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  2. Studierfenster - Wikipedia

    en.wikipedia.org/wiki/Studierfenster

    Brain Tumor Segmentation under Studierfenster. Aortic Dissection Inpainting under Studierfenster. Studierfenster or StudierFenster (SF) [1] [2] [3] is a free, non-commercial open science client/server-based medical imaging processing online framework.

  3. Brain tumor - Wikipedia

    en.wikipedia.org/wiki/Brain_tumor

    Most brain tumors have higher ADC than normal brain tissues and doctors can match the observed ADC of the patient's brain tumor with a list of accepted ADC to identify tumor type. DWI is also useful for treatment and therapy purposes where changes in diffusion can be analyzed in response to drug, radiation, or gene therapy.

  4. Image registration - Wikipedia

    en.wikipedia.org/wiki/Image_registration

    Examples include registration of brain CT/MRI images or whole body PET/CT images for tumor localization, registration of contrast-enhanced CT images against non-contrast-enhanced CT images [15] for segmentation of specific parts of the anatomy, and registration of ultrasound and CT images for prostate localization in radiotherapy.

  5. Radiomics - Wikipedia

    en.wikipedia.org/wiki/Radiomics

    After the images have been saved in the database, they have to be reduced to the essential parts, in this case the tumors, which are called “volumes of interest”. [ 2 ] Because of the large image data that needs to be processed, it would be too much work to perform the segmentation manually for every single image if a radiomics database ...

  6. Medical open network for AI - Wikipedia

    en.wikipedia.org/wiki/Medical_open_network_for_AI

    For instance, it has been utilized in academic research involving automatic cranio-facial implant design, [29] brain tumor analysis from Magnetic Resonance images, [30] identification of features in focal liver lesions from MRI scans, [31] radiotherapy planning for prostate cancer, [32] preparation of datasets for fluorescence microscopy ...

  7. ITK-SNAP - Wikipedia

    en.wikipedia.org/wiki/ITK-SNAP

    Automatic segmentation ITK-SNAP provides automatic functionality segmentation using the level-set method. This makes it possible to segment structures that appear somewhat homogeneous in medical images using very little human interaction. For example, the lateral ventricles in MRI can be segmented reliably, as can some types of tumors in CT and ...

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