I recently study with Dicom images deep learning. I want to move my dicom image processing code from python to c++. Following is my python code.
def window_img(dcm, width=None, level=None):
pixels = dcm.pixel_array * dcm.RescaleSlope + dcm.RescaleIntercept
lower = level - (width / 2)
upper = level + (width / 2)
pixels[pixels<lower] = lower
pixels[pixels>upper] = upper
pixels = (pixels - (level - width//2)) / width
return pixels
def meta_dicom_convert(dcm, ww, wc):
b = window_img(dcm, ww[0], wc[0])
g = window_img(dcm, ww[1], wc[1])
r = window_img(dcm, ww[2], wc[2])
image = np.concatenate([b, g, r], axis=2)
return image
And I try to do something like this in c++. However, I only found some method like cv::merge. I use cv::merge. But it seems a little differet from images combined by np.concatenate.
My C++ code:
DcmFileFormat dfile;
OFCondition result = dfile.loadFile("D:\\python\\RSNA\\stage_2_train\\ID_c8355f255.dcm");
DcmDataset *dcmdataset = dfile.getDataset();
double slope, intercept;
dcmdataset->findAndGetFloat64(DCM_RescaleSlope, slope);
dcmdataset->findAndGetFloat64(DCM_RescaleIntercept, intercept);
DicomImage dcmimage_brain("D:\\python\\RSNA\\stage_2_train\\ID_c8355f255.dcm");
DicomImage dcmimage_subdural("D:\\python\\RSNA\\stage_2_train\\ID_c8355f255.dcm");
DicomImage dcmimage_bone("D:\\python\\RSNA\\stage_2_train\\ID_c8355f255.dcm");
int nWidth = dcmimage_brain.getWidth();
int nHeight = dcmimage_brain.getHeight();
cout << "size = " << nWidth << " x " << nHeight << endl;
int wcenter = 40, wwidth = 80;
int lower = wcenter - (wwidth / 2);
int upper = wcenter + (wwidth / 2);
dcmimage_brain.setWindow(wcenter, wwidth);
Uint8 *pixeldata_brain = (Uint8*)(dcmimage_brain.getOutputData(8));
if (pixeldata_brain)
{
for (int i = 0; i < nWidth * nHeight; ++i) {
if (pixeldata_brain[i] < lower)
pixeldata_brain[i] = lower;
if (pixeldata_brain[i] > upper)
pixeldata_brain[i] = upper;
pixeldata_brain[i] = (255 * (pixeldata_brain[i] - lower)) / (upper - lower);
}
}
Mat brain = Mat(nWidth, nHeight, CV_8UC1, pixeldata_brain);
//brain.convertTo(brain, CV_8UC1);
wcenter = 80;
wwidth = 200;
lower = wcenter - (wwidth / 2);
upper = wcenter + (wwidth / 2);
dcmimage_subdural.setWindow(wcenter, wwidth);
Uint8 *pixeldata_subdural = (Uint8*)(dcmimage_subdural.getOutputData(8));
if (pixeldata_subdural)
{
for (int i = 0; i < nWidth * nHeight; ++i) {
if (pixeldata_subdural[i] < lower)
pixeldata_subdural[i] = lower;
if (pixeldata_subdural[i] > upper)
pixeldata_subdural[i] = upper;
pixeldata_subdural[i] = (255 * (pixeldata_subdural[i] - lower)) / (upper - lower);
}
}
Mat subdural = Mat(nWidth, nHeight, CV_8UC1, pixeldata_subdural);
//subdural.convertTo(subdural, CV_8UC1);
wcenter = 40;
wwidth = 380;
lower = wcenter - (wwidth / 2);
upper = wcenter + (wwidth / 2);
dcmimage_bone.setWindow(wcenter, wwidth);
Uint8 *pixeldata_bone = (Uint8*)(dcmimage_bone.getOutputData(8));
if (pixeldata_bone) {
for (int i = 0; i < nWidth * nHeight; ++i) {
if (pixeldata_bone[i] < lower)
pixeldata_bone[i] = lower;
if (pixeldata_bone[i] > upper)
pixeldata_bone[i] = upper;
pixeldata_bone[i] = (255 * (pixeldata_bone[i] - lower) / (upper - lower));
}
}
Mat bone = Mat(nWidth, nHeight, CV_8UC1, pixeldata_bone);
imshow("bone", bone);
//bone.convertTo(bone, CV_8UC1);
//Mat bone = Mat(nWidth, nHeight, CV_16UC1, pbone);
//bone.convertTo(bone, CV_8UC1);
// new Image size
Mat image = Mat::zeros(nWidth, nHeight, CV_8UC3);
vector<Mat> channels;
split(image, channels);
channels.at(0) = brain;
channels.at(1) = subdural;
channels.at(2) = bone;
merge(channels, image);
imshow("mergeImage", image);
waitKey();
result image: (left side: cv::merge) (right side: np.concatenate) enter image description here
Is cv::merge actually not just concatenate images in channels? Is there any other method I can use in c++ to do thing like np.concatenate? Any reply would be appreciate. thanks