def get_data_4_fusion(self, p_target_img, p_target_lab, p_atlas_imgs, p_atlas_labs, is_aug=True):
p_imgs = p_target_img + p_atlas_imgs
p_labs = p_target_lab + p_atlas_labs
imgs, labs = sitk_read_img_lab(p_imgs, p_labs, is_aug)
imgs = np.stack([convert_img_2_nor_array(img) for img in imgs], axis=-1)
labs = np.stack([convert_lab_2_array(lab) for lab in labs], axis=-1)
atlas_img = imgs[..., 1:]
atlas_lab = labs[..., 1:]
target_img = imgs[..., 0]
target_lab = labs[..., 0]
return np.expand_dims(target_img, axis=-1), np.expand_dims(target_lab,axis=-1), np.expand_dims(atlas_img,axis=-1), np.expand_dims(atlas_lab,axis=-1)
def get_dataV3(self, p_target_img, p_target_lab, p_atlas_imgs, p_atlas_labs, is_aug=True):
p_imgs = p_target_img
p_labs = p_target_lab+[p_atlas_labs[np.random.randint(len(p_atlas_labs))]]
imgs, labs = sitk_read_img_lab(p_imgs, p_labs, is_aug)
imgs = np.stack([convert_img_2_nor_array(img) for img in imgs], axis=-1)
labs = np.stack([convert_lab_2_array(lab) for lab in labs], axis=-1)
# atlas_img = imgs[..., 1:]
atlas_lab = labs[..., 1:]
target_img = imgs[..., 0]
target_lab = labs[..., 0]
# return np.expand_dims(target_img, axis=-1), np.expand_dims(target_lab,axis=-1), np.expand_dims(atlas_img,axis=-1), np.expand_dims(atlas_lab,axis=-1)
return np.expand_dims(target_img, axis=-1), np.expand_dims(target_lab,axis=-1),None, np.expand_dims(atlas_lab,axis=-1)
def get_data(self, p_target_img, p_target_lab, p_atlas_imgs, p_atlas_labs,is_aug=True):
p_imgs= p_target_img + p_atlas_imgs
p_labs= p_target_lab + p_atlas_labs
imgs,labs=sitk_read_img_lab(p_imgs, p_labs, is_aug)
# mk_or_cleardir('./tmp/')
# for img,lab,p_img,p_lab in zip(imgs,labs,p_imgs,p_labs):
# sitk_write_image(img,dir='./tmp/',name=get_name_wo_suffix(p_img))
# sitk_write_image(lab,dir='./tmp/',name=get_name_wo_suffix(p_lab))
imgs = np.stack([convert_img_2_nor_array(img) for img in imgs], axis=-1)
labs = np.stack([convert_lab_2_array(lab) for lab in labs], axis=-1)
atlas_imgs= imgs[ ...,1:]
target_img=imgs[ ...,0]
atlas_labs= labs[ ...,1:]
target_lab=labs[ ...,0]
return np.expand_dims(target_img,axis=-1), to_categorical(target_lab),atlas_imgs,atlas_labs
def get_dataV2(self, p_target_img, p_target_lab, p_atlas_imgs, p_atlas_labs, is_aug=True):
p_imgs = p_target_img + p_atlas_imgs
p_labs = p_target_lab + p_atlas_labs
imgs, labs = sitk_read_img_lab(p_imgs, p_labs, is_aug)
# mk_or_cleardir('./tmp/')
# for img,lab,p_img,p_lab in zip(imgs,labs,p_imgs,p_labs):
# sitk_write_image(img,dir='./tmp/',name=get_name_wo_suffix(p_img))
# sitk_write_image(lab,dir='./tmp/',name=get_name_wo_suffix(p_lab))
imgs = np.stack([convert_img_2_nor_array(img) for img in imgs], axis=-1)
labs = np.stack([convert_lab_2_array(lab) for lab in labs], axis=-1)
atlas_img = imgs[..., 1]
atlas_lab = labs[..., 1]
target_img = imgs[..., 0]
target_lab = labs[..., 0]
conv_target_lab=ndimage.convolve(target_lab,np.ones([self.args.patch_size,self.args.patch_size,self.args.patch_size]))
conv_atlas_lab=ndimage.convolve(atlas_lab,np.ones([self.args.patch_size,self.args.patch_size,self.args.patch_size]))
denominator=conv_atlas_lab+conv_target_lab
numerator=ndimage.convolve(target_lab*atlas_lab,np.ones([self.args.patch_size,self.args.patch_size,self.args.patch_size]))
sim=2*numerator.astype(np.float32)/(denominator.astype(np.float32)+0.000001)
# sitk_write_image(np.squeeze(atlas_labs),dir='./tmp/',name='input')
# sitk_write_image(np.squeeze(target_lab),dir='./tmp/',name='gt')
return np.expand_dims(target_img, axis=-1), np.expand_dims(target_lab,axis=-1), np.expand_dims(atlas_img,axis=-1), np.expand_dims(atlas_lab,axis=-1),np.expand_dims(sim,axis=-1)