def contours2images(patient_folder):
image_folder = pjoin(patient_folder, 'sa', 'images')
con_file = pjoin(patient_folder, 'sa', 'contours.con')
# reading the dicom files
dr = DCMreaderVM(image_folder)
# reading the contours
cr = CONreaderVM(con_file)
contours = cr.get_hierarchical_contours()
# drawing the contours for the images
for slc in contours:
for frm in contours[slc]:
image = dr.get_image(slc, frm) # numpy array
cntrs = []
rgbs = []
for mode in contours[slc][frm]:
# choose color
if mode == 'ln': # left endocardium -> red
rgb = [1, 0, 0]
elif mode == 'lp': # left epicardium -> green
rgb = [0, 1, 0]
elif mode == 'rn': # right endocardium -> yellow
rgb = [1, 1, 0]
else:
rgb = None
if rgb is not None:
cntrs.append(contours[slc][frm][mode])
rgbs.append(rgb)
if len(cntrs) > 0:
draw(image, cntrs, rgbs)
def create_pickle_for_patient(in_dir, out_dir):
scan_id = os.path.basename(in_dir)
image_folder = os.path.join(in_dir, "sa", "images")
con_file = os.path.join(in_dir, "sa", "contours.con")
meta_txt = os.path.join(in_dir, "meta.txt")
if not os.path.isdir(image_folder):
logger.error("Could not find image folder for: {}".format(scan_id))
return
if not os.path.isfile(con_file):
logger.error("Could not find .con file for: {}".format(scan_id))
return
if not os.path.isfile(meta_txt):
logger.error("Could not find meta.txt file for: {}".format(scan_id))
return
dr = DCMreaderVM(image_folder)
if dr.num_frames == 0 and dr.num_frames == 0 or dr.broken:
logger.error("Could not create pickle file for {}".format(scan_id))
return
cr = CONreaderVM(con_file)
contours = left_ventricle_contours(cr.get_hierarchical_contours())
frame_slice_dict = collect_contour_slices_by_frames(contours)
if not (len(frame_slice_dict) == 2):
logger.error("Too many contour frames for {}".format(scan_id))
return
pickle_file_path = os.path.join(out_dir, scan_id + ".p")
create_path_for_file(pickle_file_path)
diastole_frame = frame_of_diastole(frame_slice_dict, contours)
sampling_slices = calculate_sampling_slices(frame_slice_dict,
diastole_frame)
sampling_contours = []
for slice_index in sampling_slices:
shape = dr.get_image(slice_index, diastole_frame).shape
sampling_contours.append(contours[slice_index][diastole_frame])
pathology = read_pathology(meta_txt)
shape = dr.get_image(sampling_slices[0], diastole_frame).shape
contour_diff_matricies = create_contour_diff_matricies(
sampling_contours, shape)
print(type(contour_diff_matricies))
patient_data = PatientData(scan_id, pathology, cr.get_volume_data(),
contour_diff_matricies)
with (open(pickle_file_path, "wb")) as pickleFile:
pickle.dump(patient_data, pickleFile)
def generate_patient_dataset(patient_id, patient_path, axis):
axes = [
d for d in os.listdir(patient_path)
if os.path.isdir(pjoin(patient_path, d))
]
if axis not in axes:
logger.warning(f'Patient {patient_id} has no data for {axis}')
return None
axis_path = pjoin(patient_path, axis)
if axis == 'sa':
images_path = pjoin(axis_path, 'images')
dr = DCMreaderVM(images_path)
if not (os.path.exists(pjoin(axis_path, 'contours.con'))):
return None
cr = CONreaderVM(pjoin(axis_path, 'contours.con'))
images, ROI = get_images_sa(dr, cr)
elif axis == 'sale':
dr = SaleReader(axis_path)
images = get_images_sale(dr)
ROI = None
else:
logger.error(r"Axis was not 'sa' nor 'sale'")
return None
if len(images) == 0:
return None
patient_data = dr.patient_data
label = get_label(patient_path)
return Patient(patient_id, axis, images, patient_data, label, SA_ROI=ROI)
