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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.
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.
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.
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 ...
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 ...
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 ...
Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.
In the following, the image is segmented into non-brain and brain tissue, with the latter usually being sub-segmented into at least gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Since image voxels near the class boundaries do not generally contain just one kind of tissue, partial volume effects ensue that can be corrected for.
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