MUST-ABUS: Multi-View Automated Breast Ultrasound Registration and Stitching Benchmark

Dataset Summary

MUST-ABUS is a registration-centered benchmark for multi-view Automated Breast Ultrasound (ABUS) under partial-overlap and slice-level misalignment conditions. It supports unsupervised AP--MED and AP--LAT cross-view image registration, with registration-guided stitching used as downstream validation.

The cohort contains 356 retained view-specific 3D ABUS volumes from 90 subjects examined between 2020 and 2022. From these volumes, 25,692 cross-view 2D image pairs were constructed. The release includes de-identified retained source volumes, preprocessed image pairs, valid-region masks, pair correspondence files, and official patient-level splits.

Supported Tasks

• Cross-view ABUS image registration
• Cross-view correspondence estimation
• Registration-guided image stitching
• Partial-overlap-aware registration evaluation

MUST-ABUS is not designed for lesion detection, tumor segmentation, or diagnostic classification.

Dataset Structure

Source volumes

• 90 subjects
• 356 retained 3D view volumes: 136 AP, 126 LAT, and 94 MED
• 330 frames per volume, with each frame measuring 482 x 841 pixels
• GE Healthcare Invenia ABUS system with a C15-6XW transducer

Derived benchmark pairs

• 25,692 AP--MED and AP--LAT image pairs
• 10,744 AP--MED pairs
• 14,948 AP--LAT pairs
• Valid-region masks and pair-level metadata

Official patient-level split

Split	Subjects	Image pairs	Retained volumes
Train	72	20,554	297
Validation	9	2,569	31
Test	9	2,569	28
Total	90	25,692	356

All data from the same subject are assigned to one split to prevent subject-level leakage.

Annotations and Metadata

Each benchmark sample contains a partially overlapping AP--MED or AP--LAT slice pair, corresponding valid-region masks, and pair metadata. Released metadata include anonymized subject identifiers, breast side, view labels, slice identifiers, volume dimensions, and non-identifying acquisition parameters.

The dataset does not include manually annotated dense deformation fields, pixel-level stitched ground truth, or lesion-level diagnostic annotations. Valid-region masks identify effective ultrasound imaging regions and are not tumor or lesion masks.

Ethics, Privacy, and Intended Use

This retrospective single-center study was approved by the appropriate institutional Ethics Review Committee, which waived written informed consent. Direct identifiers are removed or replaced, anonymous study identifiers are used, and image content is checked for burned-in identifying information before release.

MUST-ABUS is intended for academic research on image registration, cross-view correspondence estimation, registration-guided stitching, and related medical-image analysis. Users must comply with the dataset license and data-use terms and must not attempt to re-identify any subject.

Limitations

• The dataset is from a single clinical institution and one acquisition system.
• Breast-side and view availability vary across subjects.
• Adjacent slices from the same volume are correlated and should not be treated as independent clinical cases.
• The dataset provides no dense deformation ground truth or lesion-level diagnostic labels.

Citation

Citation information and the persistent dataset DOI will be added when the benchmark paper and versioned archive record are finalized.