Source code for spinalcordtoolbox.cropping

#!/usr/bin/env python
# -*- coding: utf-8
# Functions dealing with image cropping

import logging
import numpy as np

from .image import Image, zeros_like

logger = logging.getLogger(__name__)

[docs]class BoundingBox(object): """ """ def __init__(self, xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None): self.xmin = xmin self.xmax = xmax self.ymin = ymin self.ymax = ymax self.zmin = zmin self.zmax = zmax
[docs] def get_minmax(self, img=None): """ Get voxel-based bounding box from coordinates. Replaces '-1' with max dim along each axis, '-2' with max dim minus 1, etc. :param img: Image object to get dimensions :return: """ def _get_min_value(input): if input is None: return 0 else: return input def _get_max_value(input, dim): # If empty, return maximum dimension (i.e. no change) if input is None: return dim # If input is "-1", return maximum dimension (i.e. no change). If input is "-2", returns maximum # dimension minus one, etc. elif np.sign(input) == -1: return input + dim # If user specified a non-negative value, use that else: return input xyz_to_num = {'x': 0, 'y': 1, 'z': 2} bbox_voxel = BoundingBox() for attr, value in self.__dict__.items(): if attr[-3:] == 'min': bbox_voxel.__setattr__(attr, _get_min_value(self.__getattribute__(attr))) elif attr[-3:] == 'max': bbox_voxel.__setattr__(attr, _get_max_value(self.__getattribute__(attr), img.dim[xyz_to_num[attr[0]]])) else: raise Exception(ValueError) return bbox_voxel
class ImageCropper(object): def __init__(self, img_in, mask=None, bbox=BoundingBox(), ref=None): """ :param img_in: :param mask: :param bbox: BoundingBox object with min and max values for each dimension, used for cropping. :param ref: """ self.img_in = img_in self.mask = mask self.bbox = bbox self.ref = ref def crop(self, background=None): """ Crop image (change dimension) :param background: int: If set, the output image will not be cropped. Instead, voxels outside the bounding box will be set to the value specified by this parameter. :return Image: img_out """ bbox = self.bbox"Bounding box: x=[{}, {}], y=[{}, {}], z=[{}, {}]" .format(bbox.xmin, bbox.xmax+1, bbox.ymin, bbox.ymax+1, bbox.zmin, bbox.zmax+1)) # Crop the image if background is None:"Cropping the image...") data_crop =[bbox.xmin:bbox.xmax+1, bbox.ymin:bbox.ymax+1, bbox.zmin:bbox.zmax+1] img_out = Image(param=data_crop, hdr=self.img_in.hdr) # adapt the origin in the sform and qform matrix new_origin =, [bbox.xmin, bbox.ymin, bbox.zmin, 1]) img_out.hdr.structarr['qoffset_x'] = new_origin[0] img_out.hdr.structarr['qoffset_y'] = new_origin[1] img_out.hdr.structarr['qoffset_z'] = new_origin[2] img_out.hdr.structarr['srow_x'][-1] = new_origin[0] img_out.hdr.structarr['srow_y'][-1] = new_origin[1] img_out.hdr.structarr['srow_z'][-1] = new_origin[2] # Set voxels outside the bbox to the value 'background' else:"Setting voxels outside the bounding box to: {}".format(background)) img_out = self.img_in.copy()[:] = background[bbox.xmin:bbox.xmax+1, bbox.ymin:bbox.ymax+1, bbox.zmin:bbox.zmax+1] = \[bbox.xmin:bbox.xmax+1, bbox.ymin:bbox.ymax+1, bbox.zmin:bbox.zmax+1] return img_out def get_bbox_from_minmax(self, bbox=None): """ Get voxel bounding box from xmin, xmax, ymin, ymax, zmin, zmax user input """ self.bbox = bbox.get_minmax(img=self.img_in) def get_bbox_from_mask(self, img_mask): """ Get bounding box from input binary mask, by looking at min/max values of the binary object in each dimension. """ data_nonzero = np.nonzero( # find min and max boundaries of the mask dim = len(data_nonzero) self.bbox.xmin, self.bbox.ymin, self.bbox.zmin = [min(data_nonzero[i]) for i in range(dim)] self.bbox.xmax, self.bbox.ymax, self.bbox.zmax = [max(data_nonzero[i]) for i in range(dim)] def get_bbox_from_ref(self, img_ref): """ Get bounding box from input reference image, by looking at min/max indices in each dimension. img_ref and self.img_in should have the same dimensions. """ from spinalcordtoolbox.resampling import resample_nib # Check that img_ref has the same length as img_in if not len( == len( logger.error("Inconsistent dimensions: n_dim(img_ref)={}; n_dim(img_in)={}" .format(len(, len( raise Exception(ValueError) # Fill reference data with ones[:] = 1 # Resample new image (in reference coordinates) into input image img_ref_r = resample_nib(img_ref, image_dest=self.img_in, interpolation='nn', mode='constant') #'test.nii') # for debug # Get bbox from this resampled mask self.get_bbox_from_mask(img_ref_r) def get_bbox_from_gui(self): """ Launch a GUI. The medial sagittal plane of the image is shown. User selects two points: top-left and bottom- right of the cropping window. Note: There is no cropping along the right-left direction. :return: """ from spinalcordtoolbox.gui import base from spinalcordtoolbox.gui.sagittal import launch_sagittal_dialog # Change orientation to SAL (for displaying sagittal view in the GUI) native_orientation = self.img_in.orientation self.img_in.change_orientation('SAL') # Launch GUI params = base.AnatomicalParams() params.vertebraes = [1, 2] # TODO: Have user draw a sliding rectangle instead (more intuitive) params.subtitle = "Click on the top-left (Label 1) and bottom-right (Label 2) of the image to select your " \ "cropping window." img_labels = zeros_like(self.img_in) launch_sagittal_dialog(self.img_in, img_labels, params) # Extract coordinates img_labels.change_orientation(native_orientation) cropping_coord = img_labels.getNonZeroCoordinates(sorting='value') # Since there is no cropping along the R-L direction, xmin/xmax are based on image dimension self.bbox.xmin, self.bbox.ymin, self.bbox.zmin = ( 0, min(cropping_coord[0].y, cropping_coord[1].y), min(cropping_coord[0].z, cropping_coord[1].z), ) self.bbox.xmax, self.bbox.ymax, self.bbox.zmax = ( img_labels.dim[0], max(cropping_coord[0].y, cropping_coord[1].y), max(cropping_coord[0].z, cropping_coord[1].z), ) # Put back input image in native orientation self.img_in.change_orientation(native_orientation)