Update translations from SlicerLanguageTranslations

Tutorials/STC-GEN-101_WelcomeTutorial/Translations/text_dict_hy.json

@@ -0,0 +1,49 @@
+{
+  "0_TextBox_0": "Slicer Welcome",
+  "0_TextBox_1": "Sonia Pujol, Ph.D.",
+  "0_TextBox_3": "Assistant Professor of Radiology\n\nBrigham and Women’s Hospital\n\nHarvard Medical School\n",
+  "1_Goal_title": "Goal",
+  "1_Goal_body": "This tutorial is a short introduction to the Welcome module of the Slicer open-source software.",
+  "2_TextBox_0": "Slicer5 Basics",
+  "3_TextBox_0": "Slicer5 Basics",
+  "2_TextBox_1": "*Slicer is an open-source software for segmentation, registration and visualization of medical imaging data.\n*The platform is developed through a multi-institution effort of several NIH funded large-scale consortia.\n*Slicer is for medical research only, and is not FDA approved. ",
+  "3_TextBox_1": "3D Slicer 5 version 5.10.0 includes over 100 modules and more than 190 extensions for image segmentation, registration and 3D visualization of medical imaging data.",
+  "4_TextBox_0": "Supported Platforms",
+  "4_TextBox_1": "*Slicer is a multi-platform software developed and maintained on Mac OSX, Linux and Windows.\n\n*Slicer requires a minimum of 2 GB of RAM and a dedicated graphic accelerator with 64 MB of on-board graphic memory. ",
+  "5_WelcometoSlicer_title": "Welcome to Slicer",
+  "5_TextBox_1": "Each module of Slicer includes a series of tabs, which give access to different functionalities.\n\nClick on the arrow symbol to display the content of each tab. ",
+  "6_SlicerUserInterface_title": "Slicer User Interface",
+  "6_ArrowText_0": "Toolbar",
+  "6_TextBox_1": "3D viewer",
+  "6_TextBox_3": "User Interface (UI) panel of the Slicer Welcome Module",
+  "6_TextBox_5": "Data probe",
+  "6_ArrowText_6": "2D anatomical viewers",
+  "7_WelcomeModule_title": "Welcome Module",
+  "8_WelcomeModule_title": "Welcome Module",
+  "12_WelcomeModule_title": "Welcome Module",
+  "7_TextBox_1": "The Documentation & Tutorials tab contains links to the training compendium and documentation pages of 3D Slicer.",
+  "8_TextBox_0": "The Welcome module panel contains shortcuts for loading different types of data. A series of sample data are also available.\n\nClick on Download Sample Data to access the Sample Data Module",
+  "9_SampleData_title": "Sample Data",
+  "10_SampleData_title": "Sample Data",
+  "11_SampleData_title": "Sample Data",
+  "9_TextBox_1": "The Sample Data module contains links to different sample datasets that can be downloaded into Slicer.",
+  "10_TextBox_0": "Brain MR",
+  "10_TextBox_1": "Chest CT",
+  "10_TextBox_2": "Cardiac CT",
+  "10_TextBox_3": "Diffusion Tensor Imaging (DTI) Dataset",
+  "10_TextBox_4": "Brain MRI (tumor patient)",
+  "11_ArrowText_0": "Click on MRHead to download the\ndataset in Slicer.",
+  "12_TextBox_0": "The MR scan of the brain appears\nin the 2D viewers.",
+  "13_MRBrainSampleDataset_title": "MR Brain Sample Dataset",
+  "14_MRBrainSampleDataset_title": "MR Brain Sample Dataset",
+  "15_MRBrainSampleDataset_title": "MR Brain Sample Dataset",
+  "13_TextBox_0": "Position the mouse on the little pin icon in the top left corner of the red viewer to display the viewer menu",
+  "14_TextBox_1": "Click on the link icon to link all three 2D viewers, and on the eye icon next to it\nto display the slices in the 3D viewer",
+  "15_TextBox_0": "The axial, coronal and sagittal slices appear in the 3D viewer.\nGo back to the Welcome module using the green arrow in the toolbar",
