Medical Imaging Toolbox

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Medical Imaging Toolbox

Visualize, register, segment, and label 2D and 3D medical images

Importing Medical Imaging Data

Read image data and metadata from specialized medical file formats, such as DICOM, NIfTI, and NRRD, that store data describing the patient, imaging procedure, and spatial referencing.

Visualizing 2D Images and 3D Volumes

Use interactive tools to visualize 2D and 3D medical imaging data. Generate and render 3D surfaces and volumes.

Ground Truth Labeling

Use the Medical Image Labeler app to interactively label ground truth data, semi-automate or automate the labeling process, and export labeled data for AI workflows.

Preprocessing and Augmentation

Improve image quality using preprocessing techniques and improve the effectiveness of deep learning networks using random intensity augmentation to expand the training dataset.

Medical Image Registration

Compare multimodal medical images, volumes, or surfaces using image registration to align them to a common coordinate system.

Segmentation

Segment 2D images or 3D volumes into regions such as bones, tumors, or organs using traditional or deep learning techniques, and evaluate the accuracy of the regions.

“Diagnosis of Thyroid Nodules from Medical Ultrasound Images with Deep Learning ”

By Eunjung Lee, School of Mathematics and Computing (CSE), Yonsei University

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