read_files(path, True, readPixelData=False)[0]
if not headers_only: # NOTE: Rescaling is already done pydicom_series, but maybe not for stupid MR
pixeldataIn = np.transpose(dcmInfile.get_pixel_array(),(0,2,1))
except Exception as e:
raise ValueError("{} ERROR! {} is not a valid non-Enhanced DICOM series".format(logTag, path))
return dcmInfile,pixeldataIn,getDICOMMode(dcmInfile)