+  "16_GoingFurther_title": "Going Further",
+  "17_TextBox_0": "Going Further",
+  "16_TextBox_0": "To learn more about Slicer and its different functionalities, visit the Slicer Compendium",
+  "17_TextBox_1": "https://training.slicer.org/",
+  "18_TextBox_0": "Acknowledgements",
+  "18_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n\nChan Zuckerberg Initiative (CZI)"
+}

Tutorials/STC-GEN-102_FourMinuteTutorial/Translations/text_dict_hy.json

@@ -0,0 +1,39 @@
+{
+  "0_TextBox_0": "Slicer4 Minute\n",
+  "0_TextBox_1": "Sonia Pujol, Ph.D.",
+  "0_TextBox_3": "Assistant Professor of Radiology\nBrigham and Women’s Hospital\nHarvard Medical School",
+  "1_TextBox_0": "Slicer4 minute tutorial",
+  "16_TextBox_0": "Slicer4 minute tutorial",
+  "1_TextBox_1": "This tutorial is a 4-minute introduction to the 3D visualization capabilities of the Slicer5 software for medical image analysis. ",
+  "2_TextBox_0": "Slicer5 software & dataset",
+  "2_TextBox_1": "*Download the Slicer5 software available at http://download.slicer.org\n\n*Download the Slicer4minute dataset available at https://www.slicer.org/wiki/Documentation/4.10/Training",
+  "3_3DSlicerversion5_title": "3D Slicer version 5",
+  "4_TextBox_0": "3D Slicer Scene",
+  "4_TextBox_1": "*A Slicer scene is a MRML (Medical Reality Modeling Language) file that contains a list of elements loaded into Slicer (volumes, models, fiducials, transforms, etc.)\n*In the following example, we use a scene 'Slicer4minute.mrml' composed of an MRI scan and 3D models of the head. \n*The scene file and datasets have been saved as a MRB (Medical Reality Bundle) file. \n*The MRB file format is Slicer's archive file format.",
+  "5_LoadingtheSlicer4minutedataset_title": "Loading the Slicer4minute dataset",
+  "5_TextBox_1": "Drag and drop the slicer4minute.mrb to load the scene in Slicer",
+  "6_Slicer4minuteScene_title": "Slicer4minute Scene",
+  "6_TextBox_1": "Slicer displays the elements of the slicer4minute scene. The scene contains and MRI scan and 3D surface models of the brain.",
+  "7_3DVisualization_title": "3D Visualization",
+  "9_3DVisualization_title": "3D Visualization",
+  "10_3DVisualization_title": "3D Visualization",
+  "11_3DVisualization_title": "3D Visualization",
+  "13_3DVisualization_title": "3D Visualization",
+  "14_3DVisualization_title": "3D Visualization",
+  "15_3DVisualization_title": "3D Visualization",
+  "7_TextBox_0": "Select the module Models",
+  "8_3Dvisualization_title": "3D visualization",
+  "8_TextBox_0": "Click on the pin icon on the top left corner of the red slice to display the slice Viewer menu.\nClick on the eye to display the axial slice in the 3D viewer",
+  "9_TextBox_1": "Use the slider of the red viewer to browse through the axial MR slices. \n\nSlicer simultaneously displays the axial slice in the 3D viewer",
+  "10_TextBox_0": "Select the Skin model and lower its opacity using the Opacity slider in the 3D Display tab",
+  "10_TextBox_1": "The skull_bone.vtk model appears through the skin.",
+  "11_TextBox_0": "Position the mouse in the 3D viewer, click on the left-mouse button to drag and rotate the model. \nClick on the right-mouse button to zoom in and out",
+  "12_AnatomicalViews_title": "Anatomical Views",
+  "12_TextBox_0": "Click on the pin icons in the top left corner of the red and green viewer to display the slice viewer menu\n\nClick on the eye icon to display the axial and coronal slice in the 3D viewer",
+  "13_TextBox_0": "Turn off the visibility of the skull to display the brain white matter model",
