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20202024
most citedDisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms using Self-adversarial Learning

2 citations · 4 across the 12 of their papers we have counts for

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6 papers · 1 filter

eess.IV2024

Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms

Xin Wang, Tao Tan, Yuan Gao +9

Precision breast cancer (BC) risk assessment is crucial for developing individualized screening and prevention. Despite the promising potential of recent mammogram (MG) based deep…

eess.IV2024

Non-Adversarial Learning: Vector-Quantized Common Latent Space for Multi-Sequence MRI

Luyi Han, Tao Tan, Tianyu Zhang +7

Adversarial learning helps generative models translate MRI from source to target sequence when lacking paired samples. However, implementing MRI synthesis with adversarial learning…

eess.IV2024

To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detection

Luyi Han, Tao Tan, Tianyu Zhang +7

Clinicians compare breast DCE-MRI after neoadjuvant chemotherapy (NAC) with pre-treatment scans to evaluate the response to NAC. Clinical evidence supports that accurate longitudin…

eess.IV2023★ 2 cited

Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism

Tianyu Zhang, Luyi Han, Anna D'Angelo +7

Magnetic resonance imaging (MRI) is the most sensitive technique for breast cancer detection among current clinical imaging modalities. Contrast-enhanced MRI (CE-MRI) provides supe…

eess.IV2023

An Explainable Deep Framework: Towards Task-Specific Fusion for Multi-to-One MRI Synthesis

Luyi Han, Tianyu Zhang, Yunzhi Huang +6

Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons. To address th…

eess.IV2023

IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data

Tianyu Zhang, Tao Tan, Luyi Han +5

Magnetic resonance imaging (MRI) is highly sensitive for lesion detection in the breasts. Sequences obtained with different settings can capture the specific characteristics of les…