Using dicom Images with OpenCV in Python

Question

I am trying to use a dicom image and manipulate it using OpenCV in a Python environment. So far I have used the pydicom library to read the dicom(.dcm) image data and using the pixel array attribute to display the picture using OpenCV imshow method. But the output is just a blank window. Here is the snippet of code I am using at this moment.

import numpy as np
import cv2
import pydicom as dicom

ds=dicom.dcmread('sample.dcm')
cv2.imshow('sample image dicom',ds.pixel_array)

cv2.waitkey()

If i print out the array which is used here, the output is different from what i would get with a normal numpy array. I have tried using matplotlib imshow method as well and it was able to display the image with some colour distortions. Is there a way to convert the array into a legible format for OpenCV?

Asked By: Mushfiq Alam

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Answer 1

I have figured out a way to get the image to show. As Dan mentioned in the comments, the value of the matrix was scaled down and due to the imshow function, the output was too dark for the human eye to differentiate. So, in the end the only thing i needed to do was multiply the entire mat data with 128. The image is showing perfectly now. multiplying the matrix by 255 over exposes the picture and causes certain features to blow. Here is the revised code.

import numpy as np
import cv2
import pydicom as dicom

ds=dicom.dcmread('sample.dcm')
dcm_sample=ds.pixel_array*128
cv2.imshow('sample image dicom',dcm_sample)

cv2.waitkey()

Answered By: Mushfiq Alam

Answer 2

I don’t think that is a correct answer. It works for that particular image because most of your pixel values are in the lower range. Check this OpenCV: How to visualize a depth image. It is for c++ but easily adapted to Python.

Answered By: user2466766

Answer 3

Faced a similar issue. Used exposure.equalize_adapthist() (source). The resulting image isn’t a hundred percent to that you would see using a DICOM Viewer but it’s the best I was able to get.

import numpy as np
import cv2
import pydicom as dicom
from skimage import exposure

ds=dicom.dcmread('sample.dcm')
dcm_sample=ds.pixel_array
dcm_sample=exposure.equalize_adapthist(dcm_sample)
cv2.imshow('sample image dicom',dcm_sample)

cv2.waitkey()

Answered By: Azizah Masturina

Answer 4

This is the best way(in my opinion) to open image in opencv as a numpy array while perserving the image quality:

import numpy as np
import pydicom, os, cv2

def dicom_to_numpy(ds):
    DCM_Img = ds
    rows = DCM_Img.get(0x00280010).value #Get number of rows from tag (0028, 0010)
    cols = DCM_Img.get(0x00280011).value #Get number of cols from tag (0028, 0011)
    
    Instance_Number = int(DCM_Img.get(0x00200013).value) #Get actual slice instance number from tag (0020, 0013)

    Window_Center = int(DCM_Img.get(0x00281050).value) #Get window center from tag (0028, 1050)
    
    Window_Width = int(DCM_Img.get(0x00281051).value) #Get window width from tag (0028, 1051)

    Window_Max = int(Window_Center + Window_Width / 2)
    Window_Min = int(Window_Center - Window_Width / 2)


    if (DCM_Img.get(0x00281052) is None):
        Rescale_Intercept = 0
    else:
        Rescale_Intercept = int(DCM_Img.get(0x00281052).value)

    if (DCM_Img.get(0x00281053) is None):
        Rescale_Slope = 1
    else:
        Rescale_Slope = int(DCM_Img.get(0x00281053).value)

    New_Img = np.zeros((rows, cols), np.uint8)
    Pixels = DCM_Img.pixel_array

    for i in range(0, rows):
        for j in range(0, cols):
            Pix_Val = Pixels[i][j]
            Rescale_Pix_Val = Pix_Val * Rescale_Slope + Rescale_Intercept

            if (Rescale_Pix_Val > Window_Max): #if intensity is greater than max window
                New_Img[i][j] = 255
            elif (Rescale_Pix_Val < Window_Min): #if intensity is less than min window
                New_Img[i][j] = 0
            else:
                New_Img[i][j] = int(((Rescale_Pix_Val - Window_Min) / (Window_Max - Window_Min)) * 255) #Normalize the intensities
                
    return New_Img


file_path = "C:/example.dcm"
image = pydicom.read_file(file_path)
image = dicom_to_numpy(image)

#show image
cv2.imshow('sample image dicom',image)
cv2.waitKey(0)
cv2.destroyAllWindows()

Answered By: Esa Anjum

Using dicom Images with OpenCV in Python

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