将12位DICOM图像转换为8位jpeg [英] converting 12 bit DICOM image to 8 bit jpeg

问题描述

我正在尝试使用dicom库将DICOM文件加载到python中。我已经完成了以下操作

I am trying to load DICOM files into python using the dicom library. I have done the following

ds=dicom.read_file(r"C:\Users\Z003SPFR.AD005\ML\GLCM AND SVM\data\NECT\1.IMA")
#    # store the raw image data
DicomImage = ds.pixel_array

这使我看到的值似乎是12位，因为获得的最大值约为3047，最小值为0。然后，我将自己的映射函数设置为将其设置为0-255。我使用了以下代码：

This gives me values that appear to be 12 bit, since the highest value obtained was around 3047 and lowest value was 0. Then i made my own mapping function to bring it to the range 0-255. I used the following code:

leftMin = 0
leftMax = np.amax(DicomImage)

rightMin = 0
rightMax = 255



def translate(value, leftMin, leftMax, rightMin, rightMax):
    # Figure out how 'wide' each range is
    leftSpan = leftMax - leftMin
    rightSpan = rightMax - rightMin

    # Convert the left range into a 0-1 range (float)
    valueScaled = float(value - leftMin) / float(leftSpan)

    # Convert the 0-1 range into a value in the right range.
    return rightMin + (valueScaled * rightSpan)

#print(translate(value, leftMin, leftMax, rightMin, rightMax))



def int12_to_int8(img):
    img_array = []

    for eachRow in img:
        for eachPix in eachRow:
            img_array.append(translate(eachPix,leftMin, leftMax, rightMin, rightMax))
    img_array = np.array(img_array)
    img_array = img_array.reshape(512,512)  
    return img_array

correct_range_image = int12_to_int8(DicomImage)

完成此操作后，我意识到数组img_array的类型为uint16。我希望将其作为uint8，所以我使用以下行将其转换为uint8：

After doing this I realized that the array img_array was of type uint16. I wanted it as uint8, so i used the following line to convert to uint8:

cvuint8 = cv2.convertScaleAbs(correct_range_image)

然后我显示了生成的图像。但是我收到的图像不能很好地代表原始图像。我已经张贴了原始图像和转换后图像的图片。如何更好地进行转换，以便更好地表现原始图像？我以前显示的代码在这里：

Then I displayed the resulting image. But i received an image that didn't represent the original image very well. I have posted pictures of the original image and the converted image. How can I make the conversion better so that I get a better representation of the original image?? Code I used to display is here :

cv2.imwrite('1.jpeg', cvuint8 )
cv2.imshow('image',cvuint8 )[enter image description here][1]
cv2.waitKey(0)

图像

[1]转换后的图像： https://i.stack.imgur.com/wdGCo.jpg
[2]原始图片： https://i.stack.imgur.com/JyfYI.jpg

[1] Converted Image: https://i.stack.imgur.com/wdGCo.jpg [2] Original Image: https://i.stack.imgur.com/JyfYI.jpg

推荐答案

我想出了解决问题的方法。正如艾哈迈德·艾哈迈德（Ahmed）前面提到的那样，DICOM围绕重新缩放斜率，截距和窗口水平/宽度进行适当显示。经过大量的文档之后，这是使用OpenCV，numpy和pydicom库在Python中渲染DICOM的方法，这些库使所有工作变得简单

I figured out the solution for my problem.As mentioned above by Ahmed, DICOM plays around rescale slope, intercept and window level/width for proper display. After going through lot of documents, here is the way to render DICOM in Python using OpenCV,numpy and pydicom libraries which make all work easy

代码：
1读取图像

Code: 1.Read the image

ds=dicom.read_file("image_path")
# store the raw image data
img = ds.pixel_array

1. 使用重新缩放坡度并截取来自图像标题的信息并将其转换。

1. Use rescale slope and intercept information from the image header and translate it.

rescale_slope = 1
rescale_intercept = -1024

rescale_slope=1 rescale_intercept=-1024

def translate(value,rescale_slope,rescale_intercept):

return (value*rescale_slope)+rescale_intercept 

def int12_to_int8(DicomImage):
    img_array = []

for eachRow in DicomImage:
    for eachPix in eachRow:
        img_array.append(translate(eachPix,rescale_slope,rescale_intercept))
img_array = np.array(img_array)
img_array = img_array.reshape(512,512)  
return img_array

img_1 = int12_to_int8(img)

3。使用窗口级别

3.Use window level and width information from the image header to display in the proper range.

def get_LUT_value(data, window, level)

    return np.piecewise(data, 
        [data <= (level - 0.5 - (window-1)/2),
            data > (level - 0.5 + (window-1)/2)],
            [0, 255, lambda data: ((data - (level - 0.5))/(window-1) + 0.5)*(255-0)])

level=200
window=800

scaled_img=get_LUT_value(img, window, level)

4。最后，按需要添加最终图像

4.Finally, with final image as wanted

scaled_img = cv2.convertScaleAbs(scaled_img)
cv2.imshow('image',scaled_img)
cv2.imwrite("hem.jpg",scaled_img)
cv2.waitKey(0)

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