DICOM loaded with wrong orientation

Describe the bug Hi, I’m loading some DICOM from this dataset : https://www.ircad.fr/fr/recherche/3d-ircadb-01-fr/ The way I load it is with LoadImaged

The problem is that the orientation of the data is wrong (see screenshot below)

To Reproduce Download the dataset mentioned above Run this code (replace ircad_dir by the folder where you downloaded the data)

from monai.transforms import (Compose, LoadImaged, SaveImaged, Spacingd, Orientationd)
from monai.data import DataLoader, Dataset
from monai.transforms.utility.dictionary import AddChanneld
import os

root_dir = r'..\datas\\'
ircad_dir = root_dir + r'data_ircad\\'


train_images_ircad = [os.path.join(ircad_dir, x, 'PATIENT_DICOM')  for x in os.listdir(ircad_dir)]
train_labels_ircad = [os.path.join(ircad_dir, x, 'LABELLED_DICOM')  for x in os.listdir(ircad_dir)]
data_dict = [{'image':train_images_ircad[0], 'label':train_labels_ircad[0]}]

transforms = Compose([
    LoadImaged(keys=["image","label"]),
    AddChanneld(keys=["image", "label"]),
    Spacingd(keys=["image", "label"], pixdim=(1.5, 1.5, 2.0), mode=("bilinear", "nearest")),
    Orientationd(keys=["image", "label"], axcodes="RAS"),
    SaveImaged(keys=["image", "label"], output_postfix='_after_trans')
    ])


ds = Dataset(data=data_dict, transform=transforms)
dl = DataLoader(ds, batch_size=1, num_workers=0)

for data in dl:
    continue

Expected behavior the data should have the correct orientation

Screenshots note : the ground truth is obtained by opening the DICOM from 3D Slicer Environment

================================ Printing MONAI config…

MONAI version: 0.4.0+127.g380f042 Numpy version: 1.19.2 Pytorch version: 1.7.1 MONAI flags: HAS_EXT = False, USE_COMPILED = False MONAI rev id: 380f042dec9c55ba1a5ab241ae6b1a7b3e2b07fb

Optional dependencies: Pytorch Ignite version: 0.4.2 Nibabel version: 3.2.1 scikit-image version: 0.18.1 Pillow version: 8.1.1 Tensorboard version: 2.4.1 gdown version: 3.12.2 TorchVision version: 0.8.2 ITK version: 5.1.2 tqdm version: 4.56.0 lmdb version: 1.1.1 psutil version: 5.8.0

For details about installing the optional dependencies, please visit: https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies

================================ Printing system config…

System: Windows Win32 version: (‘10’, ‘10.0.18362’, ‘SP0’, ‘Multiprocessor Free’) Win32 edition: Core Platform: Windows-10-10.0.18362-SP0 Processor: Intel64 Family 6 Model 158 Stepping 10, GenuineIntel Machine: AMD64 Python version: 3.8.8 Process name: python.exe Command: [‘C:\Users\Camille\anaconda3\envs\kitware\python.exe’, ‘c:\Users\Camille\Desktop\important\Kitware\liver-segmentation\segmentation\tmp.py’] Open files: [popenfile(path=‘C:\Program Files\WindowsApps\Microsoft.LanguageExperiencePackfr-FR_18362.35.108.0_neutral__8wekyb3d8bbwe\Windows\System32\fr-FR\kernel32.dll.mui’, fd=-1), popenfile(path=‘C:\Program Files\WindowsApps\Microsoft.LanguageExperiencePackfr-FR_18362.35.108.0_neutral__8wekyb3d8bbwe\Windows\System32\fr-FR\KernelBase.dll.mui’, fd=-1)] Num physical CPUs: 6 Num logical CPUs: 12 Num usable CPUs: 12 CPU usage (%): [9.7, 1.4, 16.7, 1.4, 12.7, 2.8, 9.9, 9.9, 8.5, 1.4, 5.6, 56.9] CPU freq. (MHz): 2208 Load avg. in last 1, 5, 15 mins (%): [0.0, 0.0, 0.0] Disk usage (%): 90.1 Avg. sensor temp. (Celsius): UNKNOWN for given OS Total physical memory (GB): 15.9 Available memory (GB): 8.2 Used memory (GB): 7.7

================================ Printing GPU config…

Num GPUs: 1 Has CUDA: True CUDA version: 10.2 cuDNN enabled: True cuDNN version: 7605 Current device: 0 Library compiled for CUDA architectures: [‘sm_37’, ‘sm_50’, ‘sm_60’, ‘sm_61’, ‘sm_70’, ‘sm_75’, ‘compute_37’] GPU 0 Name: GeForce GTX 1070 with Max-Q Design GPU 0 Is integrated: False GPU 0 Is multi GPU board: False GPU 0 Multi processor count: 16 GPU 0 Total memory (GB): 8.0 GPU 0 Cached memory (GB): 0.0 GPU 0 Allocated memory (GB): 0.0 GPU 0 CUDA capability (maj.min): 6.1

[thewtex]

Hi @JumpLK, I will work on a patch for this.

[JumpLK]

Hi, thank you for your answers, are you working on the issue or should I try to make a workaround on my side ?