Medical Image Registration - Groups

ACDC Challenge and M&Ms Challenge

The ACDC challenge and M&Ms challenge datasets are used for evaluating the proposed method.

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Medical Image Registration via Neural Fields

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NLST dataset

A large-scale lung nodule dataset with pathology- or follow-up-confirmed benign/malignant labels for low-dose and noncontrast CTs.

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SR-Reg

A public benchmark brain MR-CT registration dataset named SR-Reg is utilized in this paper.

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WORD

The WORD dataset is used for deformable image registration. The dataset consists of 150 abdominal CT scans from 150 patients with 30495 slices.

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BTCV

The Swin Transformer-based TransMorph dataset is used for deformable image registration. The dataset consists of 50 abdominal CT scans, each scan with 13 organ annotations.

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Multi-modal volume registration by maximization of mutual information

Multi-modal volume registration by maximization of mutual information.

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General Vision Encoder Features as Guidance in Medical Image Registration

General vision encoders like DINOv2 and SAM have recently transformed computer vision. Even though they are trained on natural images, encoder models have excelled in medical...

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Learning Physics-Inspired Regularization for Medical Image Registration with ...

Medical image registration aims to identify the spatial deformation between images of the same anatomical region and is fundamental to image-based diagnostics and therapy.

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9 datasets found