Julia library for visualization and annotation medical images, specialized particularly for rapid development segmentation of 3 dimensional images like CT or PET/CT scans. Has full support of nuclear medicine Data.
explain what is Texturespec object and how it is used in MedEye3D
Describe the role of each field and show print screens of how he change affect display
explain how different configurations are suitable for different kinds of medical imaging modalities (for example that CT is displayed in black and white and PET data in color scale; labels in discrete colors)
Expected Outcomes
Creating tutorial that will meet all requirements; consider doing also a video
Creating tutorial that show how to configure the window size, and how to display text including metrics from MedEval. Tutorial should involve loading data from some public repository like spleen dataset from medical decathlon [1], consider adding also video tutorial.
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Given the most common PET and MRI modalities (random FDG PET/CT, and T2, T1, FLAIR, ADC, DWI on MRI) - the user will see the image similar to what is automatically displayed in 3DSlicer
Success criteria
The user can load 2 different images, and they would display concurrently one next to the other. During scrolling the same area of the body should be displayed (for well-registered sample images) based on the supplied metadata. While moving the mouse cursor on one image the position of the cursor in the same physical spot on the other image should be displayed (physical location calculated from spatial metadata).
Success when
Given an integer mask where a unique integer value will encode information about a single supervoxel and an underlying 3d medical image user will have the option to overlay the original image with the borders of the superpixels where adjacent borders will have different colors, or show those borders on the background of the image convolved with edge filter, for example, Sobel filter