+  "14_TextBox_0": "The white matter surface, as well as the left and right optic nerves, appear in the viewer",
+  "15_TextBox_0": "Select the hemispheric_white_matter.vtk model\n\nCheck Clipping in the 3D Display tab\n\nIn the Clipping Planes tab, select the option 'Green Slice Clipping' and check 'Negative'",
+  "16_TextBox_1": "*This tutorial was a short introduction on interactive 3D visualization of MRI data and 3D models in Slicer.\n\n*The Slicer5 training compendium contains a series of tutorials and pre-computed datasets to learn how to use the software.",
+  "17_TextBox_0": "Acknowledgements",
+  "17_TextBox_1": "National Alliance for Medical Image\nComputing\nNIH U54EB005149\n\nNeuroimage Analysis Center\nNIH P41EB015902\n"
+}

Tutorials/STC-SEG-103_AIBasedSegmentationIn3DSlicer/Translations/text_dict_hy.json

@@ -0,0 +1,49 @@
+{
+  "0_TextBox_0": "AI-based Segmentation in 3D Slicer",
+  "0_TextBox_1": "Sonia Pujol, Ph. D. \nBrigham and Women's Hospital,\nHarvard Medical School\nBoston, MA",
+  "0_TextBox_3": "Slicer Ribeirão Preto Workshop\nJune 30, 2025",
+  "1_TextBox_0": "Manual vs AI-powered Segmentation",
+  "2_TextBox_0": "Manual vs AI-powered Segmentation",
+  "1_TextBox_1": "Medical images have traditionally been manually segmented, which is a time-consuming process that requires intensive effort by radiologists and is subject to inter-reader variability.",
+  "2_TextBox_1": "In the past decade, image segmentation has been powered by the development of deep learning algorithms (e.g. nnUnet by the German Cancer Research Center (DKFZ)/Helmholtz Research).\n\n\nAI-powered segmentation tools can reduce the segmentation time and provide more reproducible results.",
+  "3_TextBox_0": "AI Terminology",
+  "3_TextBox_1": "A Model is an AI algorithm that was trained to perform a specific task (e.g. brain tumor segmentation model).\n\nThe Weights of an AI model are small numbers that determine how much importance the model gives to different image features.\n\nDuring the Training phase, a model learns patterns from data labelled by experts and adjusts its weights to improve its predictions.\n\nDuring the Validation/Test phase, the model is evaluated on a separate set of data not used during the Training phase.\n\nDuring Inference, the model is applied to new datasets to perform the specific task it was trained for.",
+  "4_TextBox_0": "3D Slicer AI Tutorial",
+  "4_TextBox_1": "This tutorial focuses on running inference tasks using various pre-trained AI models for automated segmentation of anatomical and pathological structures.",
+  "5_TextBox_0": "MONAIAuto3DSeg Slicer extension",
+  "6_TextBox_0": "MONAIAuto3DSeg Slicer extension",
+  "5_TextBox_1": "This tutorial uses the pre-trained models of the MONAIAuto3DSeg Slicer extension.\n\n\nThe tool is designed to work on laptops or on average desktop computer without a GPU.",
+  "6_TextBox_1": "Multiple modalities Support (CT, MRI).\n\n\nMultiple anatomies (head, thorax, abdomen, pelvis, etc.).\n\n\nMultiple pathologies (tumor, hemorrhage, edema).",
+  "7_TextBox_0": "Slicer AI Tutorial: Segmentation Tasks",
+  "7_TextBox_1": "Segmentation Task #1: Prostate \n\n\nSegmentation Task #2: Brain Glioma \n\n\nSegmentation Task #3: Whole Body Segmentation",
+  "8_TextBox_0": "AI Segmentation Task #1: Prostate",
+  "9_TextBox_1": "AI-based Segmentation of Peripheral Zone (PZ) and Transition Zone (TZ) of the prostate on T2-weighted MRI Images.\n\n\nDataset:\nmsd_prostate_01-t2\nmsd_prostate_01-adc",
