def save_one_slice(arr, filename,width=_width, height=_height): temp = np.zeros((height, width)) x = arr[np.arange(0, 15, 2)] y = arr[np.arange(1, 16, 2)] temp [x, y] = 255 from src.util import save_slice save_slice(temp, filename)
def save_all_landmarks_one_slice(arr, filename,width=_width, height=_height): from src.util import save_slice temp = np.zeros((height, width)) x = arr[:, :, np.arange(0, 15, 2)].reshape(-1, 1) y = arr[:, :, np.arange(1, 16, 2)].reshape(-1, 1) temp[x, y] = 255 save_slice(temp, filename)
def show_all_slices_one_slice(arr, width=_width, height=_height,save=False, filename=None): from src.util import show_slice, save_slice temp = np.zeros((height, width)) x = arr[:, np.arange(0, 15, 2)].reshape(-1, 1) y = arr[:, np.arange(1, 16, 2)].reshape(-1, 1) temp[x, y] = 255 show_slice(temp) if save == True: save_slice(temp, filename)
def show_one_slice(arr, width=_width, height=_height, save=False, filename=None): from src.util import show_slice temp = np.zeros((height, width)) x = arr[np.arange(0, 15, 2)] y = arr[np.arange(1, 16, 2)] temp[x, y] = 255 show_slice(temp) if save == True: from src.util import save_slice save_slice(temp, filename)
def show_all_landmarks_one_slice_one_vertebra(arr, width=_width, height=_height,save=False, folder=None, vn=None): from src.util import show_slice, save_slice temp = np.zeros((height, width)) x = arr[:, np.arange(0, 15, 2)].reshape(-1, 1) y = arr[:, np.arange(1, 16, 2)].reshape(-1, 1) temp[x, y] = 255 show_slice(temp) if save == True: if not os.path.exists(folder): os.makedirs(folder) filename = folder + vn + '.jpg' save_slice(temp, filename)
from src.util import read_jpg img = read_jpg(fn) data = np.array(img.convert('L'), dtype=np.int16) #import numpy as np #mask = np.zeros((patient_number, 512, 512), dtype = np.int16) #idx = data > 240 # find dural sac #mask[idx] = 255 #subtracting the low pass from original from scipy import ndimage npix = 3 gauss = ndimage.gaussian_filter(data, sigma=npix) high_pass = data - gauss idx = high_pass < 0 high_pass[idx] = 0 #from skimage.feature import canny # #canvas = np.zeros((50, 84), dtype=np.int16) #canvas = np.array(canny(high_pass/255., sigma=3)*255, dtype=np.int16) ##canvas[i] = high_pass[i] from src.util import show_slice, save_slice show_slice(gauss) fn = '/Users/ruhansa/Desktop/gauss.jpg' save_slice(gauss, fn)
# data_dir = dir + '/data/p1/' data_dir = "/Users/ruhansa/Dropbox/spine/data/" data = {} from src.utils.util import read_dicom patient_num = 4 folder = data_dir + "p" + str(patient_num) + "/t2w/" data = read_dicom(folder) # from src.util import show_volume # show_volume(data,data.shape[0]) import numpy as np mask = np.zeros((512, 512), dtype=np.int16) idx = data < 30 n = 7 mask[idx[n]] = 255 from src.util import save_slice save_slice(mask, "/Users/ruhansa/Dropbox/spine/data/p" + str(patient_num) + "/label/" + str(n) + "_init.jpg") save_slice(data[n], "/Users/ruhansa/Dropbox/spine/data/p" + str(patient_num) + "/label/" + str(n) + "_raw.jpg") from src.util import show_slice show_slice(mask) show_slice(data[n]) # from skimage.filter import canny # show_slice(canny(data[n], 10))