microCT_auto_processing/Registration_ML_Tiankuo_femur.py at main · Tiankuo528/microCT_auto_processing · GitHub

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#! /home/blue/ml/sitk/bin/python

# -*- coding: utf-8 -*-

import SimpleITK as sitk
from Across_limb_registration import reg_transform, cent_transform
import os
import re
import logging
from shubow_tools import imreadseq_multithread,imsaveseq, auto_crop, down_scale, init_transform_best_angle
import shutil
import numpy as np

config = {
    "workspace":r"D:\Tiankuo\101223 Tumor+Rad+Yoda1+WBV\segmentation\week 5\mechtest",
    "outputdir":r"D:\Tiankuo\101223 Tumor+Rad+Yoda1+WBV\registration\femur\week 5 registration",
    "refdir":r"D:\Tiankuo\101223 Tumor+Rad+Yoda1+WBV\registration\femur\reference_femur", #r"C:\Users\SplLabMEEG\Desktop\BalbC1.10.2022\3. Registration\reference", # #r"C:\Users\SplLabMEEG\Desktop\BalbC1.10.2022\3. Registration\reference",
    "img_z_range":[None,None],     #[75, 625],   [800,1350]  800,1600
    "ref_z_range":[None,None],
    "initial_transform_angles":[np.pi*i/16 for i in range(-16,10)],#   -1,2
    "BASELINE_REG":True,  #False, # True,
    "RETRY": False
}

wkdir = config["workspace"]
os.chdir(wkdir)
masterdir = config["workspace"]
masteroutput = config["outputdir"]
refdir = config["refdir"]

BASELINE_REGISTRATION = config["BASELINE_REG"]

if not os.path.exists(masteroutput):
    os.mkdir(masteroutput)

format = "%(asctime)s: %(message)s"
logging.basicConfig(format = format, level = logging.INFO,
                    datefmt="%H:%M:%S")

if BASELINE_REGISTRATION:
    logging.info('Loading reference image...')
    ref_img = imreadseq_multithread(refdir,thread = 2, sitkimg=True, z_range=config["ref_z_range"])
#ref_img = down_scale(ref_img, down_scale_factor=1.0)

failed_list = []


# with open("failed.txt", "r") as f :
#     retry_file = f.readlines()

# retry_list = [i.strip("\n") for i in retry_file]

for file in sorted(os.listdir(masterdir))[0:] :
    if re.search(r"\d{3}.(week.\d) (left|right) femur", file):  #and file[:-6] in retry_list:
        imgtitle = file

        if not BASELINE_REGISTRATION:
            logging.info('Loading reference image : {}'.format(re.sub(r"week [0-5]", "week 0",file)+' registered'))
            ref_img = imreadseq_multithread(os.path.join(refdir, re.sub(r"week [0-5]", "week 0",file)+' registered')
                ,thread = 2, sitkimg=True, rmbckgrd=75, z_range=config["ref_z_range"])

        logging.info('Loading image {} ...'.format(imgtitle))

        lower = config["img_z_range"][0]
        upper = config["img_z_range"][1]

        tar_img = imreadseq_multithread(os.path.join(masterdir,file), thread=2,
                                sitkimg = True, z_range=(lower, upper))

        logging.info('Initial Transforming ...')
        ini_transform = init_transform_best_angle(sitk.Cast(tar_img, sitk.sitkFloat32),sitk.Cast(ref_img, sitk.sitkFloat32),
                angles=config["initial_transform_angles"], centerfilter="MOMENTS")
        #ini_transform = sitk.ReadTransform("/media/spl/D/MicroCT_data/Machine learning/Heart inj Aug-2019 tibia registration/381 week 0 left tibia registered/381 week 0 left tibiareg_transform.tfm")
        metric_values = []
        multires_iterations = []

        suboutput = os.path.join(masteroutput,imgtitle+" registered")
        logging.info('Registration of {} is in process...'.format(imgtitle))

        if os.path.exists(suboutput):
            shutil.rmtree(suboutput)

        os.mkdir(suboutput)

        try:
            tar_reg,tar_reg_transform = reg_transform(ref_img,tar_img,ini_transform,imgtitle,suboutput)
            logging.info("Saving images...")
            imsaveseq(tar_reg, suboutput, imgtitle+'_Reg')
            sitk.WriteTransform(tar_reg_transform,os.path.join(suboutput,imgtitle+'reg_transform.tfm'))
            logging.info('Registration of {} is in completed...'.format(imgtitle))
        except RuntimeError as ex:
            logging.info('Registration of {} failed...'.format(imgtitle))
            failed_list.append(file)
            print(ex)
            pass

print(failed_list)

with open("failed_retry.txt", "w") as f:
    for i in failed_list:
        f.write(i+"\n")