+  "10_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose Directory to Add and browse to the location of the Slicer datasets\n\nSelect the dataset3_ProstateMRI and click on Open",
+  "11_TextBox_0": "Slicer loads the prostate MRI dataset",
+  "12_TextBox_0": "Click on Welcome to Slicer in the Modules' menu and browse to the category Segmentation\n\nSelect the MONAIAuto3DSeg module",
+  "13_TextBox_0": "Enter the model's name Prostate in the Segmentation model menu",
+  "13_TextBox_1": "Select the model Prostate - Multisequence",
+  "14_TextBox_0": "Enter the Input T2 volume msd-prostate-01-t2 and the Input ADC volume msd-prostate-01-adc",
+  "14_TextBox_1": "Click on Create new segmentation on Apply",
+  "15_TextBox_0": "Slicer starts the inference",
+  "16_TextBox_0": "Slicer shows the results of the AI-based prostate segmentation",
+  "17_TextBox_0": "AI Segmentation Task #2: Brain Glioma",
+  "18_TextBox_1": "AI-based Segmentation of Neoplasm, Necrosis and Edema in Brain MRI images.\n\n\nDatasets:\n1) BraTS-GLI_00005-000-t1n (T1-weighted)\n2) BraTS-GLI_00005-000-t1c (T1-weighted post-Gd)\n3) BraTS-GLI_00005-000-t2w (T2-weighted)\n4) BraTS-GLI_00005-000-t2f (T2-FLAIR )",
+  "19_TextBox_1": "Click on Add Data in the Welcome to Slicer module\n\nClick on Choose File(s) to Add and browse to the location of the Slicer datasets\n\nIn the subdirectory dataset4_BrainMRI_Glioma, select the four datasets BraTS-GLI-00006-t1c.nii.gz, BraTS-GLI-00006-t1n.nii.gz, BraTS-GLI-00006-t2f.nii.gz, BraTS-GLI-00006-t2w.nii.gz\n\nClick on Open",
+  "20_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Brain Tumor Segmentation in the Segmentation model menu",
+  "20_TextBox_1": "Select the model Brain Tumor Segmentation (BRATS) GLI",
+  "21_TextBox_0": "Enter the input volumes as follows:\n\nInput T2F volume: BraTS-GLI_00005-000-t2f\nInput T1C volume: BraTS-GLI_00005-000-t1c\nInput T1N volume: BraTS-GLI_00005-000-t1n\nInput T2W volume: BraTS-GLI_00005-000-t2w\n\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation",
+  "22_TextBox_1": "Slicer starts running the inference task\n\nOnce the segmentation is done, 'Processing finished' appears in the Slicer GUI",
+  "23_TextBox_1": "Click on Show 3D to display the 3D segments in the 3D Viewer",
+  "24_TextBox_0": "AI Segmentation Task #3: Whole Body Segmentation",
+  "25_TextBox_1": "AI-based Segmentation of the whole body.\n\n\nDataset:\nCT_ThoraxAbdomen",
+  "26_TextBox_0": "In the Add DICOM Data module, select the Patient patient1 and double click onthe image CT_Thorax_Abdomen to load it in Slicer",
+  "27_TextBox_0": "Select the module MONAIAuto3DSeg and enter the model's name Whole Body Segmentation in the Segmentation model menu",
+  "27_TextBox_1": "Select the model Whole Body Segmentation TS1-quick",
+  "28_TextBox_0": "Select the input Volume 6:CT_Thorax_Abdomen,\n\nClick on Create new Segmentation on Apply\n\nClick on Apply to start the segmentation",
+  "29_TextBox_0": "Slicer displays the results of the AI-based segmentation using the Whole Body Segmentation TS1-quick",
+  "30_TextBox_0": "Conclusion",
+  "30_TextBox_1": "The 3D Slicer MONAIAuto3DSeg extension provides fast AI-based segmentation of anatomical and pathological structures.\n\n\nThe module can run on standard laptop and desktop computers with no GPU.",
+  "31_TextBox_0": "Acknowledgements",
+  "31_TextBox_1": "The 3D Slicer internationalization project and the 3D Slicer for Latin America project have been made possible through funding by the Chan Zuckerberg Initiative."
+}