lung_seg.py 文件源码

def get_masks(im):
    '''
    Step 1: Convert into a binary image.
    '''
    print('step1')
    binary = im < 604
    # plt.imshow(binary,cmap=plt.cm.gray)
    # plt.show()

    '''
    Step 2: Remove the blobs connected to the border of the image.
    '''
    print('step2')
    cleared = clear_border(binary)
    # plt.imshow(cleared,cmap=plt.cm.gray)
    # plt.show()
    '''
    Step 3: Label the image.
    '''
    print('step3')
    label_image = label(cleared)
    # plt.imshow(label_image,cmap=plt.cm.gray)
    # plt.show()

    '''
    Step 4: Keep the labels with 2 largest areas.
    '''
    print('step4')
    areas = [r.area for r in regionprops(label_image)]
    areas.sort()
    if len(areas) > 2:
        for region in regionprops(label_image):
            if region.area < 10 and region.area > 3:
                print(region.centroid,region.area)
                # print(region.area)
                centroid = region.centroid
                plot_im(im,centroid)
                # label_image[int(centroid[0]),int(centroid[1])] = 1000
                # for coordinates in region.coords:
                #     label_image[coordinates[0], coordinates[1]] = 0
    # binary = label_image > 999
    # plt.imshow(binary,cmap=plt.cm.gray)
    # plt.show()

    '''
    Step 5: Erosion operation with a disk of radius 2. This operation is
    seperate the lung nodules attached to the blood vessels.
    '''
    # print('step5')
    # selem = disk(2)
    # binary = binary_erosion(binary, selem)
    # plt.imshow(binary,cmap=plt.cm.gray)
    # plt.show()