# Reads the sa folder wiht dicom files and contours
# then draws the contours on the images.
from con_reader import CONreaderVM
from dicom_reader import DCMreaderVM
from con2img import draw_contourmtcs2image as draw
image_folder = 'C:\\dev\\LHYP\\sample\\13457546AMR801\\sa\\images'
con_file = 'C:\\dev\\LHYP\\sample\\13457546AMR801\\sa\\contours.con'
# reading the dicom files
dr = DCMreaderVM(image_folder)
# reading the contours
cr = CONreaderVM(con_file)
contours = cr.get_hierarchical_contours()
# drawing the contours for the images
for slc in contours:
for frm in contours[slc]:
image = dr.get_image(slc, frm) # numpy array
cntrs = []
rgbs = []
for mode in contours[slc][frm]:
# choose color
if mode == 'ln':
rgb = [1, 0, 0]
elif mode == 'lp':
rgb = [0, 1, 0]
elif mode == 'rn':
def get_patient(folder_in, patient):
temp_patient = Patient()
path = folder_in + patient
# get pathology from meta.txt
meta = open(path + '/meta.txt','rt')
line = meta.readline()
temp_patient.pathology = line.split("Pathology: ")[1].split(' \n')[0]
meta.close()
# check if images folder is empty, print Error if yes
if len(os.listdir(path+'/sa/images')) != 0:
# read dicom
dr=DCMreaderVM(path + '/sa/images')
# check if dicom is broken, print error if yes
if dr.broken is not True:
# get contours from con file
con_path = path + '/sa/contours.con'
if not os.path.exists(con_path):
print("No contour file exists: {}".format(path))
return None
cr=CONreaderVM(con_path)
contours = cr.get_hierarchical_contours()
# create temorary variables for contours and dcm images
tmp_dcm = []
tmp_contours = []
# get indices of slices with contour
slice_keys=list(contours.keys())
# get middle index in countours
if (len(contours) % 2) != 0:
mid_idx = int((len(contours)-1)/2)
else:
mid_idx = int(len(contours)/2)
# store the indices of the 7 slice we want to use
slice_indices=[
slice_keys[2],
slice_keys[3],
slice_keys[mid_idx-1],
slice_keys[mid_idx],
slice_keys[mid_idx+1],
slice_keys[-4],
slice_keys[-3]
]
# loop through contours using slice_indices
# store images in tmp_dcm, call im_conv to convert images (filter, resclale, uint8)
# check how many frames on one slice (frame_keys)
# save contours and image for the given frame
for slc in slice_indices:
frame_keys = list(contours[slc].keys())
if len(frame_keys) == 2:
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[0]]))
tmp_contours.append(contours[slc][frame_keys[0]])
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[1]]))
tmp_contours.append(contours[slc][frame_keys[1]])
elif len(frame_keys) > 2:
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[0]]))
tmp_contours.append(contours[slc][frame_keys[0]])
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[-1]]))
tmp_contours.append(contours[slc][frame_keys[-1]])
elif len(frame_keys) < 2:
if len(frame_keys) == 1:
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[0]]))
tmp_contours.append(contours[slc][frame_keys[0]])
if frame_keys[0] > 10:
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[0]-10]))
tmp_contours.append(None)
else:
tmp_dcm.append(im_conv(dr.dcm_images[slc][frame_keys[0]+10]))
tmp_contours.append(None)
else:
tmp_dcm.append(im_conv(dr.dcm_images[slc][8]))
tmp_contours.append(None)
tmp_dcm.append(im_conv(dr.dcm_images[slc][20]))
tmp_contours.append(None)
#add temporary dcm image list and contours to temp_patient
temp_patient.dcm_images = tmp_dcm
temp_patient.contours = tmp_contours
# get data from con file (CONreaderVM)
if cr.volume_data['Study_id='] != None:
temp_patient.study_id = cr.volume_data['Study_id='].split('\n')[0]
if cr.volume_data['Patient_gender='] != None:
temp_patient.gender = cr.volume_data['Patient_gender='].split('\n')[0]
if cr.volume_data['Field_of_view='] != None:
temp_patient.fov=[]
temp_patient.fov.append(cr.volume_data['Field_of_view='].split(' ')[0].split('x')[0])
temp_patient.fov.append(cr.volume_data['Field_of_view='].split(' ')[0].split('x')[1])
if cr.volume_data['Slicethickness='] != None:
temp_patient.slicethickness = cr.volume_data['Slicethickness='].split(' ')[0]
if cr.volume_data['Patient_height='] != None:
temp_patient.height = cr.volume_data['Patient_height='].split(' ')[0]
if cr.volume_data['Patient_weight='] != None:
temp_patient.weight = cr.volume_data['Patient_weight='].split(' ')[0]
# get pixel_spacing from dicom
temp_patient.pixel_spacing = dr.pixel_spacing
temp_patient.num_slices = dr.num_slices
return temp_patient
else:
print('Error: DCMreaderVM at {}/sa/images is broken'.format(path))
return None
else:
print('Error: ../images folder at {}/sa/images is empty'. format(path))
return None
for seq_index in range(dr.num_sequences):
for frame_index in range(dr.num_frames_per_sequence):
ds = dcmread(dr.get_path(seq_index, frame_index))
image = dr.get_image(seq_index, frame_index)
image = process(image, ds)
image = ((image - image.min()) *
(1 / (image.max() - image.min()) * 255)).astype('uint8')
images.append(Image.fromarray(image))
return images
axis = 'sa'
if 'sale' in dicoms_path: axis = 'sale'
reader = DCMreaderVM(dicoms_path) if axis == 'sa' else SaleReader(dicoms_path)
print('Reading frames from dicom')
os.makedirs('dicom_gifs', exist_ok=True)
save_path = os.path.join('dicom_gifs', f"{dicoms_path}.gif")
frames = get_sa_images(reader) if axis == 'sa' else get_sale_images(reader)
print(f'Saving to {save_path}')
frames[0].save(save_path,
save_all=True,
append_images=frames[1:],
duration=duration,
loop=0)