![]() Now to use the image we should rescale its pixels and put their values between 0 and 255. For that, we need to work with float pixels so that we won’t lose the information. I did that because in the next step we will scale the pixels so if we leave them integers so after the scaling we will have the overflow or the underflow losses. You can see that I added the function “astype” then float. The first line with open the Dicom image and the second one will extract the pixel array from it and that’s it for this part. New_image = ds.pixel_array.astype( float)Īs you can see, we do this in two lines of code. ds = pydicom.dcmread( 'the path to the image') For that, all we need to do is to call this component from the image. ![]() You know that a Dicom image contains a lot of information about the patient… So the image that we want to display or extract is one of the information that exists in the Dicom image. And to install Pillow we will do the same thing: pip install pillowĪnd finally Numpy: pip install numpy Extracting The Pixel Array You can use your terminal by putting this command: pip install pydicom Here are the steps that we will follow together:Īs we said, we need two libraries to make this process done, to install them it is very is. I will do with you step by step all the process, so don’t worry about that. And finally, the third one is Numpy to manipulates the arrays. The first one is Pydicom which is a library special for the Dicom images and the second one is Pillow which I prefer to use for displaying and saving the JPG image. ![]() To do that we need additional libraries to use with Python. In this case, we need only to visualize the image or to save it as a JPG or PNG so that we could open it with any software we want. The Dicom image is more than an image, it contains the pixels information, the patient information, and so on. dicom.In computer vision, we work often with medical images, and almost all the databases that we have contain DICOM images. DICOM (Digital Imaging and Communications in Medicine) is an image format for storing medical data, such as CT and MRI scan data, it also contains a lot of useful medical information, such as patient tag, study tag, series tag and image tag.If the source file is a very large file, it will take more time to upload, be sure to select a valid file.This converter cannot support encrypted or protected image files.If the file upload process takes a long time or is unresponsive or very slow, please try to cancel and resubmit.Before uploading, please make sure you agree to the terms of this website.The maximum upload file size is 200 MB.Once the upload is complete, the converter will redirect a web page to display the conversion results.Click the "Convert" button to start uploading your files.Select a image file (such as *.jpeg, *.jpg, *.nii, *.nii.gz, *.nrrd, *.pdf).The output file format is based on your choice. The tool will try to maintain the image quality of the source file and create a high quality image file as much as possible. This free DICOM converter can convert various image files to DICOM (Digital Imaging and Communications in Medicine) image, such as JPG, NIFTI, NRRD, PDF and more, or convert DICOM image files to other image formats, such as BMP, DNG, GIF, JPG, PDF, PNG, TIFF, WEBP and more.
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